This is the reference guide for AllegroGraph 3.3. The overview tutorial can be found here. An introduction to AllegroGraph covering all of its many features at a high-level is in the AllegroGraph Introduction.
Conceptual Triple-Store Structure
AllegroGraph is a graph database that makes an excellent RDF triple-store. This is a conceptual diagram of the data AllegroGraph manages:
- The bulk of an AllegroGraph triple-store is composed of assertions called triples. For historical reasons, each triple has five fields:
- subject (s)
- predicate (p)
- object (o)
- graph (g)
- triple-id (i)
All of s, p, o, and g are strings of arbitrary size. String data is associated with Unique Part Identifiers (UPIs) and managed by the string dictionary.
To speed queries, AllegroGraph creates indices which contain the assertions plus additional information (see below for more details).
AllegroGraph can also perform freetext searching in the assertions using its freetext indices (see the section on freetext indexing for details).
and Finally, AllegroGraph keeps track of deleted triples
Each assertion can be viewed as an edge p
between graph nodes s
and o
with additional data g
or as the statement "subject predicate object (in the context of graph)".
Triple-data generally comes into AllegroGraph as strings either from pure RDF/XML or as the more verbose but simpler N-Triple format. Once the triples are in AllegroGraph, it is possible to manipulate them, perform logical inference, and execute extremely fast queries.
The string dictionary manages efficient storage and fast lookup of the strings in the triple-store. We call the process of hashing a string into its UPI and storing it in the string dictionary interning.
Basic Triple-Store Operations
Adding Triples
Triples stored in files using the N-Triples 1 , RDF/XML 2 , and other formats can be loaded into the triple-store with the following functions.
Add triples from source
to the triple store.
Returns (as multiple values) the count of triples loaded and the UPI of the graph into which the triples were loaded.
source
- can be a stream, a pathname to an N-Triples file, a file URI, an HTTP URI or a string that can be coerced into a pathname. Source can also be a list of any of these things. In this case, each item in the list will be imported in turn. This can be more efficient than iterating over the items yourself since AllegroGraph will only synchronize at the end of the loading.
In the case where a list of sources is being loaded and the graph
argument is :source
, each item in the list will be associated with the URI specifying it. In this case, the second return value will be nil
.
The following keyword parameters can be used to control the loading process:
:db
- specifies the triple-store into which triples will be loaded. This defaults to the value of *db*.:graph
- the graph to which the triples fromsource
will be placed. It defaults tonil
which is interpreted asdb
's default graph. If supplied, it can be:a string representing a URIref, or a UPI or future-part encoding a URIref, which adds the triples in source to a graph named by that URI
the keyword
:source
(in which case the source argument will be interned as a URI and the loaded triples added to a graph named by that URI). This has the effect of associating the file or URL of source with the new triples.
:verbose
- specifies whether or not progress information is printed as triples are loaded. It defaults to the value of (ag-property
:verbose)
.:always-save-string-literals
- determine whether or not to save the strings of a triple's object field when the object can be encoded directly into the triple. If true (the default) then the strings will be saved. If false, then only the encoded values will be preserved (this may prevent exact round-trips if data is coerced during the encoding process).:continue-on-error-p
- determine how the parser should behave if it encounters an error parsing or adding a triple. It can be one of:nil
- meaning to raise the error normally,t
- meaning to ignore the error and continue parsing with the next line in the source,a function of four arguments: a parsing helper data structure, the line in the source where the problem was encountered, the condition that caused the error and the arguments (if any) to that condition.
You can use continue-on-error-p
to print all of the problem lines in a file using something like
(load-ntriples
"source"
:continue-on-errorp
(lambda (helper source-line condition &rest args)
(declare (ignore helper args))
(format t "~&Error at line ~:6d - ~a" source-line condition)))
load-ntriples
returns the number of triples added, and the graph used, as multiple values.
Add all of the triples from the string
to the triple store.
The following keyword parameters can be used to control the loading process:
:db
- specifies the triple-store into which triples will be loaded. This defaults to the value of *db*.:graph
- the graph to which the triples fromsource
will be placed. It defaults tonil
which is interpreted asdb
's default graph. If supplied, it can be:a string representing a URIref, or a UPI or future-part encoding a URIref, which adds the triples in source to a graph named by that URI
the keyword
:source
(in which case the source argument will be interned as a URI and the loaded triples added to a graph named by that URI). This has the effect of associating the file or URL of source with the new triples.
:verbose
- specifies whether or not progress information is printed as triples are loaded. It defaults to the value of (ag-property
:verbose)
.:always-save-string-literals
- determine whether or not to save the strings of a triple's object field when the object can be encoded directly into the triple. If true (the default) then the strings will be saved. If false, then only the encoded values will be preserved (this may prevent exact round-trips if data is coerced during the encoding process).:continue-on-error-p
- determine how the parser should behave if it encounters an error parsing or adding a triple. It can be one of:nil
- meaning to raise the error normally,t
- meaning to ignore the error and continue parsing with the next line in the source,a function of four arguments: a parsing helper data structure, the line in the source where the problem was encountered, the condition that caused the error and the arguments (if any) to that condition.
You can use continue-on-error-p
to print all of the problem lines in a file using something like
(load-ntriples
"source"
:continue-on-errorp
(lambda (helper source-line condition &rest args)
(declare (ignore helper args))
(format t "~&Error at line ~:6d - ~a" source-line condition)))
load-ntriples-from-string
returns the number of triples added, and the graph used, as multiple values.
Add triples from the named RDF/XML file to the triple-store.
Returns the number of triples added.
The additional arguments are:
:db
- specifies the triple-store into which triples will be loaded; defaults to the value of *db*.:base-uri
- this defaults to the name of the file from which the triples are loaded. It is used to resolve relative URI references during parsing. To use no base-uri, use the empty string "".:graph
- the graph to which the triples fromsource
will be placed. It defaults tonil
which is interpreted asdb
's default graph. If supplied, it can be:a string representing a URIref, or a UPI or future-part encoding a URIref, which adds the triples in source to a graph named by that URI
the keyword
:source
(in which case the source argument will be interned as a URI and the loaded triples added to a graph named by that URI). This has the effect of associating the file or URL of source with the new triples.
use-rapper-p
- Ifuse-rapper-p
is true, then the RDF/XML file will be piped through the open source tool rapper using run-shell-command. Obviously, rapper must be both installed and in your path for this to work. If rapper is not in your path, you can supply it explicitly as the value ofuse-rapper-p
.
Treat string
as an RDF/XML data source and add it to the triple-store. For example:
(load-rdf/xml-from-string
"<?xml version=\"1.0\"?>
<rdf:RDF xmlns:rdf=\"http://www.w3.org/1999/02/22-rdf-syntax-ns#\"
xmlns:ex=\"http://example.org/stuff/1.0/\">
<rdf:Description rdf:about=\"http://example.org/item01\">
<ex:prop rdf:parseType=\"Literal\"
xmlns:a=\"http://example.org/a#\"><a:Box required=\"true\">
<a:widget size=\"10\" />
<a:grommit id=\"23\" /></a:Box>
</ex:prop>
</rdf:Description>
</rdf:RDF>
")
See load-rdf/xml for details on the parser and the other arguments to this function.
Add triples from source
to the triple store.
Returns (as multiple values) the count of triples loaded and the UPI of the graph into which the triples were loaded.
source
- can be a stream, a pathname to an N-Triples file, a file URI, an HTTP URI or a string that can be coerced into a pathname. Source can also be a list of any of these things. In this case, each item in the list will be imported in turn. This can be more efficient than iterating over the items yourself since AllegroGraph will only synchronize at the end of the loading.
In the case where a list of sources is being loaded and the graph
argument is :source
, each item in the list will be associated with the URI specifying it. In this case, the second return value will be nil
.
The following keyword parameters can be used to control the loading process:
:db
- specifies the triple-store into which triples will be loaded. This defaults to the value of *db*.:graph
- the graph to which the triples fromsource
will be placed. It defaults tonil
which is interpreted asdb
's default graph. If supplied, it can be:a string representing a URIref, or a UPI or future-part encoding a URIref, which adds the triples in source to a graph named by that URI
the keyword
:source
(in which case the source argument will be interned as a URI and the loaded triples added to a graph named by that URI). This has the effect of associating the file or URL of source with the new triples.
:verbose
- specifies whether or not progress information is printed as triples are loaded. It defaults to the value of (ag-property
:verbose)
.:always-save-string-literals
- determine whether or not to save the strings of a triple's object field when the object can be encoded directly into the triple. If true (the default) then the strings will be saved. If false, then only the encoded values will be preserved (this may prevent exact round-trips if data is coerced during the encoding process).:continue-on-error-p
- determine how the parser should behave if it encounters an error parsing or adding a triple. It can be one of:nil
- meaning to raise the error normally,t
- meaning to ignore the error and continue parsing with the next line in the source,a function of four arguments: a parsing helper data structure, the line in the source where the problem was encountered, the condition that caused the error and the arguments (if any) to that condition.
You can use continue-on-error-p
to print all of the problem lines in a file using something like
(load-ntriples
"source"
:continue-on-errorp
(lambda (helper source-line condition &rest args)
(declare (ignore helper args))
(format t "~&Error at line ~:6d - ~a" source-line condition)))
load-ntriples
returns the number of triples added, and the graph used, as multiple values.
Add all of the triples from the string
to the triple store.
Returns (as multiple values) the count of triples loaded and the UPI of the graph into which the triples were loaded.
The strings should be in N-Quad format.
The following keyword parameters can be used to control the loading process:
:db
- specifies the triple-store into which triples will be loaded. This defaults to the value of *db*.:graph
- the graph to which the triples fromsource
will be placed. It defaults tonil
which is interpreted asdb
's default graph. If supplied, it can be:a string representing a URIref, or a UPI or future-part encoding a URIref, which adds the triples in source to a graph named by that URI
the keyword
:source
(in which case the source argument will be interned as a URI and the loaded triples added to a graph named by that URI). This has the effect of associating the file or URL of source with the new triples.
:verbose
- specifies whether or not progress information is printed as triples are loaded. It defaults to the value of (ag-property
:verbose)
.:always-save-string-literals
- determine whether or not to save the strings of a triple's object field when the object can be encoded directly into the triple. If true (the default) then the strings will be saved. If false, then only the encoded values will be preserved (this may prevent exact round-trips if data is coerced during the encoding process).:continue-on-error-p
- determine how the parser should behave if it encounters an error parsing or adding a triple. It can be one of:nil
- meaning to raise the error normally,t
- meaning to ignore the error and continue parsing with the next line in the source,a function of four arguments: a parsing helper data structure, the line in the source where the problem was encountered, the condition that caused the error and the arguments (if any) to that condition.
You can use continue-on-error-p
to print all of the problem lines in a file using something like
(load-ntriples
"source"
:continue-on-errorp
(lambda (helper source-line condition &rest args)
(declare (ignore helper args))
(format t "~&Error at line ~:6d - ~a" source-line condition)))
load-ntriples-from-string
returns the number of triples added, and the graph used, as multiple values.
RDF in the form of named graphs can also be loaded using load-trix
, which understands the TriX format.
Load a TriX document into the triple store named by db
.
source
- a string or pathname identifying a file, or a stream.:db
- specifies the triple-store into which triples will be loaded; defaults to the value of *db*.:verbose
- if true, information about the load progress will be printed to*standard-output*
.:default-graph
- a future-part or UPI that identifies a graph, ornil
. If it is non-null, any graphs in the TriX document that are equal to the given URI will be treated as the default graph indb
.
default-graph
can also be the symbol :source
, in which case namestring
is called on the source and treated as a URI.
We have implemented a few extensions to TriX to allow it to represent richer data:
Graphs can be named by
<id>
, not just<uri>
. (A future revision might also permit literals.)The default graph can be denoted in two ways: by providing
<default/>
as the name for the graph; or by providing a graph URI as an argument toload-trix
.- In the interest of generality, the predicate position of a triple is not privileged: it can be a literal or blank node (just like the subject and object), not just a URI.
Load a string containing data in TriX format into db
string
- a string containing TriX data:db
- specifies the triple-store into which triples will be loaded; defaults to the value of *db*.:verbose
- if true, information about the load progress will be printed to*standard-output*
.:default-graph
- a future-part or UPI that identifies a graph, ornil
. If it is non-null, any graphs in the TriX document that are equal to the given URI will be treated as the default graph indb
.
See load-trix for more details.
Note that AllegroGraph calls sync-triple-store after the bulk load completes. Therefore, if you are loading many small files, you will find it much more efficient to use the method specialized on lists
and not iterate through the the list of files yourself:
;; pathnames is a list of files
;; let load-ntriples do the work of iterating over them
(load-ntriples pathnames)
;; Much slower!!
;; probably _NOT_ what you want to do
(dolist (pathname pathnames)
(load-ntriples pathname))
If you need to load a format that AllegroGraph does not yet support (for example, Turtle) we suggest you use the excellent free tool rapper from http://librdf.org/raptor/rapper.html to create either an N-Triples or RDF/XML file that AllegroGraph can load.
Note that both load-rdf/xml*
and load-ntriples*
have been removed from AllegroGraph 3.0 and beyond because their ability to load multiple triples sources simultaneously has been incorporated directly into load-rdf/xml and load-ntriples
Adding Programmatically
You can also add triples to a triple-store programatically with the function add-triple. The three required arguments, representing the subject, predicate, and object of the triple to be added can be expressed either as:
strings in the N-Triples syntax for URI references and literals;
UPIs such as are returned by the functions intern-resource, intern-literal, intern-typed-literal, and new-blank-node;
Encoded-UPIs created with functions like value->upi; or
future-parts created using the !-reader or with functions like literal or resource.
Add a new triple to the triple-store with the given subject, predicate and object and graph, specified either as UPIs or strings in N-Triples format. The :db
keyword argument specifies the triple store to which the triple will be added and defaults to the value of *db*. Returns the numeric id of the new triple.
Note that duplicate triples can be added to a triple-store but indices will only refer to the same triple once.
Triple Manipulation
Triple parts: Resources, Literals, UPIs and more
Each triple has five parts (!), a subject, a predicate, an object, a graph and a (unique, AllegroGraph assigned) ID. In RDF, the subject must be a "resource", i.e., a URI or a blank node. The predicate must be a URI. The object may be a URI, a blank node or a "literal". Literals are represented as strings with an optional type indicated by a URI or with a (human) language tag such as en
or jp
.
3 Blank nodes are anonymous parts whose identity is only meaningful within a given triple-store.
Resources, literals and blank nodes are represented as strings in RDF/XML or N-Triple syntax. AllegroGraph stores these strings in a string dictionary and hashes them to compute a Unique Part Identifier (UPI) for each string. A UPI is a length 12 octet array. One byte of the array is used to identify its type (e.g., is it a resource, a literal, or a blank node). The other 11-bytes are used to either store a hash of the string or to store an encoding of the UPIs contents (see type mapping below for more information about encoded UPIs).
From Strings to Parts
Resources and literals can be denoted with plain Lisp strings in the syntax used in N-Triples files. However this isn't entirely convenient since the N-Triples syntax for literals requires quotation marks which then need to be escaped when writing a Lisp string. For instance the literal whose value is "foo"
must be written in N-Triples syntax as "\"foo\""
. Similarly -- though not quite as irksome -- URIs must be written enclosed in angle brackets. The add-triple function cannot know how to interpret a string like "http://www.franz.com/simple#lastName"
and will signal an error. To refer to the resource in N-Triples syntax you must write "<http://www.franz.com/simple#lastName>"
. Literals with datatypes or language codes are even more cumbersome to write as strings, requiring both escaped quotation marks and other syntax.
To make it easier to produce correctly formatted N-Triple strings we provide two functions resource and literal. (The ! reader macro, discussed below, can also be used to produce future-parts and UPIs suitable to use as arguments for most of AllegroGraph's API.):
Create a new future-part with the provided values.
:language
- If provided,language
should be a valid RDF language tag.:datatype
- If provided, thedatatype
must be a resource. I.e., it can be a string representation of a URI (e.g., "http://foo.com/") or a future-part specifying a resource (e.g., !<http://foo.com>). If it does not specify a resource, a condition of type invalid-datatype-for-literal-error is signaled. An overview of RDF datatypes can be found in the W3C's RDF concepts guide.
Only one of datatype
and language
can be used at any one time. If both are supplied, a condition of type datatype-and-language-specified-error will be signaled.
Return the provided string as a future-part naming a resource. If namespace
is provided, then string
will be treated as a fragment and the future-part returned will be the URIref whose prefix is the string to which namespace
maps and whose fragment is string
. I.e., if the namespace prefix rdf
maps to <http://www.w3.org/1999/02/22-rdf-syntax-ns#>
, then the parts created by
(resource "Car" "rdf")
and
(resource "http://www.w3.org/1999/02/22-rdf-syntax-ns#Car")
will be the same.
Some examples (we will describe and explain the ! notation below):
> (resource "http://www.franz.com/")
!<http://www.franz.com/>
> (literal "Peter")
!"Peter"
> (literal "10" :datatype
"http://www.example.com/datatypes#Integer")
!"10"^^<http://www.example.com/datatypes#Integer>
> (literal "Lisp" :language "EN")
!"Lisp"@en
Another issue with using Lisp strings to denote literals and resources is that the strings must, at some point, be translated to the UPIs used internally by the triple-store. This means that if you are going to add a large number of triples containing the same resource or literal and you pass the resource or literal value as a string, add-triple will have to repeatedly convert the string into its UPI.
To prevent this repeated computation, you can use functions like intern-resource, intern-literal, or intern-typed-literal to compute the UPI of a string outside of the add-triple loop. The function new-blank-node (or the macro with-blank-nodes) can be used to produce the UPI of a new anonymous node for use as the subject or object of a triple.
Returns true if upi
is a blank node and nil otherwise. For example:
> (blank-node-p (new-blank-node))
t
> (blank-node-p (literal "hello"))
nil
Compute the UPI of the string URI
, make sure that it is stored in the string dictionary, and return the UPI.
:db
- specifies the triple-store into which theuri
will be interned. This defaults to the value of *db*.:upi
- if supplied, then thisupi
will be used to store theuri
's UPI; otherwise, a new UPI will be created using make-upi.
Compute the UPI of value
treating it as an untyped literal, possibly with a language tag. Ensure that the literal is in the store's string dictionary and return the UPI.
:language
- if supplied, then this language will be associated with the literalvalue
. See rfc-3066 for details on language tags.:db
- specifies the triple-store into which theuri
will be interned. This defaults to the value of *db*.:upi
- if supplied, then thisupi
will be used to store theuri
's UPI; otherwise, a new UPI will be created using make-upi.
Compute the UPI of value
treating it as an typed literal with datatype datatype
. Ensure that the literal is in the store's string dictionary and return the UPI.
value
- must be a stringdatatype
- a URI, a future-part specifying a URI or a UPI specifying a URI.:db
- specifies the triple-store into which theuri
will be interned. This defaults to the value of *db*.:upi
- if supplied, then thisupi
will be used to store theuri
's UPI; otherwise, a new UPI will be created using make-upi.
db
and return the UPI. If a upi is not passed in with the :upi parameter, then a new UPI structure will be created.
This convenience macro binds one or more variables to new blank nodes within the body of the form. For example:
(with-blank-nodes (b1 b2)
(add-triple b1 !rdf:type !ex:Person)
(add-triple b1 !ex:firstName "Gary")
(add-triple b2 !rdf:type !ex:Dog)
(add-triple b2 !ex:firstName "Abbey")
(add-triple b2 !ex:petOf b1))
The following example demonstrates the use of these functions. We use intern-resource to avoid repeatedly translating the URIs used as predicates into UPIs and then use new-blank-node to create a blank node representing each employee and intern-literal and intern-typed-literal to translate the strings in the list employee-data
into UPIs. (We could also use literal to convert the strings but using intern-literal
is more efficient.)
(defun add-employees (company employee-data)
(let ((first-name (intern-resource "http://www.franz.com/simple#firstName"))
(last-name (intern-resource "http://www.franz.com/simple#lastName"))
(salary (intern-resource "http://www.franz.com/simple#salary"))
(employs (intern-resource "http://www.franz.com/simple#employs"))
(employed-by (intern-resource "http://www.franz.com/simple#employed-by")))
(loop for (first last sal) in employee-data do
(let ((employee (new-blank-node)))
(add-triple company employs employee)
(add-triple employee employed-by company)
(add-triple employee first-name (intern-literal first))
(add-triple employee last-name (intern-literal last))
(add-triple
employee salary
(intern-typed-literal sal "http://www.franz.com/types#dollars"))))))
Note that the main difference between resource and intern-resource is that the former only computes the UPI of a string whereas the latter both does this computation and ensures that the string (and its UPI) are present in the triple-store's string dictionary. (The former also returns a future part whereas the latter returns a UPI).
Working with Triples
The functions subject, predicate, object, graph, and triple-id provide access to the part UPIs of triples returned by the cursor functions cursor-row and cursor-next-row or collected by get-triples-list.
Sets and gets the graph UPI of a triple.
In addition to being returned, the optional upi
argument will be filled in with the graph's UPI. If not passed in, a new UPI will be created.
Sets and gets the object UPI of a triple.
In addition to being returned, the optional upi
argument will be filled in with the object's UPI. If not passed in, a new UPI will be created.
Sets and gets the predicate UPI of a triple.
In addition to being returned, the optional upi
argument will be filled in with the predicate's UPI. If not passed in, a new UPI will be created.
Sets and gets the subject UPI of a triple.
In addition to being returned, the optional upi
argument will be filled in with the subject's UPI. If not passed in, a new UPI will be created.
triple
.
Working with UPIs
You can also create UPIs and triples programmatically; determine the type-code of a UPI, and compare them. You may want to make your own copy of a triple or UPI when using a cursor since AllegroGraph does not save triples automatically (see, e.g., iterate-cursor for more details).
If using encoded-triples or UPIs, then the functions upi->value and value->upi will be essential. You can also check the type of a UPI with either upi-type-code or upi-typep (see type-code->type-name and its inverse type-name->type-code for additional information.)
Copy a triple.
triple
- the triple to copynew
- (optional) If supplied, then this must be a triple and the copy oftriple
will be placed into it. Otherwise, a new triple will be created.
This function is useful if you want to keep a reference to a triple obtained from a cursor returned by query functions such as get-triples since the cursor reuses the triple data structure for efficiency reasons.
Create a copy of a UPI.
upi
- the UPI to copy.
triple1
and triple2
and returns true if they have the same contents and triple-id and false otherwise. See triple-contents= if you need to compare triples regardless of their IDs.
Decodes UPI and returns the value, the type-code and any extra information as multiple values.
upi
- the UPI to decode:db
- specifies the triple-store from which the UPI originates.
The value, type-code, and extra information are interpreted as follows:
- value - a string representing the contents of the UPI
- type-code - an integer corresponding to one of the defined UPI types (see supported-types for more information). You can use type-code->type-name to see the English name of the type.
- extra - There are three disjoint sets of literals in RDF:
- "simple literals" -- a string.
- literals with datatypes
- literals with language annotations.
A literal cannot have both a language and a datatype; if a literal has type-name
:literal-typed (i.e., its type-code
is 2), then the extra
value is a datatype URI; if its type-code
is 3, then extra
will be the language code.
Examples:
> (upi->value (value->upi 22 :byte))
22
18
nil
> (upi->value (upi (literal "hello" :language "en")))
"hello"
3
"en"
See value->upi for additional information.
type-code
of a UPI. This is a one-byte tag that describes how the rest of the bytes in the UPI should be interpreted. Some UPIs are hashed and their representation is stored in a string-table. Other UPIs encode their representation directly (see upi->value and value->upi for additional details).
Returns true if upi
has type-code type-code
.
upi
- a UPItype-code
- either a numeric UPI type-code or a keyword representing a type-code. See type-code->type-name and type-name->type-code for more information on type-codes and their translations.
upi-1
and upi-2
bytewise and return true if upi-1
is less than upi-2
.
thing
appears to be a UPI. Recall that every UPI is a octet array 12 bytes in length but not every length 12 octet array is a UPI. It is possible, therefore, that upip
will return true even if thing
is not a UPI.
Returns a UPI
that encodes value
using type encode-as
.
encode-as
can be a type-code or a type-name (see supported-types and type-name->type-code for details. If a upi
keyword argument is not supplied, then a new UPI will be created. See upi->value for information on retrieving the original value back from an encoded UPI.
Note that value->upi
can not create hashed UPIs (i.e., UPIs whose value must be stored in the string dictionary. To create these, use intern-resource and intern-literal.
Comparing parts of triples
triple
is the same as part
using part= for comparison. The part
may be a UPI, a string (in N-Triples syntax) that can be converted to a UPI, or a future-part. See graph-upi= if you know that you will be comparing UPIs.
triple
is the same as part
using part= for comparison. The part
may be a UPI, a string (in N-Triples syntax) that can be converted to a UPI, or a future-part. See object-upi= if you know that you will be comparing UPIs.
triple
is the same as part
using part= for comparison. The part
may be a UPI, a string (in N-Triples syntax) that can be converted to a UPI, or a future-part. See predicate-upi= if you know that you will be comparing UPIs.
triple
is the same as part
using part= for comparison. The part
may be a UPI, a string (in N-Triples syntax) that can be converted to a UPI, or a future-part. See subject-upi= if you know that you will be comparing UPIs.
triple
is the same as upi
using upi= for comparison. The upi
must be a UPI. See graph-part= if you need to compare future-parts or convert strings into UPIs.
triple
is the same as upi
using upi= for comparison. The upi
must be a UPI. See object-part= if you need to compare future-parts or convert strings into UPIs.
triple
is the same as upi
using upi= for comparison. The upi
must be a UPI. See predicate-part= if you need to compare future-parts or convert strings into UPIs.
triple
is the same as upi
using upi= for comparison. The upi
must be a UPI. See subject-part= if you need to compare future-parts or convert strings into UPIs.
Future-Parts and UPIs
Future-parts (which are discussed in detail in their own section) can take the place of UPIs in many of the functions above. For efficiencies sake, functions like upi= assume that they are called with actual UPIs. AllegroGraph provides more general functions for the UPI only variants when it makes sense to do so. For example, future-part= works only with future-parts whereas part= works equally well with any combination of UPIs, future-parts or even strings.
Return whatever is extra
in the string of the future-part. The meaning of extra depends on the type of the part:
- resource - the prefix (if applicable)
- typed-literal - the datatype
- language-literal - the language
- other - the value will always be
nil
See future-part-type and future-part-value if you need to access the part's other parts.
Return the value
of the future-part. The meaning of value depends on the type of the part:
- resource - the namespace (if any)
- typed-literal - the literal without the datatype
- language-literal - the literal without the language
- other - the value will always be
nil
See future-part-type and future-part-extra if you need to access the others parts (no pun intended) of the part.
Returns the UPI associated with the future-part future-part
.
If the future-part
uses namespaces, then calling upi
will resolve the namespace mapping. An error will be signaled if upi
is called and there is no namespace mapping defined. You can use the errorp
keyword parameter to disable the error and return nil
instead.
Querying Triples
You can get triples out of a triple-store as a list or a cursor. The list structure is convenient but unwieldy if your query returns millions of triples (since every triple must be returned before you will see any of them). A cursor is like a database cursor from the RDBMS-world. It lets you traverse through the results of your query one step at a time.
Cursors
Cursors supply the functions cursor-next, cursor-row, and cursor-next-p for basic forward iteration. For convenience we include cursor-next-row which advances the cursor and returns the next row immediately. Cursors reuse the triple
data-structure as they move through the result set so if you want to accumulate triples, make sure to use the copy-triple function.
cursor
has at least one more triple in it. Note that cursor-row, cursor-next and cursor-next-p are lower-level cursor manipulation routines. You may be better served by using collect-cursor, count-cursor, map-cursor and iterate-cursor.
Moves cursor
forward to the next triple in the collection.
Returns t
if there was another row on which to move and nil if the cursor is exhausted. I.e., if cursor-next
returns t
, then cursor-row will return a triple.
Note that cursor-row, cursor-next and cursor-next-p are lower-level cursor manipulation routines. You may be better served by using collect-cursor, count-cursor, map-cursor and iterate-cursor.
Returns the next triple from the cursor. The actual triple object returned is always the the same (eql
) object. If you want to hold onto a triple for use after you advance the cursor, use the function copy-triple to make a copy of the value returned by cursor-next-row
Note that cursor-row, cursor-next, cursor-next-row and cursor-next-p are lower-level cursor manipulation routines. You may be better served by using collect-cursor, count-cursor, iterate-cursor and map-cursor.
Returns the triple that cursor
is currently pointing at.
If the cursor is exhausted, then cursor-row
returns nil
.
Note that cursor-row, cursor-next and cursor-next-p are lower-level cursor manipulation routines. You may be better served by using collect-cursor, count-cursor, map-cursor and iterate-cursor.
There are several natural cursor idioms, the following functions handle many of them. We suggest building your own functions using these as building blocks since there may be internal optimizations made possible only through these. 4
cursor
and collect a list of its triples. The :transform
keyword can be used to modify the triples as they are collected. It defaults to the copy-triple function but you can use any function that takes one triple as an argument. (collect-cursor
reuses the row argument so make sure that you use copy-triple
in your own code if necessary).
Iterate over the triples in cursor
binding var
to each triple. Use the :count
keyword with a fixnum value to limit the maximum number of triples that iterate-cursor
visits. The binding to var
is the same EQ triple in each iteration. Make sure to use copy-triple if you are retaining any of the triples that you visit.
The macro creates a block nil around its expansion. If iteration finishes normally by satisfying the count or by exhausting the cursor, iterate-cursor
returns the number of triples visited.
Iterate over the triples in cursor
while applying the function fn
to each one. Use the count
keyword to limit the maximum number of triples that map-cursor
visits. In each iteration fn
is applied to the current triple and to the list of arguments in args
. map-cursor
reuses a single triple as it iterates so make sure to use copy-triple if you retain any of the triples you visit.
The function returns the number of triples visited.
There are many other functions that either query a triple-store directly or return information about a triple-store. For example, count-query determines the number of matches to a query very quickly (because it doesn't bother to iterate over them) and pprint-subject lets you easily explore more about particular resources.
Return the number of triples in db
matching the query using only the indices.
Unindexed triples will not be included. An error will be signaled if the triple-store is missing the required index for the query.
Note that the count includes deleted triples, encoded triples and unencoded triples. Finally, no filter can be used with a count query.
Return an estimated count of the number of triples in db
matching the query.
Unindexed triples will not be included. An error will be signaled if the triple-store is missing the required index for the query.
Note that the estimated count includes deleted triples, encoded triples and unencoded triples.
The estimate can be off by as much as twice the triple-store's metaindex-skip-size for each index chunk that must be searched.
s
, p
, o
and g
. You may also specify that only encoded or unencoded triples by searched; whether or not to search deleted triples; and whether or not a filter should be used.. A new triple will be created unless you pass in one to use using the triple
keyword parameter. nil is returned if no triples match.
triple-id
is id
and return it. The keyword argument db
can be used to specify the triple-store in which to search. It defaults to the current triple-store, *db*
. Get-triple-by-id allocates a new triple (using make-triple
. You can prevent this by passing in your own triple using the keyword argument :triple
. The data in the triple you pass in will by overwritten.
Query a triple store for triples matching the given subject, predicate, object, and graph. These can be specified either as UPIs, future-parts, strings in N-Triple format, or the wildcard nil
. Returns a cursor object that can be used with cursor-next-p and cursor-next-row.
The following example finds every triple that starts with !ub:Kevin
.
> (add-triple !ub:Kevin !ub:isa !"programmer")
8523645
> !ub:Kevin
!<http://www.w3.org/1999/02/22-rdf-syntax-ns#Kevin>
> (get-triples :s !ub:Kevin)
#<row-cursor #<triple-record-file @ #x13c1a87a> 2019 [1 - 2018] @
#x14942bba>
> (print-triples *)
<http://www.w3.org/1999/02/22-rdf-syntax-ns#Kevin>
<http://www.w3.org/1999/02/22-rdf-syntax-ns#isa>
"programmer" .
The function get-triples
takes the following arguments:
s
,p
,o
,g
- specify the query pattern. Usenil
as a wildcard. Each of these can be a UPI, a future-part, or a string that can be converted into a part. These can also take on the value :minimum if a corresponding?-end
parameter is specified. If :minimum is used, then the range query will run from the smallest value up to the ending value.s-end
,p-end
,o-end
,g-end
- Allows for range queries over encoded triples (triples whose parts are encoded UPIs). Each?-end
parameter may only be used in conjunction with its corresponding starting value parameter. Each of these can be a UPI, a future-part, or a string that can be converted into a part. These can also take on the value :maximum if a corresponding starting parameter is specified. If :maximum is used, then the range query will run from the starting value up to the maximum value in the triple-store.The
:db
keyword argument specifies the triple store to query, defaulting to the value of *db*.filter - if supplied, the
filter
should be a predicate of one parameter, a triple. If the filter function returnsnil
, then the triple will not be included in the result set.include-deleted - if set to true, then triples that are flagged as deleted will not be filtered out by the cursor.
return-encoded-triples - If true, then get-triples returns triples with encoded parts; i.e., triples that use directly encoded UPIs rather than strings stored in the dictionary. The default value is true.
return-non-encoded-triples - if true, then
get-triples
will return triples all of whose UPIs are stored as strings. This is set to true unless overridden.
The return value is a cursor object. The functions cursor-next-row and cursor-next-p can be used to step through the cursor.
If it can be determined that one of the search parameters is not interned in the triple-store, then get-triples
will return a null-cursor
(i.e., a cursor that has no rows) and a second value of :part-not-found.
Query a triple store for triples matching the given subject, predicate, object, and graph, specified either as part IDs (UPIs), future-parts, strings in N-Triples format, or the wildcard nil
. Returns a list of matching triples. The get-triples-list
function supports a multitude of options:
db
- This keyword argument specifies the triple store to query, defaulting to the value of *db*.s
,p
,o
,g
- controls the actual query pattern. Usenil
as a wildcard.s-end
,p-end
,o-end
,g-end
- Allows for range queries over encoded triples (triples whose parts are encoded UPIs). Each?-end
parameter may only be used in conjunction with its corresponding starting value parameter.cursor
- if cursor is supplied then AllegroGraph will use it to return more triples rather than building a new cursor.if-fewer
- controls the behavior ofget-triples-list
when fewer thanlimit
triples match the query. Possible values are (defaults tonil
):nil
- return list of actual results:error
- signal error if fewer results than limitother -- return other instead of short list
if-more
- controls what happens when more results thanlimit
are available. Possible values are (defaults to:cursor
):nil
- return list of limit results:error
- signal error if more results than limit:cursor
- return the list of limit results and a second value of a cursor that will yield the remaining resultsother - return other instead of truncated list
limit
- This keyword argument can be used to place a cap on the maximum number of triples returned. It defaults to the value of the special variable get-triples-list-limit. If set, then get-triples-list will return no more than:limit
triples. If it is nil, then get-triples-list will return all of the triples found by the query. Warning: settinglimit
to nil can causeget-triples-list
to return every triple in the triple-store; this can be a very bad thing over a serial connection.return-encoded-triples
- If true, then get-triples-list returns triples with encoded parts; i.e., triples that use directly encoded UPIs rather than strings stored in the dictionary. The is set to true unless overridden.return-non-encoded-triples
- if true, thenget-triples-list
will return triples all of whose UPIs are stored as strings. This is set to true unless overridden.use-reasoner
- Deprecated. If true, then the RDFS++ reasoner will be used to return inferred triples. If left unspecified, this will be true if thedb
is a reasoning-triple-store andnil
otherwise.
Note that most of the arguments to get-triples-list
do not make sense when reasoning is turned on. AllegroGraph will signal an error if you try to combine reasoning with other parameters that it cannot use.
If it can be determined that one of the search parameters is not interned in the triple-store, then get-triples-list
will return immediately return nil.
Print information about part
down to a maximum depth of maximum-depth
using the format format
. Triples for which part is an object and their children
will be printed. See part->string and (ag-property
:default-print-triple-format)
for information about part printing. See pprint-subject to display information based on objects rather than subjects.
Note that pprint-object
is designed to show the actual triples in a store. It uses ground-triple-store to remove one layer of reasoning from db
.
Print information about part
down to a maximum depth of maximum-depth
using the format format
. Triples for which part is a subject and their children
will be printed. See part->string and (ag-property
:default-print-triple-format)
for information about part printing. See pprint-object to display information based on subjects rather than objects.
Note that pprint-subject
is designed to show the actual triples in a store. It uses ground-triple-store to remove one layer of reasoning from db
.
s
, p
and o
(and optionally g
) can be found in the designated triple-store. If left unspecified, the triple-store designated by *db*
will be searched. This is handy when you care only about the presence of a triple and not its contents. If you want to use the triple, then use get-triple instead.
Range Queries
Both get-triples and get-triples-list support fast inclusive range queries using AllegroGraph's encoded data types. Though RDF requires that subjects be resources or blank nodes and predicates by resources, AllegroGraph allows you to store and query for encoded data types in any of a triple's fields. 5 In each case, to execute a range query, you must supply a starting and ending encoded UPI. You can only make a range query on a single field in each query but you can include other fields which act as additional filters. For example:
> (get-triples :o (value->upi "12:01" :time))
:o-end (value->upi "12:59" :time)
:p !ex:startTime)
will return a cursor that iterates only all of the triples whose predicate is !ex:startTime
and whose object falls on or between 12:01 and 12:59.
6
SPARQL Overview
AllegroGraph includes twinql, an implementation of the powerful SPARQL query language. SPARQL is covered both in this reference guide and in the twinql reference and tutorial. AllegroGraph also includes a SPARQL client and Server.
Prolog Select Overview
With pure Lisp as the retrieval language, you use a combination of functional and procedural approaches to query the database. With Prolog, you can specify queries in a much more declarative manner. Allegro CL Prolog and AllegroGraph work very well together. The reference guide includes more details and the tutorial provides an introduction to using Prolog and AllegroGraph with many complete examples.
RDFS++ Reasoning Overview
See the Reasoner tutorial for more details on using AllegroGraph's RDFS++ reasoner. It works with get-triples, get-triples-list, SPARQL and the Prolog q functor.
SPOGI Caching
If you are running queries that gather a lot of triples about each particular subject, then AllegroGraph's SPOGI
cache can help you to achieve significant performance improvements. Once enabled, the cache operates in the background and saves the triples associated with every subject
/ predicate
pair that it encounters. This means that when you first execute a query like:
> (get-triples-list :s !ex:gary :p !ex:telephoneNumbers)
AllegroGraph will scan all of the triples associated with the subject !ex:gary
and cache the list of triples for each predicate. If you then execute another query involving !ex:gary
, it will return the results almost instantly. The cache tracks changes to your triple-stores and will recompute its results whenever it changes.
Gets the size of the spogi
cache. Setfable.
The cache size determines the maximum number of subjects that can be help in the cache at once. The value of *default-spogi-cache-size* is used for newly created triple-stores.
Note that
Returns true if the spogi
cache is enabled for db
.
You can use (setf spogi-cache-enabled-p)
to turn caching on and off. When using the setf method, you can use a boolean or a positive integer. If you use a positive integer, it has the same effect as turning caching on and setting the spogi-cache-size to that value.
Determines whether the SPOGI-cache is enabled for newly created triple-stores.
By default, this variable will be set to nil so that SPOGI-caching will not be in effect for newly created triple-stores. You will need to experiment with your data and queries to determine whether or not the extra RAM used by the cachine is worth the performance improvements.
Sets the default size of the SPOGI-cache for newly created triple-stores.
By default, the SPOGI-cache-size is 100000. Note that caching will not be enabled for new triple-stores unless *default-spogi-cache-enabled* is set to true.
Deleting and Undeleting triples
AllegroGraph lets us delete and undelete triples. The function delete-triples deletes triples from the triple store, using the same query syntax as get-triples.
Marks the triple whose id is id
as deleted.
Returns t
if the triple deletion flag has been changed. Returns nil
if the triple was already deleted.
See also undelete-triple and deleted-triple-p.
The :db
keyword argument specifies the triple store in which the triple should be marked as deleted.
Delete triples matching the given subject, predicate, object, and graph, specified either as part IDs, strings in N-Triples format, or the wildcard nil
. Returns the number of triples deleted.
The :db
keyword argument specifies the triple store to query, defaulting to the value of *db*.
Returns a boolean indicated whether the triple whose ID is id
is deleted.
See also delete-triple and undelete-triple.
The :db
keyword argument specifies the triple store in which to check.
Unsets the deleted flag from the triple whose id is id
.
Returns t
if the triple deletion flag has been changed. Returns nil
if the triple was not deleted before the call.
See also delete-triple and deleted-triple-p.
The :db
keyword argument specifies the triple store in which the triple should be marked as undeleted.
Undelete triples matching the given subject, predicate, object, and graph, specified either as part IDs, strings in N-Triples format, or the wildcard nil
. Returns the number of triples undeleted.
The :db
keyword argument specifies the triple store to query, defaulting to the value of *db*.
Serializing Triples
There are several methods by which you can create a textual representation of your triple-store:
- using print-triples,
- using one of the serialization functions like serialize-rdf/xml or serialize-rdf-n3
- using the serialization methods in twinql (AllegroGraph's SPARQL sub-system).
The print-triples function provides a simple mechanism to output triples to *standard-output*
or a stream. It's easy to build an export function on top of it:
(defun export-triples (triples file)
(with-open-file (output file
:direction :output
:if-does-not-exist :create
:if-exists :error)
(print-triples triples
:limit nil :stream output :format :ntriple)))
The other techniques provide more control over the output format.
Print a triple returned by cursor-next-row or get-triples-list.
Returns the triple printed.
The keyword argument :format
, which defaults to the value of (ag-property
:default-print-triple-format)
, specifies how the triple should be printed. The value :ntriples
specifies that it should be printed in N-Triples syntax. The value :long
indicates that the string value of the part should be used. And the value :concise
causes it to use a more concise, but possibly ambiguous, human-readable format.
triple-container
which can be either a triple store object, a list of triples such as is returned by get-triples-list, or a cursor such as is returned by get-triples. If the keyword argument :limit
is supplied, then at most that many triples will be displayed. The :format
keyword argument controls how the triples will be displayed, in either :ntriples
, :long
, or :concise
format. It defaults to (ag-property
:default-print-triple-format)
. The stream
argument can be used to send output to the stream of your choice. If left unspecified, then output will go to standard-output.
Write an N-Triples representation of from
to to
. from
should be a triple store, a list of triples, or a cursor. to
should be a stream, a file path to open for writing, t
(meaning *standard-output*
), or nil
(return a string).
if-exists
and if-does-not-exist
are arguments to the Common Lisp open
function which apply when to
is a filename.
If base-uri
is provided, it is used to generate a “baseURI:” comment at the start of the serialization. This comment is expected by TopBraid Composer.
base-uri
can be t
, in which case a generated UUID URN is used, or a string, UPI, or future-part
naming a URI. It can also be a triple-store instance; in this case, a UUID URN associated with the store is used. For persistent stores this value should remain constant.
In other respects this function behaves like print-triples.
Write from
, which should be a triple store, a list, or a cursor, to to
, which should be a stream, file path, t
(print to *standard-output*
), or nil
(return a string).
If from
is a triple-store
or a list of triples, and prepare-namespaces-p
is t
, it is first traversed to build a hash of namespaces to prefixes for all properties in the store. The value of db.agraph::*namespaces*
is used as a seed.
If you can ensure that every property used in the triple-store has a defined prefix, you can pass nil
for prepare-namespaces-p
to gain a speed improvement from omitting this phase.
If error-on-invalid-p
is t
, the serializer will throw an error if it encounters a type or predicate that it cannot abbreviate for RDF/XML. Ordinarily a local namespace declaration is included in such a property element instead.
If a namespace prefix table is built, it will be returned as the second value.
If from
is a cursor, it cannot be traversed multiple times, so prepare-namespaces-p
is ignored. If a property is encountered that cannot be abbreviated with the current available prefixes, an error will be signaled or a local namespace declaration generated instead.
Such local namespace declarations are verbose, and so providing a thorough namespace hash is preferred.
If a predicate cannot be abbreviated as an XML QName, your graph cannot be serialized in RDF/XML. An error will be raised in this case.
if-exists
and if-does-not-exist
are arguments to the Common Lisp open
function which apply when to
is a filename.
xml-base
can be t
, in which case a generated UUID xml:base
attribute is written into the serialized RDF/XML, or a string, UPI, or future-part
naming a URI. It can also be a triple-store instance; in this case, a UUID URN associated with the store is used.
For persistent stores this value should remain constant.
If xml-base
is nil
, no xml:base attribute will appear in the output.
Note that xml-base
values will be escaped, but they will not be checked for validity (i.e., you can successfully provide an invalid URI to this function).
If memoize-abbrev-lookups-p
is t
, a upi-hash-table
is built to store the mappings between resources in the store and string abbreviations. This hash-table will contain as many entries as there are types and properties in the data to be serialized. For some datasets disabling this caching will yield a significant reduction in space usage in exchange for a possible loss of speed.
If indent
is non-nil
, then it specifies the initial indentation of elements.
If nestp
is t
, then (subject to the order of triples in the triple store) some nesting of RDF/XML elements will be applied. nestp
of nil
will cause a flat tree to be produced, where each resource is its own top-level element. You should not rely on this alone for the purposes of processing RDF data with XML tools.
If output-types-p
is t
, then additional queries will be performed for each resource to decorate the RDF/XML with types. If nil
, then rdf:type
elements alone will be used.
Because of rounding errors and other conversion issues, the RDF/XML serializer is not guaranteed to round-trip correctly with value-encoded literals (i.e. literals stored as encoded UPIs. See the reference guide section on type mapping for more information on encoded UPIs).
Serialize source according to exchange-of-named-rdf-graphs. Serialization will probably open at least as many files as there are graphs in the source.
Returns the manifest path and the number of graphs saved.
If single-stream-p
only a single file is open at any one time. This is slower, but guaranteed not to fail with large numbers of graphs.
Write source
, which should be a triple store, cursor, or list of triples, to output
. output
must be t
(equivalent to *standard-output*
), nil
(which returns the serialization as a string), a string or pathname, which will be opened for output respecting the if-exists
and if-does-not-exist
arguments, or a stream.
The resulting output is produced according to the value of constraints
. This must be one of the following symbols:
:canonical
: each graph appears once in the output. All graphs and triples are sorted lexicographically. All graphs are named, even when a name must be generated.:collated
: each graph appears once in the output.:lenient
(ornil
, the default): graphs can appear multiple times in the output. No sorting occurs. load-trix can consume this, but not all other TriX parsers necessarily can.
The value of the default-graph
argument applies when the default graph has to be serialized. If it is nil
, the default, the AllegroGraph-specific <default/>
element is used. If it is non-null
, it should be a URI string or a valid part that will be substituted into the output.
Managing a triple-store
These functions are used to create, delete, and examine a triple-store. All of a triple-store's data is kept in a single directory whose name it shares. For convenience, many operations act by default on the current triple-store which is kept in a special variable named *db*. The with-triple-store macro makes it easy to call other code with a particular store marked current. There are also several reports that describe the triple-store in detail.
Each triple-store has two parameters that help you to manage its indices automatically: unindexed-triple-count-threshold and unmerged-chunk-count-threshold. The first controls the maximum number of unindexed triples in the store; the second controls the maximum number of index chunks or fragments. When it ships, each triple-store has both of these parameters set to zero (0) which means that no automatic indexing and merging will take place -- everything is left to your control. Here are some of the things that you will want to consider when setting these values.
- Ideally, you would like to have all of your triples indexed into a single index-fragment.
- The lower you set unindexed-triple-count-threshold, the fewer unindexed triples you will have but you will also have more index chunks.
- Each query must examine each index chunk so having too many will slow down query times.
We suggest that you experiment with variations on the parameters. Franz is very open to hearing your feedback on how you would like to manage your triple-store.
One final point is that the automatic indexing and merging is subject to checks by the AllegroGraph manager process (see manager-period elsewhere in this documentation).
db
keyword argument default to the value of this variable.
While completely unrelated to AllegroGraph, there is another symbol with the same name exported from the dbi.oracle package. If you try to have a package use both the dbi.oracle and the db.agraph packages, these two symbols will signal a package conflict error. Assuming you want to have the db.agraph symbol to be available without a package qualifier, you should define your package something like this
(defpackage :my-package
(:use :cl :dbi.oracle :triple-store ...)
(:shadowing-import-from :triple-store :*db*)
...)
or else execute this form
(shadowing-import 'db.agraph:*db*)
before using either package.
:wait
keyword parameter is passed along to close-triple-store. It defaults to nil
Close the triple store, after saving all persistent data to disk as if by sync-triple-store. Close-triple-store has the following keyword arguments:
:db
- defaults to the value of *db* and specifies which triple-store to close. If thedb
being closed iseq to *db*, then *db* is set to
nil` after it is closed. A triple-store only needs to be closed once regardless of how many times open-triple-store has been called on it.:if-closed
- controls the behavior when thedb
is either not open or nil. Ifif-closed
is:error
then an error will be signaled in this situation. If it is:ignore
, thenclose-triple-store
will just return without signaling an error. The argument defaults to:ignore
.:verbose
is true, then a message will be printed to*debug-io*
before the triple store is closed.:wait
is true thenclose-triple-store
will not return until all of its concurrent activity is complete. This includes synchronizing its data, building indices and running queries. The value of:wait
will be true unless overridden. If it is false, thenclose-triple-store
will return immediately but the triple-store will no longer be available to use. Its actual in-memory structures will not be available to the garbage-collector until all of its background activity is complete and it is finally closed.
Create a new triple store with the given name
. This is both the name of the triple-store and its location on disk. It can be the full path to a directory or just a directory name. If it is a simple name, then the directory
argument is used to convert it to a complete path.
For example, to create a triple-store named 'animals' in the directory 'c:/datafiles/biology', you could use either
(create-triple-store
"c:/datafiles/biology/animals")
or
(create-triple-store "animals"
:directory "c:/datafiles/biology/")
The directory defaults to the directory component of *default-pathname-defaults*
. You cannot use a name containing a directory path and the directory argument simultaneously.
Create-triple-store
takes numerous keyword arguments:
:if-exists
- controls what to do if the data directory already exists. The default value,:supersede
, will cause create-triple-store to delete the old triple store and create a new one;:error
causes create-triple-store to signal an error.:expected-unique-resources
- sets the initial size of the triple-store. It determines the number of unique names (e.g., resources and literals) that the triple store is expected to hold and defaults to the value of *default-expected-unique-resources*. The triple-store will grow if this number is exceeded but setting the value initially will provide better performance because no resizing will be required.:with-indices
- adds indices to the newly created triple-store. It is equivalent to calling add-index once for each index in the list of indices. It defaults to the value of the AllegroGraph propertystandard-indices
.:include-standard-parts
- if true, then AllegroGraph will add the following strings to the triple-store at creation time: rdf:type, owl:sameAs, owl:inverseOf, rdfs:subPropertyOf, rdfs:subClassOf, rdfs:range, rdfs:domain, owl:transitiveProperty. The value defaults to the ag-property(:include-standard-parts)
.:triple-store-class
- the kind of triple-store to create. If left unspecified, then the value of the property:default-triple-store-class
will be used. Depending on the class of the triple-store created, other parameters may be possible or required. For example, creating a remote-triple-store requires that you also specify aconnection
instance.:text-index-parameters
- a property list describing additional freetext-indexing parameters such as:stop-word-list
,:stop-word-file
or:minimum-word-size
.
Create-triple-store returns a triple-store object and sets the value of the variable *db* to that object.
:directory
parameter to create-triple-store or by using a full pathname as the name
argument to create-triple-store.
name
parameter used in the call to create-triple-store.
db
. This is the graph that will be assigned to any triples added to db
unless a different graph is specified.
Delete an existing triple store. Returns t
if the deletion was successful and nil
if it was not.
The db-or-name
argument can be either a triple store instance or the name of a triple store. If it is an instance, then the triple store associated with the instance will be deleted. If it is a name, then the triple store of that name in the directory designated by the :directory
keyword argument will be deleted. The directory parameter defaults to the directory component of *default-pathname-defaults*
. If db-or-name
is eq
to *db*, the *db* will be set to nil
once the triple-store is deleted.
The :if-does-not-exist
keyword argument specifies what to do if the data directory does not exist. The default value, :error
, causes delete-triple-store to signal an error. The value :ignore
will cause delete-triple-store to do nothing and return nil
.
The :if-open
keyword argument specifies the behavior if the designated triple store is currently open. The default value, :error
, causes delete-triple-store to signal an error. The value :close
causes delete-triple-store to close the triple store, as if by close-triple-store
and then delete it. If AllegroGraph is unable to close the triple store, an error may still be signaled.
Close any current triple-store and create a new empty one in a temporary directory. Make-tutorial-store takes two keyword parameters:
:temporary-directory
- the directory where the store will be created. If it is not supplied, then it will get its value from (ag-property
temporary-directory
).:use-reasoner
- If true (the default), then the new triple-store will use RDFS++ reasoning. If nil, then the triple-store will have no reasoning.
The new triple-store will be bound to *db*
and is also returned by make-tutorial-store
.
Open an existing triple store (previously created using create-triple-store) with the given name
. Name
is both the name of the triple-store and its location on disk. It can be the full path to a directory or just a directory name. If it is a simple name, then the directory
argument is used to convert it to a complete path.
For example, to open a triple-store named 'animals' in the directory 'c:/datafiles/biology', you could use either
(open-triple-store
"c:/datafiles/biology/animals")
or
(open-triple-store "animals"
:directory "c:/datafiles/biology/")
The directory defaults to the directory component of *default-pathname-defaults*
. You cannot use a name containing a directory path and the directory argument simultaneously.
You can use the :with-indices
parameter to add additional indices to the triple-store. (Adding an index multiple times has no effect). This will not remove any indices that already exist (see drop-index and drop-indices if you need to do that).
Returns a triple store object and sets the value of the variable *db* to that object. If the named triple store is already open, open-triple-store returns the same object.
WARNING Multiple calls to open-triple-store
with the same arguments will each return the same (eq) triple-store. This means that closing a store in one thread will also close the store for all other threads that have opened it. Please contact Franz support staff ([email protected]) for multi-threaded programming strategies
This function has to be called before any inferences are made. It creates internal hash-tables to speed up the reasoner. In normal operation, AllegroGraph will call prepare-reasoning as necessary. You can see diagnostic messages by using the parameter verbose
which defaults to the value of (ag-property
:verbose-prepare-reasoning)
. You can also force the hash-tables to be regenerated using the force
parameter. Finally, the show-progress
keyword argument can be used to cause prepare-reasoning
to print a message for each of the hash-tables it builds.
The function prepare-reasoning returns no value.
Ensure that all persistent data needed by the triple store is saved to disk.
Called automatically by close-triple-store and the bulk loading operations like load-ntriples. The :db
keyword argument defaults to *db*. Returns t
.
Returns the number of triples in a triple store. The :db
keyword argument specifies the triple store to use, either by name or a triple store object. It defaults to the value of *db*.
Note that reasoning triple-stores do not report accurate triple-counts (doing so might take an inordinate amount of time!).
Returns true if the triple-store with the given name
exists. Name
can be the full path to a directory or just a directory name. If it is a simple name, then the directory
argument is used to convert it to a complete path.
For example, to verify the existence of a triple-store named 'animals' in the directory 'c:/datafiles/biology', you could use either
(triple-store-exists-p
"c:/datafiles/biology/animals")
or
(triple-store-exists-p "animals"
:directory "c:/datafiles/biology/")
The directory defaults to the directory component of *default-pathname-defaults*
. You cannot use a name containing a directory path and the directory argument simultaneously.
unindexed-triple-count-threshold
unindexed triples, an indexing task will be started to index them. If a indexing-host has been added then the task will run on it (see add-indexing-host for details). Otherwise, indexing will run as a background task of the main AllegroGraph process.
Binds both var and *db* to the triple-store designated by store. The following keyword arguments can also be used:
errorp - controls whether or not
with-triple-store
signals an error if the specified store cannot be found.read-only-p - if specified then with-triple-store will signal an error if the specified triple-store is writable and read-only-p is nil or if the store is read-only and read-only-p is t.
- state - can be :open, :closed or nil. If :open or :closed, an error will be signaled unless the triple-store is in the same state.
This variable controls when changes to the triple store are written to disk. If t
, then changes will be written after every call to add-triple. If nil
(which is the default), then changes will be written only when the triple store is closed, indexed, or synchronized. A setting of nil
is more efficient but can lead to surprises: for example, the results of queries may not contain recently added triples.
Note that functions such as load-ntriples and load-rdf/xml dynamically bind *synchronize-automatically*
to nil in their inner loops for efficiency's sake. You may want to use a similar practice in any of your code that adds many triples at once.
Reports
db
(which defaults to *db* unless specified). See db-room-list if you are interested in getting the information without having it printed.
db
. This is used by the db-room function. The :db
keyword argument defaults to *db*.
stream
.
Indexing Triples
When triples are first added to the triple-store queries are performed by simple linear scanning. To avoid the cost of linear scans, triples can be indexed so that queries will be very fast. An AllegroGraph triple-store can have up to six different index flavors. Whether you need all six will depend on the sort of queries that you need to run. Each flavor is named by the order in which the triples are sorted. For example, if triples are sorted first on predicate, then object, subject, graph, and finally id, then the index flavor will be posgi. Here are the flavors AllegroGraph uses and the sorts of queries that they help optimize:
spogi get-triples _s_, ---, ---, ---
get-triples _s_, _p_, ---, ---
get-triples _s_, _p_, _o_, ---
posgi get-triples ---, _p_, ---, ---
get-triples ---, _p_, _o_, ---
ospgi get-triples ---, ---, _o_, ---
get-triples _s_, ---, _o_, ---
gspoi get-triples _s_, ---, ---, _g_
get-triples _s_, _p_, ---, _g_
get-triples _s_, _p_, _o_, _g_
gposi get-triples ---, _p_, ---, _g_
get-triples ---, _p_, _o_, _g_
gospi get-triples ---, ---, _o_, _g_
get-triples _s_, ---, _o_, _g_
Unless you tell it otherwise, AllegroGraph will assume that each new triple-store should have all six indices
7 . You can change this with the :with-indices
argument to create-triple-store and by using add-index and drop-index to manage indices explicitly.
When to index
Regardless of which flavors you are using, you must still reckon with when and how to build indices. The function index-new-triples builds indices of just the currently unindexed triples and takes time proportional to the number of triples to be indexed. However at query time each index built with index-new-triples must be queried so calling index-new-triples too often will reduce the benefits of building the indices.
To get rid of the performance drag of having too many indices, you can use index-all-triples to build a unified index of all the triples in the triple-store. While this function can take time proportional to the total number of triples in the store, it can take advantage of the indices already built by index-new-triples to speed up indexing. In general the best strategy is to use index-new-triples to build indices after each large chunk of triples is added to the store and to periodically merge the indices with index-all-triples.
Adds a new index flavor
to a triple-store.
The actual index data structure will be created the next time that AllegroGraph indexes the triple-store (either by a call to index-new-triples
or index-all-triples
or automatically through the management policy of the triple-store.)
The :db
keyword argument specifies the triple-store to which to add the index and will be *db*
unless otherwise specified.
The :location
keyword argument controls the physical location of the index. It can be left unspecified or set to the location of a directory. If left unspecified, the index will be located in the same directory as the triple-store (see data-directory). If used, it should name an empty directory.
Flavor should be a valid index name (e.g., :posgi). See index-flavors in the reference guide for additional details
Adds several indices to a triple-store at once.
Flavors
should be a list of valid index flavors. See add-index for additional details.
ag-property
:standard-indices
to a triple-store using add-indices
.
Returns the average index-fragment-count
for a triple-store. This is the total number of index chunks divided by the number of indices. The higher the chunk count, the more work each query must do to find results.
The keyword argument :db
can be used to specify the triple-store to use. It defaults to *db*
.
Remove an index from a triple-store.
The flavor
argument should be a valid index flavor name that is currently an index of the triple-store.
The keyword argument :db
controls the triple-store from which the index will be removed. It will default to *db*
unless otherwise specified.
Flavor should be a valid index name (e.g., :posgi). See index-flavors in the reference guide for additional details
Remove several indices from a triple-store at once.
Flavors
should be a list of valid index flavors that are indices of the triple-store. See drop-index for more details.
Create a unified index of all the triples in the triple store, including triples previously indexed. The time taken to index all triples includes the time index-new-triples plus the time to merge all index chunks. The first step is proportional to the number of unindexed triples multiplied by the logarithm of the same number (i.e., if N
is the number of new triples, then the time is O(N log N)
). The merge step is proportional to the total number of triples multiplied by the logarithm of the number of chunks. If you have a very large triple store to which you have added a fairly small number of new triples, you can use index-new-triples
to get most of the benefits of indexing at much lower time cost.
Indexing can run as a background task in either the same Lisp process or on multiple remote Lisp processes (see the clustering documentation for more details). Index-all-triples return the task id of the indexing task that it creates.
The wait
keyword argument controls whether index-all-triples returns immediately or waits for all indexing and merging to complete. It defaults to true. If it is false, you can use the id
of the task returned to see if indexing has completed.
See the variable maximum-indexing-sort-chunk-size for information on controlling the indexing process.
This controls the index chunk limit at which a too-many-index-chunks-error
error will be signaled.
When AllegroGraph merges index chunks, it must open all of them simultaneously. If there are too many chunks, then the operating system may run out of file handles. The *index-chunk-count-warning-limit*
setting helps manage file handle use by signaling a continuable error if there are more than this many chunks.
flavor
. The keyword argument :db
can be used to specify the triple-store to use. It defaults to *db*.
Index the triples that have been added to the triple store since the last time indices were built. The time taken to index new triples is proportional to the number of unindexed triples multiplied by the logarithm of the same number (i.e., if N
is the number of new triples, then the time is O(N log N)
).
However, the new indices will not be merged with the older indices which will cause queries to execute more slowly. To maximize query performance you will want to use index-all-triples
to build a unified index.
Indexing can run as a background task in either the same Lisp process or on multiple remote Lisp processes (see the clustering documentation for more details).
The wait
keyword argument controls whether index-new-triples returns immediately or waits for all indexing to complete. It defaults to true. If it is false, then index-new-triples return the id
of the indexing task that is created.
See the variable maximum-indexing-sort-chunk-size for information on controlling the indexing process.
stream
.
Returns the status of the current triple-store as regards indexing. This can be one of:
:scheduled
:running
:needed
- :idle
Merge-new-triples combines smaller index chunks into larger ones without trying to merge all of the chunks into one. Suppose, for example, you have loaded a triple-store with 100-million triples and then called index-all-triples. Now suppose you add several batches of a few thousand triples and call index-new-triples after each batch. At this point each index flavor will consist of many chunks: one big one for the initial load and many small ones. A full merge will take significant time and computational resources but having this many chunks makes for inefficient querying. This is when merge-new-triples
is a useful half-way measure. It will merge the small chunks into one (which should be quite fast). This will improve query performance without requiring a complete merge.
merge-new-triples
determines whether an index chunk is smaller than another one if it is less than (smaller-than-factor (policy-manager *db*))
. This value is settable per store and persists when the store is closed. It is normally set to 0.1. As an example, if you have a chunks of sizes 10,000, 2000, 1000, 1000, 1000 and 500, then a call to merge-new-triples
will merge the four smallest chunks and leave you with three chunks of sizes 10,000, 3500 and 2000.
Returns the number of triples in a triple store. The :db
keyword argument specifies the triple store to use, either by name or a triple store object. It defaults to the value of *db*.
Note that reasoning triple-stores do not report accurate triple-counts (doing so might take an inordinate amount of time!).
Returns a list of information on the indices of a triple-store.
The :db
keyword argument specifies the triple-store on which to report.
The :verbose
keyword argument controls how much information to return. If verbose
is nil, then only the flavor-names are returned. If it is true, then a list of lists is returned where each sub-list starts with an index object and continues with ranges of the unindexed triples.
Advanced Triple-Store Operations
The !-reader macro and future-parts
When working with the triple-store at the REPL (the lisp listener) it's nice to have a more concise way to refer to resources and literals than with calls to resource, literal or the part interning functions. It's also handy to be able to abbreviate the many long URIs with a common prefix such as http://www.w3.org/2000/01/rdf-schema#
. Namespaces and the !
-reader macro provide a concise syntax for both resources and literals.
The first thing the !
-reader macro allows you to do is write N-Triples strings without quotation marks (except for those required by the N-Triples syntax itself!). Thus instead of writing:
"<http://www.franz.com/>"
"\"foo\""
"\"foo\"^^<http://www.w3.org/2000/01/rdf-schema#integer>"
"\"foo\"@en"
you can simply write:
!<http://www.franz.com/>
!"foo"
!"foo"^^<http://www.w3.org/2000/01/rdf-schema#integer>
!"foo"@en
In addition, the !
-reader macro uses namespaces to abbreviate long URIs. Use the register-namespace function to assign an abbreviation to any prefix used in URIs. For instance you can register s
as an abbreviation for the URI prefix http://www.franz.com/simple#
like this:
(register-namespace "s" "http://www.franz.com/simple#")
Then you can use that prefix with the !
-reader macro to write URIs starting with that prefix:
!s:jans => !<http://www.franz.com/simple#jans>
You have probably noticed that the !
-reader macro does not seem to be doing anything:
!"hello" => !"hello"
This is because !
is converting the string "hello" into what AllegroGraph calls a future-part and the future-part prints itself using the !
-notation. If we describe
the future-part, then we will see all of the additional structure:
> (describe !"hello")
!"hello" is a structure of type future-part. It has these slots:
type :literal
value-prefix nil
value-fragment "hello"
extra-prefix nil
extra-fragment nil
value "hello"
extra nil
extra-done-p t
upi #(5 0 0 0 0 0 111 108 108 101 104 7)
triple-db nil
Now it's clear that AllegroGraph has parsed the string and performed the computations to determine the part's UPI.
future-parts are called future-parts because they cache some of the information (e.g., the namespace prefix) and wait to resolve until the namespace mappings are available which may be in the future. Before we finish describing resolution, however, here are some examples. First, literals:
!"hello"
: equivalent to (literal "hello")!"hello"@en
: equivalent to (literal "hello" :language "en")!"OK"^^<http://www.w3.org/2000/01/rdf-schema#XMLLiteral>
: equivalent to (literal "OK" :datatype "http://www.w3.org/2000/01/rdf-schema#XMLLiteral")!"OK"^^rdfs:XMLLiteral
: assuming that we have already registered the string "rdfs" with the namespace URI "http://www.w3.org/2000/01/rdf-schema#", then this is the same part as above.!"Careful"^^<rdfs:XMLLiteral>
: this would be equivalent to (literal "Careful" :datatype "rdfs:XMLLiteral") and is probably not what you intend.!"-- wrong --"^^XMLLiteral
: this is an error since a type must be either a URI or a QName (Qualified name). I.e., it must either be bracketed with '<' and '>' or it must contain a ':'.
The story for resources is very similar:
!<http://www.franz.com/products#allegrograph>
: equivalent to (resource "http://www.franz.com/products#allegrograph")!franz:allegrograph
: assuming that we have already registered "franz" to map to "http://www.franz.com/products#", then this is the same part as above.!Wrong
: this would be the URI "wrong" resolved using the current base URI. Since AllegroGraph does not support base URIs, such a part name is meaningless and will produce an error.!<smells-fishy:allegrograph>
: equivalent to (resource "smells-fishy:allegrograph") and probably not what you intend.
Future parts are resolved when it is necessary to determine their UPI. If the part uses a namespace (e.g., is something like !a:b), then the namespace will be resolved first. It is an error to try and determine a part's UPI if the necessary namespace mapping has not been registered. Once the namespace of a part is resolved, then it will not be resolved again (during the current Lisp session). After namespace resolution, a future-part is equivalent to a particular string which can be interned into a triple-store (i.e., stored in the store's string dictionary).
Future-parts make working with AllegroGraph much simpler but they do contain some machinery and can be confusing. Remember that you can always tell what is happening by using the Lisp describe
function.
The following are the functions used for enabling the !
reader macro and for managing namespaces.
:keep-standard-namespaces
is true (the default) then the namespace mappings in standard-namespaces will not be removed.
register-namespace
that can be used to recreate the original namespaces if needed later. If the optional file
argument is provided, output is written to that file. Otherwise the output is sent to *standard-output*
.
uriref
associated with namespace-prefix
or nil if there is no association.
fn
to each namespace mapping. Fn
must be a function of two arguments: the prefix and the uri.
namespace-prefix
and uri-reference
, both of which should be strings. If the errorp
keyword argument, which defaults to the value of (ag-property :error-on-redefine-namespace)
, is true, then defining a mapping for an existing prefix will signal a continuable namespace-redefinition-error condition.
The standard-namespaces is a list of (name prefix) pairs representing namespace mappings. For example:
'(("rdf" "http://www.w3.org/1999/02/22-rdf-syntax-ns#")
("rdfs" "http://www.w3.org/2000/01/rdf-schema#")
("owl" "http://www.w3.org/2002/07/owl#"))
It is used by the function register-standard-namespaces to create standard mappings.
Enables the use of the !-reader macros. The values returned are the previous definition of the character in the current readtable.
Note: enable-!-reader
modifies readtable specified by the optional readtable
argument. If left unspecified, then enable-!-reader
modifies the current *readtable*
. There is no disable-!-reader
command because Common Lisp does not provide a portable mechanism to cleanly compose and operate with multiple readtables. For information on working with readtables, please consult that Allegro Common Lisp reference.
Note: Because of its global effect, if enable-!-reader
is called on the default readtable (*readtable*
), then use of the exclaimation mark character in other Lisp packages and systems may break. Generally speaking, it is possible to work around these issues. Please contact support for additional help.
Triples and parts are represented by (simple-array (unsigned-byte 8) 56) and (simple-array (unsigned-byte 8) 12) respectively. By default the Lisp printer prints these as vectors of bytes which is not very informative when using AllegroGraph interactively. This function modifies a pprint-dispatch table to print triples and parts interpretively if this can be done in the current environment. Specifically, the value of *db* must be an open triple store, and the vector being printed must print without error in the manner of print-triple or upi->value. If any of these conditions don't hold the vector is printed normally.
If the boolean argument is true, the informative printing is enabled, otherwise disabled. For example:
> (enable-print-decoded t)
t
> (upi !"Dürst"^^xsd:string)
{Dürst}
> (enable-print-decoded nil)
nil
> (upi !"Dürst"^^xsd:string)
#(48 61 125 164 117 231 137 163 64 100 17 2)
The :pprint-dispatch argument specifies the dispatch table to modify, by default the value of print-pprint-dispatch. Once enable-print-decoded has been turned on, you can also use the special-variable *print-decoded*
to enable fine-grained control of triple and UPI printing. See the AllegroGraph tutorial for more information on the various notations AllegoGraph uses.
Clustering: indexing with multiple processors
AllegroGraph can use multiple processors (on the same machine or different machines) to dramatically increase indexing speed. This clustering ability is built on a more generic core from the net.cluster
package which is itself built upon Allegro Common Lisp's RPC mechanisms. In practice, all you need to do is make sure that Allegro Common Lisp is installed on each machine that you want to use, setup your environment to tell AllegroGraph where the machines are located and then start indexing.
The details of setting up a network for clustering are outside of the scope of this reference though Franz will be including more information on-line in the coming months. You will want to make sure that all of the machines can access the data quickly over a shared drive. The easiest setup, of course, is to use a single computer with multiple processors or processor cores.
Use add-indexing-host to tell AllegroGraph what machines to use (and the net.cluster
functions machines, remove-machine and remove-all-machines to manage them). You can optimize start-up time by calling start-remote-clients or start-all-remote-clients yourself. This starts another Lisp instance over the connection and prepares that instance to run tasks.
All of the functions that use background processes (such as indexing, merging and (eventually) querying) have a :wait
parameter to let you specify if the task should wait until all processing is complete. You can learn more about the details of a task by use find-task on the return value of a function like index-all-triples to retrieve the task instance associated with a particular ID. Finally, you can use the indexing-status and unschedule-indexing functions to see the current state of a triple-store's indexing tasks.
:agraph-cluster-code-pathname
and sys:agraph;agraph-cluster.fasl
identifier
in the task-manager. The search will occur in pending tasks, running tasks and failed tasks. The kind of search depends on the type of identifier
. If it is a number, then the match will be performed on the id
of the task; if it is a symbol or a string, then the match will be performed on task-name
; finally, if it is a task, then the task is just returned.
name
.
Freetext Indexing
AllegroGraph supports freetext indexing on the objects of triples whose predicates have been registered. Triples added after a predicate is registered will be automatically indexed. You can make sure that all triples have been indexed using the freetext-index-needs-updating-p and update-freetext-index functions.
Note that freetext indexing is orthogonal to the triple indexing performed by commands like index-all-triples. Freetext indexes let you quickly map from words and phrases to triples; triple-indexes let you quickly find triples that match particular patterns.
Once indexed, triples can be found using a simple but robust query language. Freetext indexing support includes functions to register predicates and see which predicates are registered:
Register predicate
for freetext indexing in the triple-store db
. Once registered, any triples with this predicate will have the string of their object indexed by AllegroGraph's built-in freetext indexer. Use the db
keyword argument to specify the triple-store in which to register the predicate. If left unspecified, the predicate will be registered in triple-store *db*.
(register-freetext-predicate
!<http://www.w3.org/2000/01/rdf-schema#comment>)
Returns the predicate.
Note that you have to register predicates before you add triples with that predicate. Older triples will not get indexed.
db
. See register-freetext-predicate for more information.
predicate
is registered for freetext indexing in the triple-store db
. See register-freetext-predicate for more information.
Returns true if there are any registered-freetext-predicates that may have triples that need to be added to the freetext-index of db
.
:db
- the triple-store to check; defaults to *db*.
Ensure that all freetext-registered-predicates have been applied to every triple in the store.
:db
- the triple-store to check; defaults to *db*.
And methods to query a triple-store for triples that match an expression:
Returns a list of ids of the triples whose object contains text matching the expression.
(freetext-get-ids "amsterdam")
(freetext-get-ids "\"Good girls go to heaven,
bad girls go to Amsterdam\"")
(freetext-get-ids '(and "amsterdam" "usa"))
(freetext-get-ids '(and "amst?r* (or "us?" "neth*")))
Returns a cursor that iterates over the triples whose objects contain text that matches the expression.
(iterate-cursor (triple (freetext-get-triples "amsterd*"))
(print triple))
Returns all the unique subjects in triples whose objects contain expression. This is a useful function in prolog queries. The following example is included in the tutorial.
(select (?person)
(lisp ?list
(freetext-get-unique-subjects '(and "collection" "people")))
(member ?person ?list)
(q- ?person !rdfs:subClassOf !c:AsianCitizenOrSubject))
From strings to words: Tokenizing
To index freetext, the engine first breaks strings into words (a process called tokenization). The built-in tokenizer defines a word
as any run of letters or digits 3-characters or longer. Dashes, underscores and periods do not break words unless they occur at the start or the end. Thus, the free-text index will not include words whose length is less than three (3) characters. Unless you change them, it will also omit the following stop words:
Below are some examples of strings and the words the tokenizer will extract from them:
Hello there. I am fine. how are you? | "hello" "fine" "how" "you" |
I think...therefore... I am. | "think...therefore" |
When indexing, the freetext engine first tokenizes the strings in the triple's object. | "when" "indexing" "freetext" "engine" "first" "tokenizes" "strings" "triple" "object" |
k = x^{2} + y^{2} defines a circle. | "defines" "circle" |
You can change AllegroGraph's stop-word strategy when a triple-store is created or opened using the :text-index-parameters
keyword argument. You can also use the following accessors to make changes:
Words smaller than text-index-minimum-word-size
will not be indexed.
This is setf
able. See also text-index-parameters.
A list of words that will not be indexed.
This is setf
able. See also text-index-parameters.
A property list describing additional freetext-indexing parameters.
These include:
:stop-words
- a list of words that will not be indexed:minimum-word-size
- words smaller than this will not be indexed.
text-index-parameters
is also setf
able.
The :text-index-parameters
argument to create-triple-store and open-triple-store is a property list with one or more of these keys: :minimum-word-size
, :stop-word-list
, :stop-word-file
. :minimum-word-size
will be set to 3 unless you change it. It cannot be less than 2. The :stop-word-list
and :stop-word-file
arguments can be used simultaneously. The words in the list and the words in the file will be merged into a single list. If you do use a :stop-word-file
, it must contain the words you want the indexer to ignore with each word on its own line.
It is also possible to change the freetext indexer's tokenizer but AllegroGraph does not yet include a convenient API to do so. If your freetext indexing needs require greater customization, please contact technical support.
Freetext Query Expressions
Here is the informal grammar used to build query expressions:
- pattern
- string-pattern | composite-pattern
- string-pattern
- string | phrase-string
- string
- "char*"
- char
- ? denotes a wild card that matches any single character
- char
- * denotes a wild card that matches any sequence of characters
- char
- \" denotes an escaped "
- char
- any any other character denotes itself
- phrase-string
- "\"this is a phrase\"" no ? and * allowed
- composite-pattern
- (and pattern*) | (or pattern*)
Here are some examples:
- find all the triples whose object contains the word "baseball"
(freetext-get-triples "baseball")
- triples whose object contains all of the words "baseball", "soccer", "champions"
(freetext-get-triples "baseball soccer champions") (freetext-get-triples '(and "baseball soccer champions"))
- triples whose object contains at least one of the words "baseball", "soccer", or "champions"
(freetext-get-triples '(or "baseball soccer champions"))
- triples that contain any word ending in "ball"
(freetext-get-triples "*ball")
- triples that contain any 8-letter word ending in "ball"
(freetext-get-triples "????ball")
- triples that contain the exact phrase "baseball champions"
(freetext-get-triples "\"baseball champions\"")
Data-type and Predicate Mapping
Most triple-stores work internally only with strings. AllegroGraph, however, can store a wide range of datatypes directly in its triples. This ability not only allows for huge reductions in triple-store size but also lets AllegroGraph execute range queries remarkably quickly. Use the supported-types function to see a list of datatypes that AllegroGraph can encode directly. The currently supported types are:
type-name | type code | encoded |
---|---|---|
:blank-node | 8 | yes |
:byte | 18 | yes |
:date | 23 | yes |
:date-time | 25 | yes |
:default-graph | 31 | no |
:double-float | 12 | yes |
:geospatial | 36 | yes |
:gyear | 26 | yes |
:int | 20 | yes |
:latitude | 28 | yes |
:literal | 1 | no |
:literal-language | 3 | no |
:literal-short | 7 | yes |
:literal-typed | 2 | no |
:long | 21 | yes |
:long-88 | 42 | yes |
:longitude | 29 | yes |
:node | 0 | no |
:plain | 44 | yes |
:resource | 0 | no |
:short | 19 | yes |
:single-float | 11 | yes |
:subscript | 41 | yes |
:telephone-number | 27 | yes |
:time | 24 | yes |
:triple-id | 30 | yes |
:unsigned-byte | 14 | yes |
:unsigned-int | 16 | yes |
:unsigned-long | 17 | yes |
:unsigned-long-88 | 43 | yes |
:unsigned-short | 15 | yes |
The datatypes are specified as keywords or integers (with the integers being used internally). You can translate in either direction using type-code->type-name and type-name->type-code. You can add encoded-triples (i.e., triples some of whose parts are encoded UPIs rather than references to strings) directly using add-triple or by setting up mappings between particular predicates or specific datatypes and then using one of the bulk loading functions. In the former case, you use value->upi and in the later, you use datatype-mappings and predicate-mappings.
For example, we can add a triple that directly points to another by using the :triple-id
AllegroGraph datatype. This provides a simple and light-weight reification mechanism but note that it is outside the boundaries of RDF. Here we add one triple that describes Gary's birthdate and another that says the first is wrong (see the section on simple reification for more details).
> (let ((new-id (add-triple !o:gary !o:birthdate
(value->upi "1924-03-13" :date))))
> (add-triple !o:data !o:incorrect (value->upi new-id :triple-id)))
As a second example, here is how to specify that the datatype xsd:double
maps to an AllegroGraph :double-float
and the predicate <http://www.example.com/predicate#age> maps to an :unsigned-byte
> (setf (datatype-mapping
"<http://www.w3.org/2001/XMSchema#double>") :double-float)
:double-float
> (setf (predicate-mapping
"<http://www.example.com/predicate#age>") :unsigned-byte)
:unsigned-byte
Now when you load an N-Triples file, AllegroGraph will example each triples to see if it satisfies the mappings. When it does, then an encoded-triple will be added to the triple-store. Depending on your needs, you can even tell AllegroGraph to only load encoded-triples and not worry about strings at all. This can provide tremendous spaces savings and also gives you the benefit of range queries.
In particular, if we add the triple
(load-ntriples-from-string
"<http://www.example.com/simple/gary>
<http://www.example.com/predicate#age>
\"78\" ." :always-save-string-literals nil)
Then the triple-store will have one new encoded triple whose object
contains the encoded UPI with the value of 78 and the type-code of :unsigned-byte
.
These constants can be used to specify a UPI's type-code. See upi->value and value->upi for more details.
The types +long-88+
and +unsigned-long-88+
are similar to the standard RDF long integer types but extend the range to 88 bits.
Type-code information functions
code
. See type-name->type-code and supported-types for more details. The numbers can come from the type-names returned by supported-types or can correspond to RDF node types like :blank-nodes
, :resources
and :literal
. The function returns nil if the code does not correspond to any type.
Returns the type code associated with the name
. See type-code->type-name and supported-types. The name
can be one of the supported-types or one of:
- :blank-node
- :resource
- :literal
- :literal-language
- :literal-short
- :literal-typed
The function returns nil
if there is no type-code corresponding to name.
UPI and value conversion functions
Decodes UPI and returns the value, the type-code and any extra information as multiple values.
upi
- the UPI to decode:db
- specifies the triple-store from which the UPI originates.
The value, type-code, and extra information are interpreted as follows:
- value - a string representing the contents of the UPI
- type-code - an integer corresponding to one of the defined UPI types (see supported-types for more information). You can use type-code->type-name to see the English name of the type.
- extra - There are three disjoint sets of literals in RDF:
- "simple literals" -- a string.
- literals with datatypes
- literals with language annotations.
A literal cannot have both a language and a datatype; if a literal has type-name
:literal-typed (i.e., its type-code
is 2), then the extra
value is a datatype URI; if its type-code
is 3, then extra
will be the language code.
Examples:
> (upi->value (value->upi 22 :byte))
22
18
nil
> (upi->value (upi (literal "hello" :language "en")))
"hello"
3
"en"
See value->upi for additional information.
Returns a UPI
that encodes value
using type encode-as
.
encode-as
can be a type-code or a type-name (see supported-types and type-name->type-code for details. If a upi
keyword argument is not supplied, then a new UPI will be created. See upi->value for information on retrieving the original value back from an encoded UPI.
Note that value->upi
can not create hashed UPIs (i.e., UPIs whose value must be stored in the string dictionary. To create these, use intern-resource and intern-literal.
Triple-store type-mapping functions
Return a list of the datatype and predicate mappings of db
.
- :db - defaults to *db*.
Each item in the list returned consists of a list of three elements:
- the URIref used for the mapping (predicate or datatype)
- the type-code of the mapping
- a keyword that indicates if the mapping is a
:datatype
or:predicate
mapping.
Returns the type encoding for part. Part should be XML Schema type designator. For example:
> (datatype-mapping "http://www.w3.org/2001/XMSchema#unsignedByte")
:unsigned-byte
The scope of the mapping is the db. Use (setf datatype-mapping) to add an association between a datatype and an encoded UPI type
Applies fn
to each datatype and predicate mapping of db
.
- :db - defaults to *db*.
fn
should be a function of three arguments. For each mapping, it will called with
- the URIref used for the mapping (predicate or datatype)
- the type-code of the mapping
- a keyword that indicates if the mapping is a
:datatype
or:predicate
mapping.
(See collect-all-type-mappings if you just want a list of the mappings.).
Returns the type encoding for part. Part should be the URIref of a predicate. For example:
> (predicate-mapping !<http://www.example.org/property/height>)
:double-float
The scope of the mapping is the db
. Use (setf predicate-mapping)
to create a mapping between a URIref of a predicate and one of AllegroGraph's supported-types.
> (setf (predicate-mapping !<http://www.example.org/property/height>)
:double-float)
:double-float
Federation
Managing Massive Data - Federation
The block diagram we saw above is abstract: it can be implemented in many different ways. AllegroGraph 3 uses the same programming API to connect to local triple-stores (either on-disk or in-memory), remote-triple-stores and the entirely new federated triple-store. A federated store collects multiple triple-stores of any kind into a single virtual store that can be manipulated as if it were a simple local-store. Federation provides three big benefits:
- it scales well,
- it makes triple-stores more manageable, and
- it makes data archive extremely simple.
A high-level description of these benefits is provided in the AllegroGraph introduction. This guide focuses on the classes that are used to build a federation. You can find examples in the federation tutorial and learning center.
AllegroGraph's internal architecture
Internally, an open AllegroGraph triple-store is an instance of one of the classes depicted below. Most of the time, you won't need to be concerned with this class implementation because AllegroGraph will manage it transparently. We're depicting them here because they also serve to illustrate many of AllegroGraph's capabilities.
Let's look at each of these in turn.
An Abstract-triple-store defines the main interfaces a triple-store must implement. This class has four main subclasses:
concrete-triple-stores manage actual triples whereas the other three function as wrappers between real triples and the store.
federated-triple-stores provide mechanisms to group and structure arbitrary collections of other triple-stores.
Encapsulated-triple-stores let us add new behaviors to existing stores in a controlled and easily optimized fashion. The best example of an encapsulated-store is a reasoning-triple-store which endow triple-stores with RDFS++, rule based or other reasoning engines. Other encapsulated-store examples are graph-filtered-triple-store and ground-only-triple-store.
Finally, a remote-triple-store lets AllegroGraph use triple-stores being served by other processes either locally or anywhere on the network. These triple-stores can be other AllegroGraph stores or connections to Oracle and Sesame ones. 8
By combining these four classes, you can build a triple-store composed of leaf stores from anywhere, implementing differing reasoning rules, from entirely different architectures and treat them as if they comprise a single unified store living on your desktop.
Create a new federated triple-store named name
which federates each of the triple-stores listed in stores
. This also sets *db*
to the value of the federated store.
A error of type name-in-use-error
is signaled if name
already names a triple-store (see find-triple-store).
Create a new encapsulated-triple-store wrapping db
and and return it.
The new store will be named name
and will be of type wrapper-class
(which must be a subclass of encapsulated-triple-store. The additional wrapper-args
are passed along to the newly created store.
Create an encapsulation that allows only some triples to be seen in the inner store.
db
- the store to be encapsulated. The default is taken from*db*
.name
- a unique name for the new store. The default is to prefix the name of the inner withgraph-filtered-
and add a gensym suffix.graphs
- A non-empty list of triple part specifiers. Only the triples in the graphs specified by this list are visible in the encapsulated store.cached-wrapper-key
- If this argument isnil
, the call creates a new instance of a filtering wrapper. If the argument ist
, a new key is generated from the list of graphs. This key will be equalp to any other key generated from the same set of graphs. If the argument is any other non-nil value, it is used as a key in an equalp hash-table; if a previously created wrapper is found, the previous instance is returned. If no entry is found, a new wrapper is created and saved in the table. The default value is taken from the variable*cached-wrapper-key*
. The initial value of this variable isnil
.
Remove one layer of encapsulation from a triple store.
If the triple store is not encapsulated, then it it returned unchanged. If it is an encapsulation, then the immediate inner store is returned. This may be yet another encapsulation.
In many cases, ground-triple-store is the more appropriate operation. In some cases, some form of db-find-inner-store must be called instead. Sometimes even db-find-inner-store is not the right one.
This is a deprecated and obsolete macro.
It expands to a call equivalent to inner=triple=store and thus removes one layer of encapsulation if possible.
In many cases this operation is not what is intended and [ground-triple-store] is a more appropriate function.
Signal a warning for usage of this obsolete and ambiguous function.
This function returns a triple store that does not contain any inferred triples.
If the given triple store is not a reasoning store, then it is returned unchanged.
If the triple store is a reasoning encapsulation, then the inner triple store is returned.
In some cases, the function returns a new encapsulated store instance that represents the desired intent.
Note AllegroGraph's federated triple-stores help solve problems associated with the management and understanding of massive datasets -- AllegroGraph does not keep track of where those datasets live or how to access them. You are responsible for finding each leaf triple-store and configuring them as best suits your particular problem space. You are also responsible for ensuring that leaf triple-stores remain open for as long as the federation is in use. Franz will continue to enhance AllegroGraph's federation support and the persistence of complex relationships between triple-stores. Please be sure you are using the most recent release of AllegroGraph and to contact us ([email protected]) if you have any questions or issues.
Modifying data in federated triple-stores
With a few exceptions that will be mentioned below, AllegroGraph treats federated triple-stores as if they were read-only. The primary reason for this is that AllegroGraph cannot know which of the leaf triple-stores you wish to modify. You can still make modifications to a federated triple-store, but to do so you must select one of the leaf stores and modify it. The exceptions to this practice occur in federated loading and federated indexing
Federated Loading
AllegroGraph provides internal support for loading either a large N-Triples file or many small N-Triples files into all of the leaf stores of a federation simultaneously. 9 . However, the API for this ability is still in flux and is not exported. If you need to do this, please contact support and we would be happy to assist you.
Federated indexing
AllegroGraph also supports simultaneously indexing the leaves of a federated triple-store. When an indexing command is issued, each separate store is tasked to handle its own indexing. This provides another mechanism to divide large indexing tasks across multiple machines.
Federation, triple-ids, default-graphs and blank nodes
Federation adds a new ambiguity to triples, the default-graph and blank node identifiers: from which leaf store did they come? To see the sort of problem that can arise, imagine that we federate two small stores into one as in the figure below:
Now let's try a simple query: What is the rdf:type
of the thing whose ex:isNamed
is <Gary>
? To answer this, we would first ask for the triples whose predicate is ex:isNamed
and whose object is <Gary>
and find this:
_:anon1 ex:isNamed "Gary"
then we would ask for the triples whose subject is _:anon1
and whose predicate is rdf:type
. If the federation could not tell blank nodes from different stores apart, then it would give us back two answers:
_anon1 rdf:type <Human>
_anon1 rdf:type <Dog>
and that would be wrong!
To prevent this, AllegroGraph keeps track of the originating triple-store for each blank node, triple-id and default-graph UPI. If you look at any of these UPIs or triples in its raw form (i.e., if enable-print-decoded is nil), then you will see that some of the bytes in these data-structures encode the triple-store's ID.
Franz is still exploring the semantics surrounding some of these issues (for example, sometimes if may make more sense to allow multiple leaf stores to use the same default-graph UPI) and will continue to improve federation support by making it more flexible without giving up its speed or ease of use.
Simple Reification
Suppose I have triple t that states s p o and I want to further claim that I believe it. I'd like to say:
- name:Gary believes t
This ability to talk about an assertion is called reification. In RDF, reifying a triple requires creating a new blank node (_:anon
) so that we can say
- name:Gary believes _:anon
and then making (at least) four assertions:
- _:anon is rdf:type rdfs:Statement,
- _:anon has rdfs:subject s,
- _:anon has rdfs:predicate p , and
- _:anon has rdf:object o
This is a lot of work when all we really want is to say something about an assertion. Because AllegroGraph provides both persistent triple-ids and encoded UPIs, we can reify another triple by saying simply:
- name:Gary believes [the triple-id of t]
In Java, the code for this would look like:
AllegroGraph ag;
Triple t;
...
ag.addStatement("<name:Gary>", "<some:believes>",
ag.createEncodedLiteral(t.queryAGId(), "triple-id"));
and in Lisp, we would use value->upi with a type-code of +triple-id-tag+. You can find another example and more discussion of AllegroGraph's direct reification in the AllegroGraph Tutorial.
SPARQL Query Language
parse-sparql
takes a string and parses it into an s-expression format. A parse error will result in a sparql-parse-error
being raised.
This function is useful for three reasons: validation and inspection of queries, manual manipulation of query expressions without text processing, and performing parsing at a more convenient time than during query execution.
You do not need an open triple store in order to parse a query.
default-base
and default-prefixes
allow you to provide BASE
and PREFIX
arguments to the parser without inserting them textually into the query.
default-base
should be nil
or a string, and default-prefixes
can either be a hash-table
(string prefix to string expansion) or a list similar to db.agraph:*standard-namespaces*
.
parse-sparql
returns the s-expression representation of the query string.
run-sparql
takes a SPARQL query as input and returns bindings or new triples as output.
Since AllegroGraph 3.0 it is a convenient wrapper for the db-run-sparql methods specialized on particular database classes and query engines. You might consider using those methods directly to gain more control over the execution of your queries.
You should consider specifying an engine
argument in your invocations of run-sparql; the choice of default execution engine is not guaranteed to remain the same in future releases.
Allowable values for engine
are keyword symbols returned by get-sparql-query-engines.
The precise arguments supplied to run-sparql vary according to the query engine. These are the typical arguments expected by the default engines.
SELECT
and ASK
query results will be presented according to the value provided for results-format
, whilst the RDF output of DESCRIBE
and CONSTRUCT
will be serialized according to rdf-format
. Both of these arguments take keyword values.
If the format is programmatic (that is, it is intended to return values rather than print a representation; :arrays
is an example) then any results will be returned as the first value, and nothing will be printed on output-stream
.
The
query
can be a string, which will be parsed byparse-sparql
, or an s-expression as produced byparse-sparql
. If you expect to run a query many times, you can avoid some parser overhead by parsing your query once and callingrun-sparql
with the parsed representation.If
query
is a string, thendefault-base
anddefault-prefixes
are provided to parse-sparql to use when parsing the query. See the documentation for that function for details. Parser errors signaled within parse-sparql will be propagated onwards byrun-sparql
.Results or new triples will be serialized to
output-stream
. If a programmatic format is chosen for output, the stream is irrelevant. An error will be signaled ifoutput-stream
is not astream
,t
, ornil
.If
limit
,offset
,from
, orfrom-named
are provided, they override the corresponding values specified in the query string itself. AsFROM
andFROM NAMED
together define a dataset, and the SPARQL Protocol specification states that a dataset specified in the protocol (in this case, the programmatic API) overrides that in the query, if eitherfrom
orfrom-named
are non-nil
then any dataset specifications in the query are ignored. You can specify that the contents of the query are to be partially overridden by providingt
as the value of one of these arguments. This is interpreted as 'use the contents of the query'.from
andfrom-named
should be lists of URIs: future-parts, UPIs, or strings.default-dataset-behavior
controls how the query engine builds the dataset environment ifFROM
orFROM NAMED
are not provided. Valid options are:all
(ignore graphs; include all triples) and:default
(include only the store's default graph).default-graph-uris
allows you to specify a list of resources which, when encountered in the SPARQL dataset specification, are to be treated as the default graph of the store. Each resource can be a resource UPI, resource future-part, or a URI string. For example, specifying '("http://example.com/default") will cause a query featuring
FROM
to execute against the union of the contents of the named graph <http://example.com/baz>
and the store's default graph, as determined by (default-graph-upi db)
.
with-variables
should be an alist of variable names and values. The variable names can be strings (which will be interned in the package in which the query is parsed) or symbols (which should be interned in the package in which the query is to be, or was, parsed). The variable names can include or omit a leading '?'. Note that a query literal in code might be parsed at compile time. Using strings is the most reliable method for naming variables.
Before the query is executed, the variables named after symbols will be bound to the provided values.
This allows you to use variables in your query which are externally imposed, or generated by other queries. The format expected by with-variables
is the same as that used for each element of the list returned by the :alists
results-format
.
db
(*db*
by default) specifies the triple store against which queries should run.destination-db
(db
by default) specifies the triple store against which Update modifications should take place. This is primarily of use whendb
is a read-only wrapper around a writable store, such as when reasoning has been applied.If
verbosep
is non-nil
, status information is written to*sparql-log-stream*
(*standard-output*
by default).
Three additional extensions are provided for your use.
If
extendedp
is true (or*use-extended-sparql-verbs-p*
is true, and the argument omitted) some additional SPARQL verbs become available.SUM
,AVERAGE
,MEDIAN
,STATS
,CORRELATION
, andCOUNT
can all be used in place ofSELECT
. These verbs are still experimental and undocumented, and can only be used with the:allegrograph-2
query engine.extendedp
also controls other syntactic extensions in SPARQL queries, such asGEO
syntax. Extensions are enabled by default in all versions of AllegroGraph after 3.2.If
memoizep
is true (or*build-filter-memoizes-p*
is true, and the argument omitted) calls to SPARQL query functions (such asSTR
,fn:matches
, and extension functions) will be memoized for the duration of the query. For most queries this will yield speed increases whenFILTER
orORDER BY
are used, at the cost of additional memory consumption (and consequent GC activity). For some queries (those where repetition of function calls is rare) the cost of memoization will outweigh the benefits. In large queries which call SPARQL functions on many values, the size of the memos can grow large.
Memoization also requires that your extension functions do not depend on side-effects. The standard library is correct in this regard.
- In some circumstances you can achieve substantial speed increases by sharing your memos between queries. Create a normal
eql
hash-table with(make-hash-table)
, passing it as the value of thememos
argument torun-sparql
. This hash-table will gradually fill with memos for each used query function.
If you wish to globally enable memoization, set the variables as follows:
(progn
(setf *build-filter-memoizes-p* t)
(setf *sparql-sop-memos* (make-hash-table)))
Be aware that the size of *sparql-sop-memos*
could grow very large indeed. You might consider using a weak hash-table, or periodically discarding the contents of the hash-table.
load-function
is a function with signature(uri db &optional type)
ornil
. If it is a function, it is called once for eachFROM
andFROM NAMED
parameter making up the dataset of the query. The execution of the query commences once each parameter has been processed. Thetype
argument is either:from
or:from-named
, and theuri
argument is a part (ordinarily afuture-part
) naming a URI. The default value is taken from*dataset-load-function*
. You can use this hook function to implement loading of RDF before the query is executed.
The values returned by run-sparql
are dependent on the verb used. The first value is typically disregarded in the case of results being written to output-stream
. If output-stream
is nil
, the first value will be the results collected into a string (similar to the way in which cl:format
operates).
The second value is the query verb: one of :select
, :ask
, :construct
, or :describe
. Other values are possible in extended mode.
The third value, for SELECT
queries only, is a list of variables. This list can be used as a key into the values returned by the :arrays
and lists
results formats, amongst other things.
Individual results formats are permitted to return additional values.
permitted-verbs
is a keyword, either:all
or:read-only
. This defaults to:all
, and will permit any kind of SPARQL or SPARQL/Update query. Use:read-only
to allow onlySELECT
,ASK
,DESCRIBE
, andCONSTRUCT
queries. Note that you must also enable extended mode (using:extendedp :update
) to use SPARQL/Update operations.
format
argument. See the documentation for run-sparql for more information.
Run the provided query, using the results to construct a new graph. The new graph is either returned or serialized onto output-stream
as specified by the format
argument. construct-pattern
must be a list of triple patterns. query-pattern
is used as input to run-sparql-select.
See the documentation for run-sparql for more information.
UPI coercion depends on the current value of *db*!
Run the provided query, using the results to construct a new graph. The new graph is either returned or serialized onto output-stream
as specified by the format
argument. targets
is a list of resources to describe. query
is used as input to run-sparql-select to yield further resources to describe.
See the documentation for run-sparql for more information.
Run the provided query, serializing the results as specified by the format
argument. :distinct
can be t
or :distinct
, meaning full DISTINCT
processing, or :reduced
, which optionally discards duplicates.
See the documentation for run-sparql for more information.
Return a list of alists, each of which contains the values for the requested variables
in order.
If variables
is not provided, you can find the names of the ones returned in the second return value.
Return a list of lists, each of which contains the values for the requestedvariables
in order.
If variables
is not provided, you can find the names of the ones returned in the second return value.
Prolog Select
The q and q- functors
The main interface to Prolog is the function q- (for simple query). The q- functor is analogous to get-triples. There are many versions of the functor but the simplest one has three arguments (for subject, predicate and object). You can supply any combination of these arguments and the functor will iterate over all of the possible matches in the triple-store, unifying its logic variables to each result in turn. The example below assumes that enable-print-decoded is active.
> (?- (q- ?x !rdf:type ?z))
?x = {http://example/ok#ViewDerivedObject}
?z = {owl:Class}
;; type Enter
?x = {http://example/ok#UserActions}
?z = {owl:Class}
;; type period ( . )
This documentation uses the usual Prolog argument notation. A +
prefix on an argument indicates that is must be supplied (it is input to the predicate), a -
prefix indicates the argument is output and must not be supplied, and a ± prefix indicates the argument may be either.
As is usual with Prolog, you can stop the iteration by typing a period (' . '). The q- variant of the query functor even supports AllegroGraph range queries.
Query the triple-store. If the store is a simple store, then q is the same as q-. If the store is an encapsulated-triple-store (for example, a reasoning-triple-store) then the effect of q
and q-
can differ. Unify s
, p
, and o
with the triples in the store.
The third argument may be of the form (-o +o-min +o-max)
to specify a range of values for the object component of the triples. Range queries are always bypass any reasoning wrappers on the store.
Unify s
, p
, o
, and g
with the triples in the store.
The third argument may be of the form (-o +o1 +o2) to specify a range of values for the object component of the triples. Range queries always bypass any reasoning wrappers on the store.
The fourth argument may be of the form (-g +g1 +g2) to specify a range of values for the graph component of the triples. Only one of the object or graph positions may specify a range.
The fourth argument may also be of the form (-g (:member +g1 +g2 ...)) or (-g (:member . +glist)) to specify a finite set of allowed graph values.
Unify s
, p
, o
, g
, and id
with the triples in the store.
Unify s
,p
, o
, g
, id
and triple
.
Query a triple-store's ground store. If the store is not a reasoning store, then q-
is equivalent to q Unify s
, p
, and o
with the triples in the store.
The third argument may be of the form (-o +o1 +o2)
to specify a range of values for the object component of the triples. Range queries always bypass any reasoning wrappers on the store.
Unify s
, p
, o
, and g
with the triples in the store. See (q ?s ?p ?o ?g)
for a detailed description of the arguments
Unify s
, p
, o
, g
, and id
with the triples in the store.
Unify s
,p
, o
, g
, id
and triple
.
Query the triple store specified by the first argument. The remaining arguments specify s
,
p,
o, and/or
g` components as in q and q-.
The first argument must be a symbol that names a store defined in a :named-store
planner option or it must be a Prolog expression that evaluates to a triple store. The symbol *db*
can appear as a name; in that case the qd
form is equivalent to a q
form with the same triple parts. Unify s
, p
, and o
with the triples in the store.
The fourth argument may be of the form (-o +o1 +o2)
to specify a range of values for the object component of the triples. Range queries always bypass any reasoning wrappers on the store.
Unify s
, p
, o
, and g
with the triples in the store. See (q ?s ?p ?o ?g)
for a detailed description of the arguments
Unify s
, p
, o
, g
, and id
with the triples in the store.
Unify s
,p
, o
, g,
id
and triple
.
The Select Macros
You can combine multiple q clauses into a query using one of the family of select macros. These evaluate a list of Prolog clauses and then do something with the solutions found 10 . There are three dimensions in which this family of macros differ:
distinct - if the macro has
distinct
in its name, then each unique solution is only returned once, i.e., it will only occur in the result set once or only be used as a callback once.translation - If the macro has a
0
(zero) in its name, then it will return solutions whose UPIs are not-translated. Otherwise, it will look up the UPIs in the string dictionary and return those. Operations like select0 can therefore be much faster than select and are more natural if the UPI will be used in a further query.callbacks - If the macro has
callback
in its name, then you must provide a callback function that will accept a solution and do something with it. The callback function argument is evaluated and may be either a function of one argument or the name of such a function.
Each macro takes as its first argument a template
. Often the template is a a single var
or a simple list of vars
. But in general the template may be a tree composed of Lisp data and Prolog variables
The select macros will find each solution to the list of supplied Prolog clauses. It will then build up a fresh instance of the template tree with each Prolog var in the tree replaced by the variable in the solution. For example:
> (select ((:name ?name) (:age ?age))
(q- ?x ?isa !ex:person)
(q- ?x ?hasname ?name)
(q- ?x ?hasage ?age))
would return a list of results like
(((:name "Gary") (:age 12))
((:name "Xaviar") (:age 56))
...
)
Select planner options described below can also be used to control the behavior of the select expression and the format of the result. If planner options are used for this purpose, it is recommended to use the basic select
macro instead of the variants. Using a variant witha conflicting option may yield unexpected results.
You can find other examples of using select in the Using Prolog with AllegroGraph tutorial.
Evaluate the Prolog clauses
and return a list of all solutions. Each solution is a copy of the template (which is a tree) where each Prolog variable is replaced by its string value. See select0 if you want UPIs rather than strings.
The code generated by all the variants of this macro always binds *db*
. Consequently, any modification of this variable in the body clauses will disappear when control exist the code.
clauses
and return a list of all solutions. Solutions consist fresh copies of the template (which is a tree) where each Prolog variable in the tree is replaced by its UPI value in the solution. If you are interested in part-names rather than raw UPIs, see select.
callback
once for each solution. Solutions consist of a fresh copy of the template with each var
replaced by the string value of the Prolog variable in the solution. The callback argument is evaluated. See select0/callback if you are want UPIs rather than strings.
callback
once for each solution. Each solution is a copy of the template with each Prolog variable replaced by its UPI. The callback argument is evaluated. See select/callback if you want strings rather than UPIs.
clauses
and return a list of all distinct solutions. Each solution is a copy of the template where each Prolog variable in the tree is replaced by its string value See select0-distinct if you want UPIs rather than strings.
clauses
and return a list of all distinct solutions. Each solution is a copy of the template (which is a tree) where each Prolog variable is replaced by its UPI value. See select-distinct if you want strings rather than UPIs,
callback
once for each distinct solution. Each solution is a fresh copy of the template with each var
replaced by the string value of the Prolog variable in the solution. The callback argument is evaluated. See select0-distinct/callback if you want UPIs rather than strings.
callback
once for each distinct solution. Each solution is a fresh copy of the template with each var
replaced by the UPI value of the Prolog variable in the solution. The callback argument is evaluated. See select-distinct/callback if you want strings rather than UPIs.
Prolog and range queries
You can make range queries using the same prolog q
functor as you do to make non-range queries. We support range queries on either the object
or the graph
fields (but not on both simultaneously in the same clause. What follows is a list of all the 9 possibilities for q
. Each token in the functor may be a UPI literal, a Prolog variable (possibly anonymous) or nil. We use a -
prefix on a token to indicate that it is a placeholder and it cannot be used as a variable; a +
prefix to indicate that the token must be supplied and a ?
to indicate that the token is either. .
Suppose, for example, that we use AllegroGraph to record the velocities during a mythical 1000-km trip:
;;;;;;;;;;;;;;;;;;;; A 1000 KM trip.
(in-package :triple-store-user)
(create-triple-store "My1000KmTrip" :if-exists :supersede)
(register-namespace "t" "http://www.me.disorg#"
:errorp nil)
;; add triples describing a 1000-km trip
(loop with km = 0 ; distance in km
with time = 0 ; time in seconds
as kmh = (random 80.0) ; velocity in km/hr
do (add-triple
!t:me
!t:distance
(value->upi km :double-float)
:g (value->upi time :unsigned-long))
(add-triple
!t:me
!t:velocity
(value->upi kmh :double-float)
:g (value->upi time :unsigned-long))
(incf km (/ kmh 60))
(incf time 60)
count 1 ; Number of data points, which is
; also the duration in minutes.
while (< km 1000))
(index-all-triples)
We can then use the following select
query to find triples that represent the 1-minute periods where average speed is 75..80 km/h and the distance at which it occurred.
(loop for (time speed distance)
in (sort (select (?time ?v ?distance)
(lisp ?v75 (value->upi 75 :double-float))
(lisp ?v80 (value->upi 80 :double-float))
(q- !t:me !t:velocity (?v ?v75 ?v80) ?time)
(q- !t:me !t:distance ?distance ?time))
(lambda (x y) (< (first x) (first y))))
do (format t "~7d ~5f ~5f~%" (/ time 60) speed distance))
This last form could be written more succinctly using the ++ syntax explained in the tutorial:
(loop for (time speed distance)
in (sort (select (?time ?v ?distance)
(q- !t:me
!t:velocity
(?v (value->upi 75 :double-float)
(value->upi 80 :double-float))
?time)
(q- !t:me !t:distance ?distance ?time))
(lambda (x y) (< (first x) (first y))))
do (format t "~7d ~5f ~5f~%" (/ time 60) speed distance))
Other AllegroGraph Prolog functors
subject
with the subject field of triple
.
predicate
with the predicate field of triple
.
object
with the object field of triple
.
graph
with the graph field of triple
.
triple-id
with the triple-id field of triple
.
part1
is part= to part2
. Each of part1
and part2
should be UPIs, future-parts or strings in N-Triples format that can be converted into resources or literals.
Select Query Planner
AllegroGraph's Prolog query language (select) includes an optimizer that speeds up complex queries via:
- clause re-ordering,
- clause transformations and simplifications,
- generation and use of UPI maps.
As part of the transformation process, the query-optimizer works with AllegroGraph's dynamic RDFS++ reasoner to perform some inferences at query planning-time (rather than repeatedly during query run-time).
The optimizer works automatically and in most situations you do not need to do anything special to make use of it: simply ask your Prolog query and let the optimizer run. Query optimization is a black art, however, so sometimes you may want to see what is happening inside AllegroGraph. Furthermore, there are some additional, non-automatic tuning options that you may want to consider.
AllegroGraph's query optimizer and dynamic-reasoner are both areas of active research and development. We value your feedback on both the positives and the negatives so that we can continue to make AllegroGraph the best RDF graph database for your projects.
Query plan options
Query plan options can be used to control the planning and transformation process. You can specify these options by including keyword
clauses in the body of your query. A keyword
clause is a two item list consisting of the option (a keyword
) and its value. For example, this query uses the :display-plan
option so that the generated plan will be printed to *standard-output*
:
(select0 (?x)
(:display-plan t)
(q ?x !ub:memberOf !<http://www.Department0.University0.edu>)
(q ?x !rdf:type !ub:Person))
There are four kinds of plan options: store management, introspection, planner control, and result manipulation. The current list of options is:
- store management
X :graph-filterquery-plan-option
Specifies a graph-filtered-triple-store that will be used as the default store to be queried.
The format of the option is
(:graph-filter g1 g2 ...)
wheregi
are Lisp expressions that evaluate to triple parts. The expressions are evaluated in the lexical context of theselect
expression.At most one occurrence of this option is allowed in each
select
expression. An occurrence of this option rebinds the value of*db*
for the entireselect
expression. The order of :reasoner and :graph-filter options is significant.X :reasonerquery-plan-optionSpecifies that a reasoning store will be used as the default store to be queried.
The format of the option is
(:reasoner [function] reasoner-keyword-args...)
. If the function name is ommitted. use apply-rdfs++-reasoner. The remainder of the option is used as the argument list of the call to the reasoner function.An occurrence of this option rebinds the value of
*db*
for the entireselect
expression. The order of:reasoner
and:graph-filter
options is significant.X :named-storequery-plan-optionSpecifies a named triple-store. The name may be used as the store argument of
qd
clauses in the body of theselect
expression. When aqd
clauses specifies a named store, the clause is recognized by the select planner.The format of the option is
(:named-store name store-expression)
wherename
must be a symbol that is not the symbol*db*
and cannot be interpreted as a Prolog variable, andstore-expression
is a Lisp expression that evaluates to a triple store. The expression is evaluated once when theselect
expression is evaluated.This option may occur multiple times. If a name is specified more than once, only the rightmost definition is seen by the body clauses. The ordering of
:named-store
options is significant, and the ordering with respect to:graph-filter
and:reasoner
options is also significant.
- introspection
X :display-planquery-plan-optionprints a representation of the transformed query to
*standard-output*
.X :plan-onlyquery-plan-optioncreate the query plan but do not actually run it.X :verbosequery-plan-optionprint details of the estimation process to*standard-output*
. - planner control
X :remove-redundant-type-filtersquery-plan-optionindicate whether or not to remove
rdf:type
clauses that seem to be redundant from the query. A type clause might be redundant because it can be inferred from other clauses (e.g., via domain or range information).X :reorderquery-plan-optionindicate whether or not to perform clause re-ordering.X :use-mapsquery-plan-optionindicate whether or not to useUPI maps
.X :use-plannerquery-plan-optionindicate whether or not to use the query planner.X :use-transformsquery-plan-optionindicate whether or not to transform clauses into putatively simpler forms. - result manipulation
X :count-onlyquery-plan-optionignore the result template and return only the count of results.X :distinctquery-plan-optionreturn only distinct results (this can be achieved by using select-distinct and its kin).X :limitquery-plan-optionReturn at most
limit
results. If:distinct
is also true, the at mostlimit
distinct results are returned.
More options may be added in the future; See below for details on how you can determine which options exist and their current settings.
Query Planner Examples
The following example queries are taken from the LUBM Benchmark. We will cover several examples showing the different sorts of transformations that the query planner performs.
type filter removal and transformations
Q3 asks for all of the publications of a particular professor:
(select0 (?x)
(:display-plan t)
(q ?x !ub:publicationAuthor !u0d0:AssistantProfessor0)
(q ?x !rdf:type !ub:Publication))
We use the :display-plan
option so that we can see how AllegroGraph interprets the query. Note that the rdfs:domain of !ub:publicationAuthor is !ub:Publication so the second clause is redundant and can be removed.
11 Secondly, !ub:publicationAuthor does not participate in any RDFS++ reasoning for this store. Thus the planner transforms the q
clause into an internal q/upis-
one:
;; Return 1 variables: ?x
;; estimate: 256 results per binding
(q/upis- ?x {publicationAuthor} {AssistantProfessor0})
The q/upis-
functor performs certain extra though minor optimizations over and above the more generic q-.
clause re-ordering and more transformations
Query 2 asks for a listing of students who take a course from their advisors:
(select0 (?x ?y ?z)
(:verbose t)
(:display-plan t)
(q ?x !ub:advisor ?y)
(q ?x !ub:takesCourse ?z)
(q ?y !ub:teacherOf ?z)
(q ?x !rdf:type !ub:Student)
(q ?y !rdf:type !ub:Faculty)
(q ?z !rdf:type !ub:Course))
Note that we've used the :verbose
query plan option to display additional information during the query process. The information display below is unlikely to match what you see since it is dependent on the inner workings of the planner and the particular store being used. Here is the information from the planning process.
;; Compute estimate: nil {advisor} nil nil : 204,997
;; Compute estimate: nil {takesCourse} nil nil : 1,433,856
;; Compute estimate: nil {teacherOf} nil nil : 108,288
;; Compute estimate: nil {type} {ResearchAssistant} nil : 36,608
;; Compute estimate: nil {type} {GraduateStudent} nil : 126,208
;; Compute estimate: nil {type} {UndergraduateStudent} nil : 393,984
;; Compute estimate: nil {type} {Student} nil : 256
;; Choose q ?y {teacherOf} ?z: approximately 108,288 bindings for ?y, ?z.
;; Compute estimate: nil {advisor} 108288 nil : 9
;; Compute estimate: nil {takesCourse} 108288 nil : 14
;; Compute estimate: nil {type} {ResearchAssistant} nil : 36,608
;; Compute estimate: nil {type} {GraduateStudent} nil : 126,208
;; Compute estimate: nil {type} {UndergraduateStudent} nil : 393,984
;; Compute estimate: nil {type} {Student} nil : 256
;; Choose q ?x {advisor} ?y: approximately 9 bindings for ?x.
;; Compute estimate: 8.177778 {takesCourse} 108288 nil : 1
;; Compute estimate: 8.177778 {type} {ResearchAssistant} nil : 1
;; Compute estimate: 8.177778 {type} {GraduateStudent} nil : 1
;; Compute estimate: 8.177778 {type} {UndergraduateStudent} nil : 1
;; Compute estimate: 8.177778 {type} {Student} nil : 1
;; Choose q ?x {takesCourse} ?z.
;; Compute estimate: 1 {type} {ResearchAssistant} nil : 1
;; Compute estimate: 1 {type} {GraduateStudent} nil : 1
;; Compute estimate: 1 {type} {UndergraduateStudent} nil : 1
;; Compute estimate: 1 {type} {Student} nil : 1
;; Choose q ?x {type} {Student}.
And now the generated plan:
;; Return 3 variables: ?x, ?y, ?z
(db.agraph::find-or-create-map #:?map13983 {advisor} :object :subject)
(db.agraph::find-or-create-map #:?map13984 {takesCourse} :object
:subject)
(db.agraph::find-or-create-map #:?map13985 (?? +rdf-type-uri+) :object
:subject)
!
;; estimate: 108,288 results per binding
(q/upis- ?y {teacherOf} ?z)
;; estimate: 9 results per binding
(db.agraph::q-upi-table #:?map13983 ?y ?x)
;; estimate: 1 results per binding
(db.agraph::q-upi-table #:?map13984 ?z ?x)
;; estimate: 4 results per binding
(lispp*
(let ((reasoner (reasoner *db*)))
(declare (ignorable reasoner))
(or (db.agraph.upi-maps:upi-pair-present-p #:?map13985
{UndergraduateStudent} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985
{GraduateStudent} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985
{ResearchAssistant} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985 {Student}
?x))))
The compute estimates
shows how the query planner is attempting to reorder the clauses more favorably. The planner currently uses a simple greedy heuristic but this will change as the planner evolves. Once the ordering is determined, the transformation process begins. There are two main transformations used in this query: UPI maps and reasoner simplification.
Transformations
The query-planner and dynamic-reasoner use the following broad categories of transformation: reordering, UPI maps, reasoner simplifications, and clause simplifications. Generally speaking, you should not worry about the exact nature and syntax of the transformations as these are both likely to change.
Reordering
When a query has many clauses, the order in which they are executed can have a huge effect on total query speed. The query-planner uses a set of heuristics and statistical information about the triple-store in order to try and determine the best order in which to run the query. The heuristics may fail especially for complex queries. If you suspect that the planner is ordering your query incorrectly, use the :display-plan
and :reorder
query-plan-options to diagnose the problem.
UPI maps transformation
A UPI map is a persistent index mapping one column of a triple to another.
12 Typically, the index is over only a portion of all of the triples in a store. For example, a UPI map might map from object to subject for all rdf:type
triples in the store. This map would make determining whether or not some x
was of type T
very fast. UPI maps provide a cache for certain kinds of queries and can dramatically improve query speed.
The query-planner and dynamic-reasoner determine when building UPI maps makes sense for a query and will build them as necessary the first time that they are needed. Once built, maps can be reused until the store changes. See the reference section below for some variables that help control how the query planner uses UPI maps.
The UPI map transformation appears in a query-plan in two places:
- The finding or building of the map. This looks like
- The use of the map:
(find-or-create-map #:?map13983 {advisor} :object :subject)
(db.agraph::q-upi-table #:?map13983 ?y ?x)
The :use-maps
query-plan-option controls whether or not a query will use any UPI maps.
reasoner simplification
The dynamic-reasoner examines each clause in the context of the store when the query is run. Depending on the store's ontology, many clauses can be re-written into faster executing forms at query-plan time. Most of the transformations let AllegroGraph move computation out of the inner-loop
of the reasoner; they can help greatly increase query speed. As an example, consider how AllegroGraph can transform (q ?x !rdf:type !ub:Student)
. The type information in the store will not change while the query is running, so AllegroGraph can consult the ontology once and determine that ?x
can be inferred to be a student
if there is a ground triple that says ?x
is of rdf:type
ub:UndergraduateStudent
, ub:GraduateStudent
, ub:ResearchAssistant
, or ub:Student
. Adding UPI maps into the mix, the finished transformation looks like:
(lispp*
(or (db.agraph.upi-maps:upi-pair-present-p #:?map13985
{UndergraduateStudent} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985
{GraduateStudent} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985
{ResearchAssistant} ?x)
(db.agraph.upi-maps:upi-pair-present-p #:?map13985 {Student}
?x)))
The set of transformation and their actual syntax will change over time as the query-planner and dynamic-reasoner become more capable.
Clause simplification
Though reasoning transformations provide the most dramatic speedups, there are some other transformation that can also make queries more efficient. Most of these have more to do with reducing consing
and shaving small amounts off of clause execution. An example is the transformation of q- clauses into asserted-1
, asserted-po
, asserted-sp
, or asserted-p
clauses. Because the latter four have slightly simpler execution paths, they provide measurable increases in speed.
Note that these asserted-*
functors may change or disappear in future revisions and should not be relied in outside of the query planner itself.
Store Management Options
The select options :graph-filter
and :reasoner
allow a program to modify the store used in the select query without affecting the current default store in the surrounding program.
A query such as
(select (?x)
(:graph-filter !ex:g1)
(q ?x !ex:pred ?y))
is applied to the subset of triples where the graph component is !ex:g1
.
And the query
(select (?x)
(:graph-filter !ex:g1)
(:reasoner)
(q ?x !ex:pred ?y))
is applied to all the triples that can be inferred from the set of triples where the graph component is !ex:g1
.
In both cases the triple store (bound to db) in the surrounding context is not affected.
Note that a query such as
(select (?x)
(:reasoner)
(:graph-filter !ex:g1)
(q ?x !ex:pred ?y))
is likely to yield surprising or unexpected results. In this case, the graph filter is applied to the triples generated by the reasoner. But in the default case, these inferred triples use the default graph of the base store as the graph component of the inferred triples. It would be more constructive to pose the query
(select (?x)
(:reasoner :inferred-graph !ex:g2)
(:graph-filter !ex:g1 !ex:g2)
(q ?x !ex:pred ?y))
Reference
name
.
The location where UPI maps are kept for this store.
The persistent and settable property helps control where AllegroGraph will search for UPI maps for this triple-store. If nil, the UPI maps are kept in the maps
sub-directory of the triple-store's directory. If non-nil, then UPI maps will be kept in the directory this property specifies.
Though this property is necessary to use UPI maps with a read-only triple-store, it also adds several risks to triple-store management. Care must be taken that multiple triple-stores do not place their UPI maps in the same directory -- the results in this situation are undefined. Secondly, UPI maps in an external directory will not be automatically deleted. This issues will be ameliorated in future-releases
Controls whether or not UPI maps are used with type inference.
If true, then the dynamic-reasoner will build a UPI map on rdf:type and use this map for subsequent type inference.
This variable will be nil or contain an instance of the type query-plan
.
query-plan
is an opaque data structure. It should not generally be used other than internally.
Controls whether or not UPI maps may be used for sub-property reasoning.
If true, then the dynamic-reasoner may decide to use UPI maps when a predicate is involved in sub-property reasoning.
RDFS++ Reasoning
AllegroGraph's reasoner supports the following predicates:
- rdf:type
- rdfs:domain
- rdfs:range
- rdfs:subClassOf
- rdfs:subPropertyOf
- owl:inverseOf
- owl:sameAs
- owl:TransitiveProperty
and OWL hasValue reasoning (see the reasoner tutorial and the hasValue reasoning tutorials for more details).
Note that the reasoner is designed to efficiently answer questions like "What are properties of this subject?" or "Tell me all the subjects that have this type?" It is not designed for efficiently determining all of the inferred triples in a store (e.g., "Tell me everything you know."). You should expect fast answers for queries whose predicate is specified but you will not see such good performance for more open-ended calls to get-triples. We will continue to enhance the reasoner as AllegroGraph develops.
The following additional functions and variables are also part of the reasoner:
Return a new reasoning-triple-store that encapsulates db
and adds an rdfs++-reasoner.
db
- the triple-store to encapsulate. The defaults to the value of *db*.name
- the name to give the encapsulated-triple-store. Defaults to the current db-name of thedb
prefixed with rdfs++- and with a generated suffix .has-value-reasoning-enabled
- when true, enable OWL hasValue reasoning. The default is nil.inferred-graph
- This argument specifies the graph component of all inferred triples. The default is to use the default graph of the specified triple store.cached-wrapper-key
- If this argument isnil
, the call creates a new instance of a reasoning wrapper; this instance will cause a new invocation of prepare-reasoning when the first query is issued. If the argument is not nil, it is used as a key in an equalp hash-table; if a previously created wrapper is found, the previous instance is returned. If no entry is found, a new wrapper is created and saved in the table. The default value is taken from the variable*cached-wrapper-key*
. The initial value of this variable is nil.remote-reasoning
- This argument is meaningfull only when the db (or*db*
) argument is a remote-triple-store instance. A non-nil value specified that the reasoning wrapper is created on the server side. The value returned byapply-rdfs++-reasoner
is a newremote-triple-store
instance pointing to the reasoner on the server side.
db
. The new store will have a reasoner of reasoner-class
and be named name
.
triple
is the result of inference (as opposed to be physically present in the triple-store).
reasoner
of a reasoning-triple-store.
Deprecated. This variable will be removed in a future version of AllegroGraph. If your triple-store reasoning needs are simple, you can query the ground-triple-store of a reasoning-triple-store. See the reference guide for more information.
If true, then the RDFS++ reasoner will be used in queries. This will effect get-triples and the output of SPARQL and Prolog select queries.
AllegroGraph also supports hasValue reasoning.
Prepare-reasoning
is a function called internally by the AllegroGraph reasoner. It is unlikely that you will ever need to call it yourself. Its purpose is to update the internal data structures used by the reasoner.
This function has to be called before any inferences are made. It creates internal hash-tables to speed up the reasoner. In normal operation, AllegroGraph will call prepare-reasoning as necessary. You can see diagnostic messages by using the parameter verbose
which defaults to the value of (ag-property
:verbose-prepare-reasoning)
. You can also force the hash-tables to be regenerated using the force
parameter. Finally, the show-progress
keyword argument can be used to cause prepare-reasoning
to print a message for each of the hash-tables it builds.
The function prepare-reasoning returns no value.
Remote Client and Sesame HTTP Support
AllegroGraph supports a client/server environment for clients implemented in Lisp or in Java. The Lisp client API is described in Lisp Client Reference and the Java client API is described in Java Tutorial and Javadocs.
The Lisp server is managed with the following functions exported from db.agraph.
Start a server that allows client programs to access AllegroGraph triple stores.
The port argument (default 4567) is the port number where the server listens for connections.
The jport argument is unused but reserved for situations where two ports are required.
The users argument specifies the number of simultaneous connections allowed. The default is 50.
The limit argument specifies the total number of connections allowed over the life of the server. The default is nil to specify unlimited connections.
The root argument, when non-nil, specifies a default pathname for the entire Lisp image running the server.
The nanny argument may be nil or a number n of seconds. When non-nil, all connections are scanned every n seconds and triple stores opened by dead connections are closed.
The ender argument specifies a function of no arguments. This function is called just before the triple store associated with a dead connection is closed.
The timeout argument specifies a time interval in seconds. If a triple store cannot be accessed within this time interval, an error is signaled.
The idle-life argument specifies a time interval in seconds. If a triple store is open but idle for this interval, it is closed automatically (and re-opened if needed). The default is 24 hours, i.e. (* 24 60 60).
The indexing argument is currently ignored.
The worker-stream argument specifies a stream that worker threads can use for random output. The value nil specifies the system default. The value t specifies initial-terminal-io. Any other value must be a suitable stream. When running the server under the Franz Emacs-Lisp interface, the value t may be needed to avoid background-stream errors.
The error-log argument specifies a stream or file path where error information can be printed. The default is nil. When nil, the error information is sent to the client. When t, print error information on the server console. When :none, error information is not generated at all.
The verbose and debug arguments may be non-nil to trigger status and progress messages.
The eval-in-server-file is nil (client eval requests not allowed) or is a filename where each line is a regular expression of a valid Lisp expression. If the contents of the file change while the server is running the server tables are updated. The server checks the file every 10 seconds. The file must exist when the server is started. If the file is deleted while the server is running, the table is cleared, and subsequent client eval requests are disabled until the server is restarted.
The function returns two values: a server port instance that becomes the default server port, and the port number where the server is listening.
Stop an AllegroGraph server and optionally any client connections. If the wait argument is non-nil, wait for the server to be fully shut down. A numeric value is a timeout interval in seconds.
Method (agj-server)
Stop the connection identified by the argument.
Method (integer)
Stop the connection identified by integer.
Method (agj-server)
Stop the listening server. If the optional argument is non-nil, stop any running connections as well. The default is t
.
Method (null)
Stop the default listening server. If the optional argument is non-nil, stop any running connections as well. The default is t
.
This function enables or disables progress messages from client calls. The arguments and results of each call from the client are printed.
The onoff argument may be omitted, nil, :toggle, :close, a string, or any other non-nil value.
Two values are returned, the previous trace state and the new trace state, in that order.
If the argument is omitted, the function returns the current trace state.
If the argument is nil, a previous trace state is terminated.
If the argument is :toggle, the current trace state is reversed.
If the argument is :close, a previous trace state is terminated.
If the argument is a string, it should be a pathname to a writable file. The file is opened and supersedes any existing file. Trace output is initiated, and sent to the file.
- Any other non-nil value initiates trace output to standard-output.
This function maps triple store integer ids to the actual triple store instance.
The client code references each triple store by an integer identifier. This integer is printed in the ag-server-trace output.
If the tsx argument is nil or unspecified, the function returns an alist of all known triple stores.
If the tsx argument is an integer, the function returns the specified triple store instance.
- If the setdb argument is non-nil, then the current (global) value of
*db*
is set to the triple store instance.
This symbol is not used in AllegroGraph 3.0.
Global default value of indexing parameter: ((min % max) (min avg max))
value
argument may three possible values. nil is the default and initial value and allows select queries that have no escapes to Lisp code, that is, queries that do not contain the ?? syntax or calls to any of the lisp, lisp*, etc. functors. The value t allows all queries without checking, and is appropriatge only for environnments where clients can be trusted. The value :disallow blocks any use of select by clients.
Sesame HTTP Support
A sesame-server
is an instance of the sesame-server
class. It represents a server at a given host and port that can handle Sesame 2.0 HTTP requests. See the HTTP protocol reference for additional details.
This function creates a sesame-server instance and optionally starts the HTTP server. The returned value is the server instance. This value also becomes the default server.
The path argument (default is /sesame) specifies the initial part of the server URL.
The timeout argument is the default timeout value for all registered triple stores. If a triple store is not available within that number of seconds, a bad request return code is sent back to the client. The default is 15 seconds.
The idle-life argument is the default idle interval in seconds for an open triple store. If a triple store stays open but idle for this interval, it is closed automatically. The default is 24 hours.
The start argument, if non-nil, ensures that the HTTP server is running. If the value is a list, it is passed to the AllegroServe start function. The most common value is (list :port nnn).
The wserver argument may be an AllegroServe wserver instance.
The class argument (default sesame-server) allows applications to provide a sub-class.
The output-stream argument is a synonym for worker-stream retained for compatibility with previous versions of AllegroGraph. If the worker-stream argument is specified, the output-stream argument is ignored.
- If the worker-stream argument is specified, it must be a stream. This stream will be bound to standard-output, terminal-io, and debug-io in worker threads running Sesame HTTP requests. Binding this argument to initial-terminal-io may be needed when running under eli.
When the server argument is an instance of sesame-server, start that Sesame server instance.
When the server argument is nil, start a Sesame server using the default server instance.
When the server argument is an instance of sesame-server, stop that Sesame server instance.
When the server argument is nil, stop the default Sesame server instance.
When the server argument is an instance of sesame-server, make a triple store available as a Sesame 2.0 Remote Repository on that server.
If db is specified, name and directory must be omitted or consistent. If name and directory are specified, db must be omitted or consistent.
The specified database will be opened and closed as required.
Id defaults to name; it is the id by which the database will be known to clients. If id is not unique, an error is signaled.
When the server argument is nil, make a triple store available as a Sesame 2.0 Remote Repository. The default server instance is used for the operation.
Method (sesame-server)
Return the port number where this server is listening.
Method (null)
Return the port number where the default Sesame HTTP server is listening.
value
argument may three possible values. nil is the default and initial value and allows select queries that have no escapes to Lisp code, that is, queries that do not contain the ?? syntax or calls to any of the lisp, lisp*, etc. functors. The value t allows all queries without checking, and is appropriatge only for environnments where clients can be trusted. The value :disallow blocks any use of select by clients.
Specialized Datatypes
In addition to the "encoded UPIs" for the various computer numeric datatypes, AllegroGraph supports several specialized datatypes for efficient storage, manipulation, and search of Social Network, Geospatial and Temporal information.
Social Network Analysis
By viewing interactions as connections in a graph, we can treat a multitude of different situations using the tools of Social Network Analysis (SNA). SNA lets us answer questions like:
How closely connected are any two individuals?
What are the core groups or clusters within the data?
How important is this person (or company) to the flow of information?
How likely is it that this person and that person know one another?
The field is full of rich mathematical techniques and powerful algorithms. AllegroGraph's SNA toolkit includes an array of search methods, tools for measuring centrality and importance, and the building blocks for creating more specialized measures. These tools can be used with any "network" data set whether its connections between companies and directors, predator/prey food webs, chemical interactions, or links between web sites.
Navigating Through a Graph - Generators
The graph functions described below all use generators
in their definitions. A generator is a function of one-argument, a vertex, that returns a list of nodes that are connected to the vertex. The definition of connected depends on the generator. In a directed graph, connected may refer only to the nodes that point to a specific vertex or it may refer to the nodes at which the vertex points. Generators can also ignore edge direction in a graph and return a list of nodes that are adjacent to the specific vertex.
We provide several helper utilities and a generator definition language to define both simple ad complex generator functions. When the graph operations below take a generator as argument, you may supply either a function of one argument or the name of a generator that has been defined using the generator definition language.
the Generator Definition Language
The language consists of
(:objects-of &key node p)
(:subjects-of &key node p)
(:undirected &key p)
(select var select-clause*)
Define a new SNA generator function and associate it with `name.
Returns the new function. The function is defined using a simple language. See the reference guide for details on the syntax and semantics of this language.
Lookup a registered sna-generator
by name and return its associated function.
name
can be:
a generator function itself (in which case it is simply returned),
a neighbor-matrix created via build-neighbor-matrix
the name of a generator previously defined with the defsna-generator macro,
the name of a neighbor-matrix previously defined with defneighbor-matrix, or
- a symbol naming an existing function which is assumed to act as a generator.
name
with an SNA generator function. Returns the new function. If the function
is nil
, then the association is removed.
Notes
The generator returns the (distinct) union of the UPIs found by the clauses.
In both
:objects-of
and:subjects-of
, thenode
parameter is syntactic sugar and can be left off.In all three of
:objects-of
,:subjects-of
, and:undirected
, thep
variable can be a single property or a list of properties
Examples
(register-namespace "ex" "http://namespace.franz.com/namespace#")
(defsna-generator involved-with ()
(:objects-of :p (!ex:kisses !ex:intimateWith)))
(defsna-generator involved-with (node)
(:objects-of :node node :p (!ex:kisses !ex:intimateWith)))
(defsna-generator involved-with ()
(:undirected :p (!ex:kisses !ex:intimateWith)))
(defsna-generator in-movie-with (node)
(select (?x)
(q- ?x !franz:stars (?? node))))
(Note the use of Allegro Prolog ??
idiom that we use to treat the symbol node as a variable in the body of the macro.)
Saving time - the Neighbor-Matrix
Generators provide a fast and flexible mechanism to navigate though arbitrary graphs. AllegroGraph automatically saves the results of recent node expansions but generators still require repeated queries against the triple-store. If you know that you will be operating on a particular group of nodes in your graph, you can greatly increase the speed of some of the SNA algorithms by building a neighbor-matrix (which is essentially an in-memory sparse adjacency matrix) and using it rather than the generator in your queries. You can build a neighbor-matrix with build-neighbor-matrix
.
group
using generator
including all nodes reachable within max-depth
steps from group. I.e., If max-depth
is zero, then only the group will be queried; if it is one, then the cache will include the group and it neighbors; etc.
Defines a Neighbor-Matrix structure for group
using generator
including all nodes reachable within max-depth
steps from group and associates it with name
.
If max-depth
is zero, then only the group will be queried; if it is one, then the cache will include the group and it neighbors; etc.
Associate the neighbor-matrix matrix
with name
.
To remove a matrix use register-neighbor-matrix
with nil
.
The neighbor-matrix for a particular group and generator saves all of the information needed to use the SNA algorithms (but only for that group and that generator). To use it, call the algorithm you want but pass in the neighbor-matrix instead of the generator. Secondly, the group
argument to the function must be set to nil and any actor
arguments must be members of the group used to create the matrix. The following examples compute the same result:
Using just the generator
> (defsna-generator knows ()
(:undirected :p !f:knows))
#<Function (:anonymous-lambda 35) @ #x11e18772>
> (setf group (ego-group !<http://www.franz.com/ont/person-1> 2 'knows))
({person-898} {person-47649} {person-91744} {person-90811}
{person-17690} {person-59736} {person-84513} {person-63689}
{person-91562} {person-62312} ...)
> (length group)
147
> (time (group-degree-centrality group 'knows))
; cpu time (non-gc) 100 msec user, 120 msec system
; cpu time (gc) 20 msec user, 0 msec system
; cpu time (total) 120 msec user, 120 msec system
; real time 251 msec
; space allocation:
; 4,795 cons cells, 1,629,912 other bytes, 0 static bytes
7.1275467e-4
Using the Neighbor-Matrix
> (time (setf neighbor-matrix
(build-neighbor-matrix group 'knows 0)))
; cpu time (non-gc) 130 msec user, 170 msec system
; cpu time (gc) 30 msec user, 0 msec system
; cpu time (total) 160 msec user, 170 msec system
; real time 1,263 msec
; space allocation:
; 5,577 cons cells, 965,136 other bytes, 0 static bytes
#<neighbor-matrix 147 members @ #x11bbbe12>
> (time (group-degree-centrality group neighbor-matrix))
; cpu time (non-gc) 10 msec user, 0 msec system
; cpu time (gc) 0 msec user, 0 msec system
; cpu time (total) 10 msec user, 0 msec system
; real time 9 msec
; space allocation:
; 594 cons cells, 684,728 other bytes, 0 static bytes
7.1275467e-4
It's clear that the in-memory neighbor-matrix gives a tremendous speed boost (and is much more memory efficient). On the down side, it took some time to build so it would not make sense to use it unless you need to expand nodes many times. One area where this occurs is whenever an SNA algorithm relies on path-finding. For example, the actor-closeness-centrality algorithm requires finding the shortest path between an actor and every other member of the group. Lets compare:
> (time (actor-closeness-centrality
!<http://www.franz.com/ont/person-1> group 'knows))
; cpu time (non-gc) 1,750 msec user, 2,140 msec system
; cpu time (gc) 100 msec user, 10 msec system
; cpu time (total) 1,850 msec user, 2,150 msec system
; real time 20,200 msec
; space allocation:
; 84,703 cons cells, 13,531,840 other bytes, 0 static bytes
0.5214286
> (time (actor-closeness-centrality
!<http://www.franz.com/ont/person-1> group neighbor-matrix))
; cpu time (non-gc) 10 msec user, 0 msec system
; cpu time (gc) 0 msec user, 0 msec system
; cpu time (total) 10 msec user, 0 msec system
; real time 12 msec
; space allocation:
; 13,273 cons cells, 1,803,600 other bytes, 0 static bytes
0.5214286
As the groups get larger, path-finding algorithms do not scale well but this poor performance can be offset for a while using the neighbor-matrices.
Search
There are many ways to search in a graph and the one you choose will depend both on the application and on the kind of graph data you have collected. The SNA library provides multiple search functions whose operation is controlled by generators as defined above. Most operations come in several flavors. For example,
- breadth-first-search - returns whether or not you can get there from here.
- map-breadth-first-search-paths - applies a function to each possible path from here to there
- all-breadth-first-search-paths - collects and returns a list of all the paths from here to there.
We also provide an additional set of search functions specialized for bipartite graphs.
Breadth First Search
Search db
in breadth first fashion starting at start
and looking for end
, using generator
to expand the search space. Returns nil
if no path can be found (within depth) and the first such path found otherwise. The arguments are:
- start - a UPI or future-part or string that can be converted into a UPI.
- end - a UPI, future-part or string that can be converted into a UPI.
- generator - a function of one argument or a generator name. See the description of generators for additional details.
- maximum-depth - If supplied, this restricts the length of the paths searched. Only paths (from
start
) less than or equal to this will be checked. If maximum-depth is not specified, it defaults tonil
which means to search all paths. Warning in large graphs this can be very expensive.
start
and end
using breadth-first-search to find the path and generator
to determine when two nodes are adjacent. Returns nil
if no path exists.
fn
to each path between start
and end
using generator
to determine adjacent nodes and breadth-first-search to find paths.
Return a list of all (the shortest) paths between start
and end
using generator
to determine adjacent nodes and breadth-first-search to find paths.
all-breadth-first-search-paths
will search for a path no longer than maximum-depth
. If maxiumum-depth
is left unspecified, then the entire graph will be searched (obvisouly, this can be very expensive in large graphs). Note that once a path is found, no longer paths will be found (i.e., the maximum-depth
becomes the length of the first path found.) Since breadth-first search is guaranteed to find the shortest path between start
and end
, this function actually returns a list of the shortest paths.
Please contact [email protected] if your path finding needs are not met by this algorithm so that we can work to make our SNA module more flexible.
Depth First Search
Search db
in depth first fashion starting at start
and looking for end
, using generator
to expand the search space. Returns nil if no path can be found (within depth) and the first path found otherwise. The arguments are:
- start - a UPI, future-part or string that can be converted into a UPI.
- end - a UPI, future-part or string that can be converted into a UPI.
- generator - a function of one argument or a generator name. See the description of generators for additional details.
- maximum-depth - If supplied, this restricts the length of the paths searched. Only paths (from
start
) less than or equal to this will be checked. If maximum-depth is not specified, it defaults tonil
which means to search all paths. Warning in large graphs this can be very expensive.
start
and end
using depth-first-search to find the path and generator
to determine when two nodes are adjacent. Returns nil
if no path exists.
fn
to each path between start
and end
using generator
to determine adjacent nodes and depth-first-search to find paths.
Return a list of all paths between start
and end
using generator
to determine adjacent nodes and depth-first-search to find paths.
all-depth-first-search-paths
will search for a path no longer than maximum-depth
. If maxiumum-depth
is left unspecified, then the entire graph will be searched (obvisouly, this can be very expensive in large graphs). Note that once a node appears in a path, it will not appear in any longer paths (though it may appear in paths of the same or shorter length depending on the order in which nodes are discovered.
Please contact [email protected] if your path finding needs are not met by this algorithm so that we can work to make our SNA module more flexible.
Bidirectional Search
start
and end
(using generator
to determine when two nodes are adjacent.
start
and end
using bidirectional-search to find the path and generator
to determine when two nodes are adjacent. Returns nil
if no path exists.
fn
to each path between start
and end
using generator
to determine adjacent nodes and bidirectional-search to find paths.
Return a list of all (shorter) paths between start
and end
using generator
to determine adjacent nodes and bidirectional-search to find paths.
all-bidirectional-search-paths
will search for a path no longer than maximum-depth
. If maxiumum-depth
is left unspecified, then the entire graph will be searched. Note that once a path is found, no longer paths will be searched. (Though some longer paths may appear in the results after a shorter one because of the recursive algorithm employed.)
Please contact [email protected] if your path finding needs are not met by this algorithm so that we can work to make our SNA module more flexible.
Bipartite graphs
fn
to each path between start
and end
using generator-1
and generator-2
to determine adjacent nodes and breadth-first-search to find paths. The function assumes that generator-1
can be used on the start
node; the node type of the end
node does not matter.
fn
to each path between start
and end
using generator-1
and generator-2
to determine adjacent nodes and depth-first-search to find paths. The function assumes that generator-1
can be used on the start
node; the node type of the end
node does not matter.
fn
to each path between start
and end
using generator-1
and generator-2
to determine adjacent nodes and bidirectional-search to find paths.
Graphs Measures
There are many ways to measure information about a graph and its structure. Some of these focus on the graph as a whole while others target particular actors (vertices).
Who is nearby
nodal-neighbors
returns a list of other nodes that can be reached from node
by following an edge. Node
should be a vertex in the graph represented by the triple-store; See the description of generators for additional details.
Note that the nodal-degree of a node is the same as `(length (nodal-neighbors node)). See noda-degree for additional details.
The nodal-degree of node
is the total number of edges that connect it to other nodes in the graph. Edges are found using the generator
. See the description of generators for additional details.
Note that the interpretation of nodal-degree depends entirely on the generator being using in the calculation. Suppose, for example, that we have a graph with three nodes and two edges:
A --> B <-- C
and that these are encoded in AllegroGraph as
!ex:A !ex:linksTo !ex:B
!ex:C !ex:linksTo !ex:B
If we define three generators:
(defsna-generator linksTo (node)
(:objects-of :p !ex:linksTo))
(defsna-generator linksFrom (node)
(:subjects-of :p !ex:linksTo))
(defsna-generator links (node)
(:undirected :p !ex:linksTo))
then we will find that
> (nodal-degree !ex:B 'linksTo)
0
> (nodal-degree !ex:B 'linksFrom)
2
> (nodal-degree !ex:B 'links)
2
Finally, note that nodal-degree
is the same as the length of the list of nodes returned by nodal-neighbors.
The ego-group function returns a list of nodes in node
s ego group.
These are the other nodes in the graph (represented by the triple-store) that can be reached by following paths of at most length depth
starting at node
. The paths are determined using the generator
to select neighbors of each node in the ego-group. See the description of generators for additional details.
Centrality Measures
The centrality of an actor in a network is a measure of its prestige or importance or power. There are many ways to measure it and the best way varies with the application.
Actor
is a node in the graph; group
is a list of nodes (e.g., the actor's ego group) and generator is either a function or name. See the description of generators for additional details.
group-degree-centrality
measures group cohesion by finding the maximum actor centrality in the group, summing the difference between this and each other actor's degree centrality and then normalizing. It ranges from 0 (when all actors have equal degree) to 1 (when one actor is connected to every other and no other actors have connections.
An actor centrality measure provides insight into how central or important an actor is in the group. Closeness-centrality is the (normalized) inverse average path length of all the shortest paths between the actor and every other member of the group. (The inverse so that higher values indicate more central actors).
Actor
is a node in the graph; group
is a list of nodes (e.g., the actor's ego group) and generator is either a function or name. See the description of generators for additional details.
group-closeness-centrality
is measured by first finding the actor whose closeness-centrality
is maximized and then summing the difference between this maximum value and the actor-closeness-centrality of all other actors. This value is then normalized so that it ranges between 0 and 1.
An actor centrality measure provides insight into how central or important an actor is in the group. Betweenness-centrality measures how much control an actor has over communication in the group.
The actor-betweenness-centrality of actor i is computed by counting the number of shortest paths between all pairs of actors (not including i) that pass through actor i. The assumption being that this is the chance that actor i can control the interaction between j and k.
Actor
is a node in the graph; group
is a list of nodes (e.g., the actor's ego group) and generator is either a function or name. See the description of generators for additional details.
group-betweenness-centrality
is measured by first finding the actor whose betweenness-centrality
is maximized and then summing the difference between this maximum value and the actor-betweenness-centrality of all other actors. This value is then normalized so that it ranges between 0 and 1.
Page-rank centrality is a specific implementation of a more general eigenvector centrality measure. Given a set of nodes in a graph, the page-rank-centrality
function returns a vector representing the importance or influence of each node. Though it is not actually computed like this, you can imagine that we repeatedly pick a node at random and then execute a random walk following the edges of the graph while noticing which nodes our walker visits. The page-rank centrality is the probability that the walker will be on a particular node when it stops.
- group - a list of nodes in the triple-store
- generator - a generator describing how to get from one to another
- :dampening-factor - the effects how quickly the iterate algorithm stabilizes
Returns a vector of (unnormalized) page-ranks in the same order as the nodes in group
.
Cliques
In graph theory, a clique
is a fully connected subgraph in a larger graph. AllegroGraph supplies function to determine is a subgraph is a clique and to find all of the cliques in a graph.
subgraph
is linked to every other member. As usual, the generator
is used to determine whether or not a link exists between two nodes. See the description of generators for additional details.
node
is a member (using generator
to find adjacent nodes). Each clique returned will contain at least minimum-size
and no more than maximum-size
members. If `maximal-only is true, then only the largest cliques will be returned.
fn
to each clique in which node
is a member and whose size is at least minimum-size
and less than maximum-size. The
generator is used to find adjacent nodes. If
maximal-only` is true, then only maximal-cliques are mapped.
Prolog and Social Network Analysis
The functions described above have analogues in the Prolog world.
Graph Search
Unifies path with each path found from start
to end
using a breadth first search strategy.
start
- the node at which to startend
- the node at which to stopgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).max-depth
- the maximum depth to search.path
- bound to a list of UPIs representing a path fromstart
toend
. Each element in the path will be a UPI U such that there is a triple whose subject is U; whose object is the next element in the list; and which is returned by a call togenerator
. Iterates over paths betweenstart
andend
of all lengths. Warning Searching for all possible paths in a large triple-store can take a long amount of time.
Iterates over paths between start
and end
that are no longer than max-depth
.
Unifies path
with each path found from start
to end
using a depth first search strategy.
start
- the node at which to startend
- the node at which to stopgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).max-depth
- the maximum depth to search.path
- bound to a list of UPIs representing a path fromstart
toend
. Each element in the path will be a UPI U such that there is a triple whose subject is U; whose object is the next element in the list; and which is returned by a call togenerator
. Iterates over paths betweenstart
andend
of all lengths. Warning Searching for all possible paths in a large triple-store can take a long amount of time.
Iterates over paths between start
and end
that are no longer than max-depth
.
Unifies path
with each path found from start
to end
using a bidirectional search strategy (i.e., preceding from start
and end
simultaneously).
start
- the node at which to startend
- the node at which to stopgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).max-depth
- the maximum depth to search.path
- bound to a list of UPIs representing a path fromstart
toend
. Each element in the path will be a UPI U such that there is a triple whose subject is U; whose object is the next element in the list; and which is returned by a call togenerator
. Iterates over paths betweenstart
andend
of all lengths. Warning Searching for all possible paths in a large triple-store can take a long amount of time.
Iterates over paths between start
and end
that are no longer than max-depth
.
Graph Measures
Unifies degree
to be the nodal-degree of actor
in the current triple-store (i.e., the current value of *db*).
actor
- a node in the graphgenerator
- the name of the generator function used to compute adjacent nodes in the graph (see the section on generators for more details).
Unifies neighbor
to each vertex that has an edge pointing away from or towards actor
in the graph defined by generator
in the current triple-store (i.e., the current value of *db*).
actor
- a node in the graphgenerator
- the name of the function used to determine adjacent nodes. (See generators for more details).
The density of group
is the normalized average degree of the actors in the group. Roughly, this is a measure of how many of the possible connections between actors are actually realized.
group
- a list of nodes in the graph (these can be UPIs, future-parts, or strings that can be coerced into UPIs).generator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify group
to the list of UPIs representing the ego group of actor
in the graph.
actor
- a node in the graphdepth
- how many links to travel when fining the ego group.generator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
See ego-group-member to iterate over each member instead of collecting them all into a list.
If member
is supplied, then ego-group-member
succeeds if and only if member
is in the ego-group of actor
.
Unify member
with each of the other actors in actor
's ego-group.
actor
- a node in the graphdepth
- how many links to travel when fining the ego group.generator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
See ego-group to directly collect all of the members of an actor's ego-group.
Unify clique
with each of the graph cliques (i.e., completely connected sub-graphs) in graph in which actor
plays a member.
actor
- a node in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details). The arity three version ofclique
iterates over all cliques that have three or more members
The arity four version of clique
iterates over all cliques that have minimum-size
or more members
Succeeds if group
is a clique in graph (where edges between nodes are defined by generator
).
group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the actor-degree-centrality of actor
.
actor
- a UPI in the graph (or something that can be coerced into a UPI).group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the group-degree-centrality of group
.
group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the actor-closeness-centrality of actor
.
actor
- a UPI in the graph (or something that can be coerced into a UPI).group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the group-closeness-centrality of group
.
group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the actor-betweenness-centrality of actor
.
actor
- a UPI in the graph (or something that can be coerced into a UPI).group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Unify centrality
with the group-betweenness-centrality of group
.
group
- a list of items that can be coerced into UPIs in the graphgenerator
- a function that specifies how to find the neighbors of an actor in the graph (see generators for more details).
Geospatial Primitives
Introduction
AllegroGraph provides a novel mechanism for efficient storage and retrieval of data elements which are coordinates in a two-dimensional region. We often refer to this as "geospatial" although that term refers more specifically to positions on or around the earth's surface. AllegroGraph supports a more-general notion of two-dimensional coordinates, both on a flat plane such as the surface of a silicon chip, a sphere such as the earth's surface, or any other two-dimensional geometry system a user can define by writing some additional Lisp code. However, we will use the term geospatial to include any such data when there is no danger of ambiguity
AllegroGraph supports a :geospatial UPI type. The geospatial UPI type supports up to 256 subtypes, some predefined and others available for the application programmer to custom design. A geospatial UPI always encodes both an X and Y ordinate inside a single UPI in a way that allows efficient searching. The subtype specifies how external numeric data (e.g. degrees, radians, meters, or nanometers) is converted to and from the geospatial UPI internal representation.
In the 3.0 release geospatial UPIs are not supported for remote triple stores. Remote stores will be supported in the next release. For using geospatial UPIs from Java, see the several examples in the learning center.
Geospatial Subtypes
It is the job of a geospatial subtype to convert coordinates in some external representation to and from UPI representation. There are helper functions for defining certain important kinds of subtypes, for example, latitude and longitude on the earth's surface, and simple X:Y coordinates over a finite range of the infinite Cartesian plane.
The precision of each ordinate in the internal UPI representation is 32-bits. Dividing the circumference of the earth by 2^32 reveals that the resolution of a 32-bit integer longitude is slightly better than 1 cm.
Suppose we want to search a triple store for geospatial UPIs that are close to a certain XY, i.e., within a bounding box [X1,Y1,X2,Y2]. In a traditional RDF store (perhaps using :latitude and :longitude types) the X and Y would be in separate triples. If the two ordinates were combined a single part, it would still only be possible to search over a range of {X1,X2}, but within that range every Y value must be retrieved and range tested. As the size of the data increases, and therefore the total number of UPIs within the X range {X1,X2} increases, this scales badly.
A geospatial UPI does combine the two ordinates into a single value, but it adds a third component to the UPI. The Y dimension (or latitude) is decimated into strips of a fixed width, and UPIs are sorted first on the strip, then on the X, and finally on the actual Y value.
How does the Y strip help? In any of the AllegroGraph indexes, UPIs in any particular one of the SPOG are sorted as 12-byte unsigned integers. Within any index, all geospatial UPIs of a given subtype will sort together, first sorted on Y strip, then on the unsigned 32-bit integer X, then finally on the unsigned 32-bit integer Y. The Y strip is a decimation of the Y value. In other words, the Y values are divided into narrow strips. UPIs (within a given subtype) are sorted first on the strip, then the X, then the Y. If we expect searches to be concerned with regions (or radii) about R in size, and if the strip width is chosen to be within an order of magnitude of the search size, it helps the search tremendously.
Suppose we have a large number of GPS latitude and longitude information of cell phone locations, and that the data points have a resolution around 10 meters. Suppose we are interested in searching over a radius of 100 meters. If we store the latitude-longitude UPIs using a strip width of 100 meters, then to find all candidates within the bounding box [X-100,Y-100,X+100,Y+100] requires scanning short regions of two strips. Each candidate within those regions can be further filtered for exact distance. The proportion of entries that must be filtered out is 1-(pi/4)
.
Suppose our strips are larger, 500 meters. In that case our 100 meter radius search needs scan at most only two strips, and frequently only one, but the scan overall is somewhat less efficient because number of entries that must be filtered is greater. Even if the Y region lies completely within a single strip, the proportion of undesired entries that must be filtered is approximately 1-(pi/(4*5))
. If the Y region of interest spans two strips, the proportion of entries that must be examined and rejected by the filter is 10-(pi/(4*10))
.
If we err in the other direction and make the strips significantly smaller than the typical search radius, the proportion of entries that must be examined and filtered is not much affected, but the number of Y strips that must be scanned over the range [X1,X2] increases, causing more cursor creation and scans of disjoint sections of the index file. For example, if the strip width were 10 meters, the 100-meter radius query would have to examine 10 or 11 strips. This requires more cursor initialization and accessing multiple separate regions of the index.
In practice, even if the strip size for a particular geospatial subtype is as much as an order of magnitude away from the Y range used in a particular search, the strip approach is tremendously more efficient than direct X-Y search even for huge databases. If it is anticipated that data will be searched using widely different ranges at different times, then the data can be duplicated in the database using multiple subtypes with different strip sizes. For example, if we sometimes wanted to find cell phones records within a 100 meter radius of a location, and other times wanted to find calls within a 10 kilometer radius of a location, then it might make sense to record the data with multiple separate triples (or perhaps use both the object and graph UPIs of a single triple) with strip widths appropriate for each of the expected types of searches.
This points out the important limitation of the geospatial UPI strip concept. It requires that the program creating the data know in advance something about how the data will be used, i.e., the typical width of regions of interest. Fortunately, this estimate does not need to be exact. Even an order of magnitude error will not make the data unusable.
Defining and Managing Geospatial Subtypes
AllegroGraph cannot anticipate all of the geospatial subtypes that future applications might find necessary. An application must define the subtypes it wants to use, and there are some helper functions to assist for obvious popular requirements such as Earth-surface latitude/longitude with any desired strip width.
A geospatial subtype needs to define a number of functions to translate to and from the internal fields of the UPI and the external data. It is important to realize that an X-Y location most-intuitively consists of two separate numerical values. Other UPI types once way or another contain only a single value -- a string for resources and string literals, and a single number for the various numeric types, including time etc. This means that the familiar functions upi->value and value->upi may not immediately be applicable. Although the application program rarely needs be concerned with the strip component, it does need communicate back and forth the two values for X and Y.
One way to work around this would be to use Common Lisp's built in complex numbers. Another way is to use Common Lisp's multiple values. The advantage of a complex is that it is a single quantity that contains two numeric values, either integer or float. This is supported, but since manipulating complex number is a a little less efficient and computationally involved, it is more usual to employ conversion functions that deal with the two values as separate numbers.
(A geospatial subtype is associated with a unique UUID. In the future there will be a facility, not yet implemented, which will search for or otherwise reconstruct a subtype from a UUID. It will also be possible to use geospatial UPIs with federation, but currently geospatial UPIs are not supported in federated stores.)
An application can control all aspects of encoding and decoding x/y data to and from geospatial UPIs but this is rarely necessary and only so for exceptional kinds of models. Simple defining macros are provided for define geospatial subtypes for a region on a flat Cartesian plane and for the surface of a sphere (as for longitude/latitude).
xmin
..xmax
and Y range ymin
..ymax
and with the strip-width
specified.
latitude-strip-width-in-km
is specified in degrees.
latitude-strip-width-in-miles
. The range of latitudes and longitudes are given by these keyword arguments with these defaults: lat-min
-90.0, lat-max
+90.0, lon-min
-180.0, lon-max
+180.0.
latitude-strip-width-in-km
is specified in kilometers.
Execution of these macros returns an opaque geospatial subtype object that implements the subtype. It is typical to save it somewhere in order to use it later. See the defparameter in the example below.
The first defines a Cartesian subtype covering the specified region of the Cartesian plane. Units of the four arguments are at the discretion of the programmer and may be any type of real numbers.
The other four macros define a spherical subtype. A subtype can be defined to use either longitude/latitude in decimal degrees or radians. For longitude/latitude, the strip width may be given in miles (relative to the earth's average radius), kilometers, or degrees in latitude.
Before using a geospatial subtype it must be defined, usually by executing one of the above operators. Before storing a triple with a part with a geospatial subtype into a triple store, it is necessary to add that subtype to the set of subtypes known to that store. This is done with the add-geospatial-subtype-to-db function.
When opening a triple store containing one or more geospatial subtypes, geospatial subtypes it uses will be recreated in the running AllegroGraph program if they are not already registered in that image.
When working in spherical coordinates it is idiomatic to speak of "latitude and longitude" and to present the latitude before the longitude, as in "37.5N127.3W". Latitude, i.e. the North/South axis, corresponds intuitively to Cartesian Y, and longitude corresponds intuitively to Cartesian X. However, in Cartesian coordinates it is typical to present X before Y, as in "the point {3,-5}". Since Cartesian and spherical coordinates mostly share a common API, we will in AllegroGraph uniformly speak of longitude/latitude and present the longitude before the latitude. The only exception will be in parsing and printing ISO6709 latitude-longitude strings, where the standard defines latitude to appear before longitude.
Internally, the several varieties of latitude-striping subtypes all represent latitude and longitude ordinates as 32-bit unsigned integers. The ranges -90..+90
and -180..+180
are scaled so that any coordinate in ISO6709 format ±DDMMSS±DDDMMSS
will round-trip between internal and external string representations without change or loss of precision. Each second in latitude corresponds to 3300 units in the integer encoding, and each second in longitude corresponds to 6600 integer units, so fractional seconds that are exact submultiples will be reproducible. These rather strange numbers were chosen as being close to the maximum resolution possible within 32 bits, and having a large number of prime divisors:
3300: 2 2 3 5 5 11
6600: 2 2 2 3 5 5 11
The geospatial programming API generally converts all numeric ordinate values to floats, and returns them similarly. The need to scale ordinates to and from 32-bit unsigned integer quantities, as they are represented in a geospatial UPI, imposes rounding errors. This is even more evident in Cartesian subtypes, since Cartesian ranges are arbitrary, unlike sperical ordinates, so no simple prime divisor selection can be applied. Ordinate numbers that were encoded from pleasantly round decimal fractions, and even some integers, will when externalized show annoying lengthy decimal fractions. This is unpleasant, but the intended application of Allegrograph geospatial encoding is efficient and accurate calculation, not the exact preservation of textual presentation. It is more important that encoded geospatial data can be externalized and reloaded without loss of resolution or accuracy. If you need reliable preservation of RDF lexical form, you might want to store duplicate data as string literals. AllegroGraph obviously always preserves literals accurately.
*standard-output*
the (mod 256) subtype index UUIDs of each the geospatial subtype that has been registered in the running AllegroGraph image.
subtype
argument may be a geospatial-subtype object returned by one of the register functions, or the mod 256 index of the subtype in this executing AllegroGraph image. An error is signaled if the subtype is still in use (as in add-geospatial-subtype-to-db) by any open database.
Define a geospatial subtype. It returns two values: an opaque object representing the subtype and an mod 256 integer which is the subtype index within this running AllegroGraph image.
This function is usually called from higher-level geospatial subtype definers such as register-cartesian-striping and similar definers, and would only be called in applications that need to define custom geospatial subtypes not covered by those existing functions.
The additional arguments:
documentation - A documentation string.
base-uuid - uuid
2v-encoder - A function of arguments
(subtype x y &optional (upi (make-upi)))
which encodes the givenx
andy
as a UPI. If the optional UPI argument is used, that UPI is filled in. Otherwise a fresh UPI is allocated.2v-decoder - A function that takes a UPI of this geospatial subtype and returns two values, the X and the Y (or e.g. longitude and latitude) that the UPI encodes.
x->usb32 - A function that translates a real number into an monotonic (unsigned-byte 32) integer.
usb32->x - A function that does the reverse.
y->usb32 - Ditto for y.
usb32->y - Ditto for Y.
- usb32->strip - A function that takes a real number for Y and computed the (unsigned-byte 16) strip number in which that value belongs.
AllegroGraph takes care of the mapping between the subtype index in the local AllegroGraph and the subtype index in an open triple store. In general these will not be the same.
The next three functions are not normally needed by Allegrograph applications but are included for completeness and introspection.
db
. See add-geospatial-subtype-to-db. Some geospatial queries require the subtype as an argument, and since opening a database with geospatial data reconstructs any unregistered subtypes automatically, it may be more convenient when opening an existing store to obtain a subtype object this way rather than by reregistering it manually.
geospatial subtype
in argument db
which must be an open triple store. This information is not usually needed by application programs.
(mod 256)
index of this argument geospatial-subtype in the running AllegroGraph image. Not needed in normal programming.
Converting between Geospatial Data and UPIs
subtype-index
, strip
and x
and y
coordinates.
subtype
and x
and y
coordinates.
This creates using the given geospatial subtype a UPI with the given x and y coordinates.
x
and y
coordinates of a geospatial UPI as multiple values.
This returns x and y of a geospatial part as multiple values. See the example below.
Using Automatic Predicate and Type Mapping with Geospatial Data
These functions create type or predicate mappings for geospatial subtypes. subtype os a geospatial-subtype object. The predicate-part or datatype arguments are the same as could be passed to setf of datatype-mapping or predicate-mapping.
(setf predicate-mapping)
but is used for spherical geospatial subtypes. Automatic mapping needs to know the intended subtype for geospatial data predicates.
(setf predicate-mapping)
but is used for Cartesian geospatial subtypes. Automatic mapping needs to know the intended subtype for geospatial data predicates.
(setf datatype-mapping)
but is used for spherical geospatial subtypes. Automatic mapping needs to know the intended subtype for geospatial datatypes.
(setf datatype-mapping)
but is used for Cartesian geospatial subtypes. Automatic mapping needs to know the intended subtype for geospatial datatypes.
Retrieving Geospatial Triples
pred
and an object
UPI that is a geospatial UPI with the given subtype and within the specified Cartesian bounding box. If :use-g is true, the triple's graph
slot is searched instead of the object
. The units are implicit in the data.
subtype
is a geospatial-subtype object such as is returned by register-cartesian-striping. pred
is a UPI or future part specifying the predicate of triples to be matched. It must be supplied. x
and y
are the coordinates around which to search, and radius
is the search radius. The units of radius
are implicit in the subtype. All matching triples with an object of the specified geospatial subtype and within the search radius will be returned by the cursor. If the use-g
argument is specified and is true, the graph part of triples is searched instead of the object. The other arguments are as for get-triples.
There are Prolog analogs to the functions above. The triple argument is unified to successive triples that have predicate pred
and an object
within the bounding box or radius.
-triple
against each triple with predicate +pred
with an object of geospatial subtype +subtype
within the bounding box x-min
x-max
y-min
y-max
. The +subtype
is the object returned by register-cartesian-striping and similar functions.
-triple
against each triple with predicate +pred
with an object of geospatial subtype +subtype
within radius
distance of coordinate x
y
. The +subtype
is the object returned by register-cartesian-striping and similar functions.
The Haversine formula is used to compute the "Great Circle" distance on a sphere. See pred
and an object UPI that is a geospatial UPI with the given subtype and within the specified spherical radius. If :use-g
is true, the graph is searched instead of the object. This is the spherical analog to the bounding box functions above.
subtype
is a geospatial-subtype object such as is returned by register-latitude-striping-in-miles. pred
is a UPI or future part specifying the predicate of triples to be matched. It must be supplied. lon
and lat
are the coordinates around which to search, and radius-in-miles
is the search radius. All matching triples with an object of the specified geospatial subtype and within the search radius will be returned by the cursor. If the use-g
argument is specified and is true, the graph part of triples is searched instead of the object. The other arguments are as for get-triples.
radius-in-km
is given in kilometers.
radius-in-radians
is given in radians. This incompletely implemented and nonfunctional in release 3.0.
These functions have Prolog analogues: the triple argument is unified to successive triples that have predicate pred
and an object
within the spherical radius.
-triple
against each triple with predicate +pred
with an object of geospatial subtype +subtype
within +radius
miles of +longitude
and +latitude
. These last three arguments are typically floating-point numbers. The +subtype
is the object returned by register-latitude-striping-in-miles and similar functions.
+radius
is in kilometers.
Haversine Conversions
These compute the haversine distance between two spherical coordinates. The first returns a value in radians while the other two return an actual distance on the earth's surface in kilometers or miles.
lon1r
, lat1r
, lon2r
, and lat2r
, all in radians.
lon1
, lat1
, lon2
, and lat2
, all in degrees.
lon1
, lat1
, lon2
, and lat2
, all in degrees.
Polygon Support
There is a prototype facility for dealing with polygon regions. It can be used to determine if a pair of geospatial ordinates lies within a region defined by a polygon. The current interface is Lisp specific but will eventually also be provided by the Java client.
All computations on a polygon are performed on a Lisp data representation, a proper list of conses of X and Y ordinates which are the vertexes of the polygon. Successive vertexes define the edges with an implied edge between the last and first element. There is no requirement that a polygon be convex, or even non-self-intersecting. Polygons work with any geospatial subtype, including both Cartesian and spherical ordinates, although the predicates for the interior of a polygon compute in the Cartesian plane and do not account for spherical ordinates. This is a reasonable optimization for small regions of the sphere, except near the poles.
When a polygon must be stored in a triple store (e.g. the boundaries of a city) by convention it can be done with an ordered set of triples, one for each vertex. The Subject is any convenient identifier for the polygon, the Object is a geospatial UPI for the vertex, and the Graph is available for any other purpose. The Predicate is a nonnegative integer UPI of type +rdf-subscript+ which orders the vertexes. These can be extracted from the triple store by the polygon-vertexes function.
polygon-upi
.
The polygon-subject-upi is the subject identifying the desired polygon. This function returns a fresh list of the vertexes of the polygon. A polygon could have been stored in a triple store with code like the following:
(defparameter *cartesian-10*
(register-cartesian-striping -1000 1000 -1000 1000 10))
(add-geospatial-subtype-to-db *cartesian-10*)
(defparameter *my-pentagon*
'((234.56 . 347.31)
(243.07 . 348.40)
(247.85 . 357.02)
(230.68 . 349.52)
(231.37 . 348.62)))
(defparameter *penta*
(with-temp-upi (u)
(with-temp-upi (s)
(loop with id = (new-blank-node)
for vertex-number from 1
for (x . y) in *my-pentagon*
do (add-triple id
(value->upi vertex-number :subscript)
(geospatial->upi *cartesian-10* x y u))
finally (return id)))))
penta will be set to the new blank node that names this polygon. Its vertexes can now be retrieved given it's UPI as subject.
(polygon-vertexes *penta*) =>
((234.56006 . 347.31006) (243.07007 . 348.40002)
(247.84998 . 357.02002) (230.67993 . 349.52002)
(231.37 . 348.62))
polygon
is a list of vertexes such as is returned by polygon-vertexes. Returns true if the point [x,y] is inside the polygon. Boundary cases for vertexes of points on the edges are indeterminate.
This predicate returns true if the given point is inside the polygon. The polygon is a list of coordinates, as above. Points on an edge or vertex will return an indeterminate result since they are subject to float rounding.
(point-inside-polygon-p (polygon-vertexes *penta*) 235.5 350.0) => t
(point-inside-polygon-p *my-pentagon* 235.5 350.0) => t
(point-inside-polygon-p *my-pentagon* 235.5 356.0) => nil
See the polygon section in the Geospatial tutorial for more examples how polygons can be used.
inner
polygon is contained entirely within the outer
polygon. Boundary cases for points on vertexes or edges are indeterminate. The outer-convex-p
boolean may be passed, and if true allows a more-efficient algorithm to be used.
This function tests whether the inner polygon is entirely contained by the outer polygon. Again, results are indeterminate if any vertexes of the inner polygon fall on edges or vertexes of the outer polygon, or if any edges of the two polygons are collinear. The outer-convex-p boolean may be passed, and if true allows a more-efficient algorithm to be used.
predicate
and an object that is a geospatial UPI of subtype subtype
within the polygon. If use-g
is supplied and true, the graph is used instead. Boundary cases for vertexes of points on the edges are indeterminate. The other arguments are as for get-triples-geospatial-bounding-box
This function returns a cursor that return all triples with the specified predicate that have an Object that is a geospatial UPI of the specified subtype and which is within the given polygon. If :use-g is true, the graph is searched instead of the object.
-triple
to each triple with predicate +predicate
and an object part of geospatial subtype +subtype
within the polygon denoted by the list polygon
. Boundary cases on the vertexes and edges are not specified.
These are the Prolog analogs to get-triples-inside-polygon. They successively unify the -triple argument to each triple inside the given polygon.
Temporal Primitives
AllegroGraph's encoded UPIs support efficient storage and retrieval of temporal data including datetimes, time points, and time intervals:
- datetimes in ISO 8601 format: "2008-02-01T00:00:00-08:00"
- time points: !ex:point1, !ex:h-hour, !ex:when-the-meeting-began, etc
- time intervals: !ex:delay-interval (e.g., from point !ex:point1 to !ex:h-hour)
Note that AllegroGraph does not currently support datetimes with fractional seconds. This will be corrected in a future release.
Once data has been encoded, applications can perform queries involving a broad range of temporal constraints on data in the store, including:
- relations between points and datetimes
- relations between intervals and datetimes
- relations between two points
- relations between two intervals
- relations between points and intervals
The temporal reasoning tutorial describes all of these capabilities in detail and also functions as a reference guide.
Managing AllegroGraph
AllegroGraph provides several utilities to help you manage your triple-stores and AllegroGraph itself. Most of the management operations are carried out automatically but there may be occasions when you will want to take greater control.
The following functions let you set and get properties that control AllegroGraph, find the version you are using and operate on all of the triple-stores that you have open.
Begin logging AllegroGraph messages to pathname
. Return the pathname to which logging is directed.
A pathname
of t
will create a log named agerror.log
in the current user's home directory.
The category-specification
keyword argument controls which messages are logged. If left unspecified, it defaults to
(or fatal error warn)
which will log any messages that come from these categories. You should not need to alter this specification unless requested by AllegroGraph support.
See ag-disable-logging to stop the logging.
Returns the value of the property associated with name
. With no argument, prints all property names and values to standard output. Setfable.
> (setf (ag-property :default-print-triple-format) :ntriples)
:ntriples
> (ag-property :default-print-triple-format)
:ntriples
extended
argument is true, then it also returns the build date.
Search for an open triple-store named by designator
. Designator can be one of the following:
- An object of type triple-db
- A pathname which is the directory of a triple-store (cf. data-directory)
- A string which can be coerced into a pathname which is the directory of a triple-store
- A string which is the
name
of an open triple-store.
Note that it is possible that two or more triple-stores are open which have the same name
. In this case find-triple-store will signal an error of type ambiguous-triple-store-designator.
In addition to several special variables that can be dynamically bound to control its behavior dynamically, AllegroGraph has the following properties:
errorp
keyword argument to register-namespace. If true and errorp
is not supplied, then calling register-namespace with a namespace-prefix
that already has a namespace mapping will signal an error. Otherwise the namespace mapping will be changed silently.
The default value for the format
keyword argument to print-triple, print-triples, and part->string. May be one of these values:
:ntriples - Print appropriate for an N-Triples syntax file, including angle brackets and other punctuation, and escaping all characters outside the permitted set with \uxxxx escapes. The permitted characters are approximately the printable 7-bit ASCII. Triples written in this format are intended to be readable without loss of information, provided encoded UPIs have appropriate type or predicate mappings in effect.
:long - Exactly like :ntriples, except that no character \uxxxx escaping is performed. This is appropriate for printing to a stream that can support and display Unicode characters.
:concise - This format is intended for human-readable presentation. Characters are not escaped, language and type tags are suppressed from literals, and numeric encoded UPIs are printed numerically. If an appropriate namespace prefix is registered, it is used, otherwise URIs are printed fully.
:terse - Similar to :concise, except that only the fragment portion of a URI is printed, and long literal strings are truncated with "..." ellipses.
The default is :ntriples
.
sys:temporary-directory
.
verbose
in AllegroGraph functions that have a verbose keyword argument. Examples include load-ntriples, load-xml/rdf and index-all-triples.
prepare-reasoning
will output information messages as it runs inferences.
Finally, AllegroGraph periodically runs a variety of background checks to help optimize your triple-stores. These are controlled by the AllegroGraph agraph-manager. You can set how often AllegroGraph runs these checks using manager-period.
AllegroGraph-Manager
of the AllegroGraph application.
policy
to see what management operations need to be done and then do them.
Returns true if and only if the AllegroGraph manager process is paused.
If the manager is paused, then the background process that frees unused resources will not be executed.
resume-agraph-manager
).
pause-agraph-manager
).
manager
). The manager is started automatically when AllegroGraph opens a triple-store so Application programmers will not generally need to use this.
REPL Interface
In addition to the !
reader macro, AllegroGraph provides a handful of functions to make it easier to interact with the triple-store from the REPL.
Triples and parts are represented by (simple-array (unsigned-byte 8) 56) and (simple-array (unsigned-byte 8) 12) respectively. By default the Lisp printer prints these as vectors of bytes which is not very informative when using AllegroGraph interactively. This function modifies a pprint-dispatch table to print triples and parts interpretively if this can be done in the current environment. Specifically, the value of *db* must be an open triple store, and the vector being printed must print without error in the manner of print-triple or upi->value. If any of these conditions don't hold the vector is printed normally.
If the boolean argument is true, the informative printing is enabled, otherwise disabled. For example:
> (enable-print-decoded t)
t
> (upi !"Dürst"^^xsd:string)
{Dürst}
> (enable-print-decoded nil)
nil
> (upi !"Dürst"^^xsd:string)
#(48 61 125 164 117 231 137 163 64 100 17 2)
The :pprint-dispatch argument specifies the dispatch table to modify, by default the value of print-pprint-dispatch. Once enable-print-decoded has been turned on, you can also use the special-variable *print-decoded*
to enable fine-grained control of triple and UPI printing. See the AllegroGraph tutorial for more information on the various notations AllegoGraph uses.
Print a triple returned by cursor-next-row or get-triples-list.
Returns the triple printed.
The keyword argument :format
, which defaults to the value of (ag-property
:default-print-triple-format)
, specifies how the triple should be printed. The value :ntriples
specifies that it should be printed in N-Triples syntax. The value :long
indicates that the string value of the part should be used. And the value :concise
causes it to use a more concise, but possibly ambiguous, human-readable format.
triple-container
which can be either a triple store object, a list of triples such as is returned by get-triples-list, or a cursor such as is returned by get-triples. If the keyword argument :limit
is supplied, then at most that many triples will be displayed. The :format
keyword argument controls how the triples will be displayed, in either :ntriples
, :long
, or :concise
format. It defaults to (ag-property
:default-print-triple-format)
. The stream
argument can be used to send output to the stream of your choice. If left unspecified, then output will go to standard-output.
The default value for the format
keyword argument to print-triple, print-triples, and part->string. May be one of these values:
:ntriples - Print appropriate for an N-Triples syntax file, including angle brackets and other punctuation, and escaping all characters outside the permitted set with \uxxxx escapes. The permitted characters are approximately the printable 7-bit ASCII. Triples written in this format are intended to be readable without loss of information, provided encoded UPIs have appropriate type or predicate mappings in effect.
:long - Exactly like :ntriples, except that no character \uxxxx escaping is performed. This is appropriate for printing to a stream that can support and display Unicode characters.
:concise - This format is intended for human-readable presentation. Characters are not escaped, language and type tags are suppressed from literals, and numeric encoded UPIs are printed numerically. If an appropriate namespace prefix is registered, it is used, otherwise URIs are printed fully.
:terse - Similar to :concise, except that only the fragment portion of a URI is printed, and long literal strings are truncated with "..." ellipses.
The default is :ntriples
.
Print information about part
down to a maximum depth of maximum-depth
using the format format
. Triples for which part is a subject and their children
will be printed. See part->string and (ag-property
:default-print-triple-format)
for information about part printing. See pprint-object to display information based on subjects rather than objects.
Note that pprint-subject
is designed to show the actual triples in a store. It uses ground-triple-store to remove one layer of reasoning from db
.
Print information about part
down to a maximum depth of maximum-depth
using the format format
. Triples for which part is an object and their children
will be printed. See part->string and (ag-property
:default-print-triple-format)
for information about part printing. See pprint-subject to display information based on objects rather than subjects.
Note that pprint-object
is designed to show the actual triples in a store. It uses ground-triple-store to remove one layer of reasoning from db
.
From Parts and UPIs to Values
See upi->value and upi->values for additional information.
part
which can be either a UPI or a future-part.
part
in ;long syntax. Part can be either a UPI or a future-part.
part
in N-Triples syntax. Part can be either a UPI or a future-part.
part
(which can be a UPI or a future-part). The :format
keyword argument controls the format and can be one of :ntriples
, :long
, :concise
, or :terse
, as with the :format
argument to print-triple. The default is the value of (ag-property
:default-print-triple-format)
.
part
which can be either a UPI or a future-part.
part
. Part
can be UPI or a future-part.
Deprecated: use part->value instead.
Returns the value of the part
which can be UPI or a future-part.
Miscellaneous Utilities
UPI hash-tables
upi
in the upi-hash-table table
and whether or not the value was found. setf may be used with gethash/upi
to modify the value associated with a upi
or to add a new association to the hash-table.
table
.
fn
to each UPI/value association in the upi-hash-table table
. fn
should be a function of two arguments. It will be called with a UPI as the first argument and the value associated with the UPI as the second.
upi
and its value in the upi-hash-table table
.
Other
CVS/Ontology Management
Ontology management is often done by non-programmers. It's a little much to ask non-programmers to use one of the APIs for AllegroGraph just to get data into a database. For these users, we have created a tool for reading entire ontologies, a collection of triples, into a database. This tool assumes:
- A single ontology is represented by data in a single file.
- The ontology must have a unique name.
- CVS is used to store the files containing the ontologies.
- A CVS tagging mechanism is used to indicate which versions of an ontology the tool will use.
Since ontologies must have a unique name, it is recommended users of this tool maintain a consistent naming scheme. For example, the full module and path in the module of the file containing the ontology. For example: ontology_module/groupA/ontology123.owl
. Here ontology_module
is the CVS module name and groupA/ontology123.owl
is the file name of the ontology in the CVS module.
These tools work using tags made in CVS with the tag
command. Each version of the ontology to be added to the database is tagged. For example, in a working copy of the `ontology_module' module, you could execute this command:
$ cvs tag -F jason_beta groupA/ontology123.owl
jason_beta
is the name of the CVS tag and groupA/ontology123.owl
is the name of the file in the module. -F
means to forcibly move the tag to the current version, if the tag has been used before.
Now, we could use the update_ontology command, like so:
$ update_ontology ontology_name nasa.db jason_beta \
ontology_module/groupA/ontology123.owl
This would unload, or delete, all previous triples in nasa.db
that have the ontology name ontology_name
, and then load the triples from the file groupA/ontology123.owl
with the version given by jason_beta
in the CVS module ontology_module
.
Requirements
The CVSROOT environment variable must be set.
CVS must be installed. On Windows, Cygwin CVS is recommended. See www.cygwin.com for more information.
'rapper' must be installed to convert files in formats other than N-Triples format.
The
bin
directory in the AllegroGraph installation directory should be in your PATH, otherwise full path qualification will need to be done to execute the command line tools.
update_ontology command line arguments
$ update_ontology [-v] ontology_name database cvs_tag module_path
where
-v
allows for verbose operation, mostly for debuggingontology_name
is the name of the (e.g., ontology3)database
is the name of the database in which the triples are updatedcvs_tag
is the CVS tag (e.g., User1_beta) which specifies the the desired new version of the ontologiesmodule_path
is the name of the file in the CVS repository that contains the updated ontology. For example, if the module name isontology
and the file isontology3
, then the module_path would beontology/ontology3
.
The update_ontology command will retrieve from CVS the exact version of the ontologies specified by the tag User1_beta
and executes ths sync_ontology command:
$ sync_ontology ontology3 module:ontology3:User1_beta database
where
module:ontology3:User1_beta
is shorthand for: the fileontology3
in modulemodule
with version given byUser1_beta
sync_ontology command line arguments
update_ontology uses a lower-level command line tool, sync_ontology. The arguments to it are:
$ sync_ontology [--src format] ontology_name file ag_database
where
--src
is used to convert the file fromformat
to n-triples format. Currently,format
must be one of the format arguments accepted by rapper 1.4.15, which are: rdfxml, turtle, or rss-tag-soup. NOTE: a file extension of.owl
automatically implies aformat
ofrdfxml
.ontology_name
is the name of the ontology, and is used as the named graph for all triples added to the databasefile
contains the triples to be added to the databaseag_database
is the name of the database to which the triples are added
Other uses (mainly for testing):
$ sync_ontology -p [-n limit | -n none]
[-f { concise | long | ntriple } ]
database [ontology_name]
where
-p
signals "print mode", used to print a database-n limit
is use to set the :limit argument to get-triples-list, and a value ofnone' is the same as
nil'-f concise
or-f long
are used as the:format
argument toprint-triples
To delete triples:
$ sync_ontology -d database ontology_name
where -d
is used to delete triples for an ontology
To initialize a database:
$ sync_ontology -Z [-r expected-unique-resources] database
where
-Z
is used to initialize a database-r expected-unique-resources
is use to set the create-triple-store argument of the same name
Indices
All of the functions and variables in AllegroGraph's public interface are indexed below.
Function and Macro index
- actor-betweenness-centrality
- actor-closeness-centrality
- actor-degree-centrality
- add-geospatial-subtype-to-db
- add-index
- add-indexing-host
- add-indices
- add-standard-indices
- add-triple
- ag-disable-logging
- ag-enable-logging
- ag-property
- ag-property-names
- ag-server-db
- ag-server-trace
- agraph-application
- agraph-manager
- all-bidirectional-search-paths
- all-breadth-first-search-paths
- all-depth-first-search-paths
- allegrograph-version
- apply-rdfs++-reasoner
- average-index-fragment-count
- bidirectional-distance
- bidirectional-search
- blank-node-p
- breadth-first-distance
- breadth-first-search
- build-neighbor-matrix
- clear-namespaces
- clear-type-mappings
- cliquep
- cliques
- close-all-triple-stores
- close-triple-store
- collect-all-type-mappings
- collect-cursor
- collect-namespaces
- collect-open-triple-stores
- copy-triple
- copy-upi
- count-cursor
- count-query
- create-triple-store
- cursor-next
- cursor-next-p
- cursor-next-row
- cursor-row
- data-directory
- datatype-mapping
- db-apply-reasoner
- db-name
- db-room
- db-room-list
- default-graph-upi
- default-query-plan-option
- defined-query-plan-options
- defneighbor-matrix
- defsna-generator
- delete-triple
- delete-triple-store
- delete-triples
- deleted-triple-p
- depth-first-distance
- depth-first-search
- display-namespaces
- drop-geospatial-subtype
- drop-index
- drop-indices
- dump-namespaces
- ego-group
- enable-!-reader
- enable-lisp-in-client-select-queries
- enable-print-decoded
- encapsulate-triple-store
- encoded-types
- estimate-required-space
- estimated-count-query
- export-to-sesame
- federate-triple-stores
- find-cluster-code
- find-sna-generator
- find-task
- find-triple-store
- freetext-get-ids
- freetext-get-triples
- freetext-get-triples-list
- freetext-get-unique-subjects
- freetext-index-needs-updating-p
- freetext-predicate-p
- freetext-registered-predicates
- future-part-extra
- future-part-type
- future-part-value
- future-part=
- geo-parts->upi
- geospatial->upi
- geospatial-subtype-index-in-db
- geospatial-subtype-index-in-this-image
- geospatial-subtypes-in-db
- get-triple
- get-triple-by-id
- get-triples
- get-triples-geospatial-bounding-box
- get-triples-geospatial-radius
- get-triples-haversine-km
- get-triples-haversine-miles
- get-triples-haversine-radians
- get-triples-inside-polygon
- get-triples-list
- get-variable-list
- gethash/upi
- graph
- graph-density
- graph-part=
- graph-upi=
- ground-triple-store
- group-betweenness-centrality
- group-closeness-centrality
- group-degree-centrality
- has-value-reasoning-enabled
- hash-table-count/upi
- hashed-upi-p
- haversine-km
- haversine-miles
- haversine-r
- index-all-triples
- index-coverage-percent
- index-fragment-count
- index-new-triples
- index-status-report
- indexing-needed-p
- indexing-status
- inferred-triple-p
- inner-triple-store
- inner=triple=store
- intern-literal
- intern-resource
- intern-typed-literal
- iterate-cursor
- literal
- load-nquads
- load-nquads-from-string
- load-ntriples
- load-ntriples-from-string
- load-properties
- load-rdf-manifest
- load-rdf/xml
- load-rdf/xml-from-string
- load-trix
- load-trix-from-string
- longitude-latitude->upi
- lookup-namespace
- machines
- make-future-part
- make-graph-filtered-store
- make-sesame-server
- make-triple
- make-tutorial-store
- make-upi
- make-upi-hash-table
- manage-agraph
- manage-triple-store
- manager-paused-p
- manager-period
- map-all-type-mappings
- map-bidirectional-search-paths
- map-bidirectional-search-paths-bipartite
- map-breadth-first-search-paths
- map-breadth-first-search-paths-bipartite
- map-cliques
- map-cursor
- map-depth-first-search-paths
- map-depth-first-search-paths-bipartite
- map-namespaces
- map-open-triple-stores
- maphash/upi
- merge-new-triples
- new-blank-node
- nodal-degree
- nodal-neighbors
- object
- object-part=
- object-upi=
- open-triple-store
- page-rank-centrality
- parse-sparql
- part->concise
- part->long
- part->ntriples
- part->string
- part->terse
- part->value
- part-value
- part=
- pause-agraph-manager
- point-inside-polygon-p
- polygon-inside-polygon-p
- polygon-vertexes
- pprint-object
- pprint-subject
- predicate
- predicate-mapping
- predicate-part=
- predicate-upi=
- prepare-reasoning
- print-triple
- print-triples
- print-type-mappings
- reasoner
- register-cartesian-striping
- register-freetext-predicate
- register-geospatial-subtype
- register-latitude-striping-in-degrees
- register-latitude-striping-in-km
- register-latitude-striping-in-miles
- register-latitude-striping-in-radians
- register-namespace
- register-neighbor-matrix
- register-sna-generator
- register-standard-namespaces
- remhash/upi
- remove-all-machines
- remove-machine
- report-loaded-geospatial-subtypes
- reset-properties
- resource
- resume-agraph-manager
- run-sparql
- run-sparql-ask
- run-sparql-construct
- run-sparql-describe
- run-sparql-select
- save-properties
- select
- select-distinct
- select-distinct/callback
- select/callback
- select0
- select0-distinct
- select0-distinct/callback
- select0/callback
- serialize-ntriples
- serialize-rdf-manifest
- serialize-rdf-n3
- serialize-rdf/xml
- serialize-trix
- sesame-server-port
- set-cartesian-datatype-mapping
- set-cartesian-predicate-mapping
- set-spherical-datatype-mapping
- set-spherical-predicate-mapping
- spogi-cache-enabled-p
- spogi-cache-size
- start-ag-server
- start-agraph-manager
- start-all-remote-clients
- start-remote-clients
- start-sesame-server
- stop-ag-server
- stop-agraph-manager
- stop-sesame-server
- string+
- subject
- subject-part=
- subject-upi=
- supported-types
- sync-triple-store
- text-index-minimum-word-size
- text-index-parameters
- text-index-stop-words
- triple-contents=
- triple-count
- triple-exists-p
- triple-id
- triple-store-exists-p
- triple-store-id
- triple-store-indices
- triple=
- type-code->type-name
- type-name->type-code
- undelete-triple
- undelete-triples
- unindexed-triple-count-threshold
- unmerged-chunk-count-threshold
- unschedule-indexing
- update-freetext-index
- upi
- upi->geospatial
- upi->longitude-latitude
- upi->value
- upi->values
- upi-map-directory
- upi-type-code
- upi-typep
- upi<
- upi=
- upip
- value->upi
- with-blank-nodes
- with-temp-triple
- with-temp-upi
- with-triple-store
Functor index
- actor-betweenness-centrality
- actor-closeness-centrality
- actor-degree-centrality
- bidirectional-search-paths
- breadth-first-search-paths
- clique
- cliquep
- depth-first-search-paths
- ego-group
- ego-group-member
- graph
- graph-density
- group-betweenness-centrality
- group-closeness-centrality
- group-degree-centrality
- nodal-degree
- nodal-neighbors
- object
- part=
- predicate
- q
- q-
- qd
- qs
- subject
- triple-id
- triple-inside-bounding-box
- triple-inside-bounding-box-g
- triple-inside-haversine-km
- triple-inside-haversine-km-g
- triple-inside-haversine-miles
- triple-inside-haversine-miles-g
- triple-inside-haversine-radians
- triple-inside-haversine-radians-g
- triple-inside-polygon
- triple-inside-polygon-g
- triple-inside-radius
- triple-inside-radius-g
- upi=
Variable index
- *agj-idle-life*
- *agj-indexing*
- *agj-timeout*
- *agraph-version*
- *db*
- *default-expected-unique-resources*
- *default-spogi-cache-enabled*
- *default-spogi-cache-size*
- *expand-type-clause-with-map-p*
- *get-triples-list-limit*
- *index-chunk-count-warning-limit*
- *last-query-plan*
- *maximum-indexing-sort-chunk-size*
- *print-decoded*
- *print-triples-list-limit*
- *standard-namespaces*
- *synchronize-automatically*
- *use-maps-for-subproperties-s-o-p*
- *use-reasoner*
-
For information on the N-Triples format, see both the W3C description and the information in the RDF test cases. Additionally the file w3c-ntriples-tests.nt in the
sample-inputs
directory of the AllegroGraph distribution contains a set of test cases and provides a good overview of what can be represented. ↩ - Details of the RDF/XML syntax can be found in the RDF/XML-primer and related documentation. ↩
- Language tags are defined in RFC-3066 ↩
-
The function
do-cursor
has been removed from AllegroGraph as of version 3.0. Please use the function map-cursor and the macro iterate-cursor instead. ↩ - The Prolog q- functor provides an interface to range queries for only the object and graph slots of a triple. ↩
- It is possible to use range queries with UPIs of type :short-literal since these are stored directly in the UPI and not in the string dictionary. The only caveat is that you must make sure that all of your data really does fit into a short literal UPI. This is equivalent to saying that all of your strings must be less than or equal to 10 bytes in length after they have been UTF-8 encoded. ↩
- To be precise, AllegroGraph uses the :standard-indices property to determine which indices newly created triple-stores should have. The default value for this property is to use all possible indices. ↩
- The Oracle and Sesame connections will be implemented during the second and third quarters of 2008. ↩
- AllegroGraph only provides support for simultaneously loading of a large N-Triples files because other formats cannot be split into separately managed chunks. ↩
-
Remember that
select
is a macro and that using it in the REPL will produce interpreted code. This means that selects run in the REPL will be significantly slower than those that you write inside of compiled functions. (Note also that both the HTTP and the Java interfaces to AllegroGraph ensure that any select calls get compiled before they run). Whether compiled queries execute significantly faster depends on whether the generated code performs a lot of backtracking or other repeated computation. ↩ -
In this case, there are fewer ub:publicationAuthor triples than rdf:type ones so the
type
clause provides no help at all. If the type clause was more restrictive, then the planner will keep the type clause and move it first. ↩ - See the upi-map-directory function for information on where UPI maps are kept. ↩