Warning: This document is for an old version of RDFox.

14. Programmatic Access to RDFox

Programmatic control of RDFox can be gained remotely via a RESTful API exposed through an HTTP endpoint or in-memory via Java.

This section describes the functionality provided in both APIs for managing the different information elements of the system. This section should be understood as a reference for the JAVA and REST APIs in RDFox, and it requires understanding of the structure of RDFox as described in Section 4.

14.1. Basics of the Java API

The Java API provides access to RDFox via connections to a server and/or its data stores. A connection encapsulates the identity of the object being connected to, as well as the credentials of the user making the connection. The following example demonstrates a typical life cycle of a connection.

String serverURL = ...;
String roleName = ...;
String password = ...;
ServerConnection sConn = ConnectionFactory.newServerConnection(serverURL, roleName, password);
// Use the server connection...
String dataStoreName = ...;
DataStoreConnection dsConn = sConn.newDataStoreConnection(dataStoreName);
// Use the data store connection...
dsConn.close();
sConn.close();

Both server and data store connections must be closed after use in order to release system resources. There are no requirements that a server connection must be closed after a data store connection — that is, both connections are independent.

For convenience, one can connect to a data store directly.

String serverURL = ...;
String dataStoreName = ...;
String roleName = ...;
String password = ...;
DataStoreConnection dsConn = ConnectionFactory.newDataStoreConnection(serverURL, dataStoreName, roleName, password);
// Use the data store connection...
dsConn.close();

All connections are single-threaded — that is, they can safely be used only from one thread at a time. Using the same connection from multiple threads results in undefined behavior and can lead to a system crash (although the server itself will not be corrupted provided that the containing process survives the crash). To use RDFox concurrently, one should use a distinct connection per execution thread.

RDFox provides various APIs for adding and deleting facts and rules. All updates are performed within the context of a transaction, which ensures that either all changes are performed as a unit, or no changes are performed at all. The transaction API is described in more detail in Section 14.9.

Adding or deleting facts or rules might require adjusting the inferred facts. In most cases, RDFox achieves this by using highly optimized incremental reasoning algorithms, whose aim is to update the derived facts while minimizing the amount of work. This process is automatically initiated before a query is evaluated in a transaction; thus, each query evaluated in a transaction always sees the results of prior updates made on the transaction. To promote performance, incremental reasoning is initiated only when a query is issued or a transaction is committed; thus, if several updates are issued before a transaction is committed, incremental reasoning is run only once.

It is generally good practice to add all rules before the facts, or to add rules and facts in an arbitrary order but grouped in a single transaction. This will usually increase the performance of the first reasoning operation.

14.2. Basics of the RESTful API

The RESTful API is available whenever the RDFox Endpoint is listening. Please refer to Section 13 for details of how to configure, start and stop the endpoint.

The endpoint provides access to one RDFox server via the following API keys.

/                                   : management of the server (GET/PATCH)
    /connections                    : management of server connections (GET/POST)
        /<SRVCONN>                  : management of a server conection (GET/PATCH/DELETE)
    /datastores                     : listing available data stores (GET)
        /<DSTRNAME>                 : management of a data store (GET/PATCH/POST/DELETE)
            /connections            : management of data store connections (GET/POST)
                /<DSCONN>           : management of a data store conection (GET/PATCH/DELETE)
                    /cursors        : management of transaction cursors (GET/POST)
                        /<CURSID>   : management of a cursor (GET/POST/DELETE)
                    /transaction    : management of the connection transaction (GET/POST)
            /content                : data store content (GET/PATCH/PUT/POST/DELETE)
            /datasources            : listing available data sources (GET)
                /<DSRCNAME>         : management of a data source (GET/POST/DELETE)
                    /tables         : listing available data source tables (GET)
                        /<DTNAME>   : information about a data source table (GET)
                            /data   : sampling facts of a data source table (GET)
            /dictionary             : the data store dictionary (GET)
            /sparql                 : data store SPARQL endpoint (GET/POST)
            /stats                  : listing the available statistics (GET/PUT)
                /<STNAME>           : management of the statistics (GET/PUT/POST/DELETE)
            /tupletables            : listing available tuple tables (GET)
                /<TTNAME>           : management of a tuple table (GET/POST/DELETE)
    /health                         : checking that the endpoint is healthy (GET)
    /password                       : changing the password of the authenticated role (PUT)
    /roles                          : listing roles (GET)
        /<ROLENAME>                 : management of a role (POST/DELETE)
            /privileges             : management of a role's privileges (GET/PATCH)
            /memberships            : management of a role's memberships (GET/PATCH)
            /members                : listing a role's members (GET)

14.2.1. Authentication

The RESTful API supports basic HTTP authentication. For example, to supply role name Aladdin with password OpenSesame, one should include the following header into the request:

Authorization: Basic QWxhZGRpbjpPcGVuU2VzYW1l

Since RESTful API is stateless, this header should be included with each call — that is, the role name and password are not kept between calls.

When no Authorization header is present in a RESTful API call, the call is processed with the role name guest and password guest. To prevent anonymous access via the RESTful API, the guest role can be deleted.

RDFox also supports a proprietary RDFox authentication scheme intended for use with explicit connection management. This feature is described in Section 14.2.5.

14.2.2. Key-Value Pairs as Arguments

Several API calls take a set of key-value pairs as arguments. In the RESTful API, these can be encoded into the query string, or into the request body using the application/x-www-form-urlencoded content type for PATCH/POST/PUT requests. If a request requires both a message body and request parameters, then the request parameters must be part of the query string.

14.2.3. Treating GET Results as Answers to SPARQL Queries

Many RESTful API calls return information about various parts of the data store. For example, one can list all data stores in a server, all data sources in a data store, and so on. In order to avoid introducing additional formats, the output of all such requests are formatted as answers to certain SPARQL queries. (This does not mean that such a query can be evaluated through a SPARQL endpoint; rather, it only means that the same result format is reused to represent query results.)

Answers of such queries can be serialised using any of the supported query answer formats (see Section 14.3.2) apart from application/sparql-results+resourceid.

Content negotiation determines the format to be used, as usual in the SPARQL 1.1 protocol. The examples in this document use the CSV format for simplicity. All such calls accept an optional parameter with name filter, whose value must be a SPARQL 1.1 FILTER expression. If a filter expression is specified, it is evaluated for each answer in the list, and only those answers on which the expression returns true are returned.

14.2.4. RESTful Connections and Transactions

Just like in the Java API, each RESTful API request is also evaluated within a context of a server or a data store connection. The RESTful endpoint provides two ways of associating a connection with each request.

  • If no connection management headers are present in the HTTP request, each request will be evaluated in the context of a fresh connection. This provides users with a convenient way of using the RESTful API without any complication with connection management, which is arguably not natural in a connectionless protocol such as HTTP.

  • By including a connection HTTP request parameter, users can specify that the request should be evaluated within a specific connection. In such a case, a connection can be understood as a session: creating a connection requires checking the caller’s credentials, and subsequent requests on this connection are performed with the credentials associated with the connection. Moreover, connections can be used to support user-controlled transactions. Finally, the RESTful API provides calls for managing server and data store connections.

Most RESTful API calls are evaluated inside a read-only or a read/write transaction, which is started implicitly whenever the underlying connection is not already associated with a transaction. Depending on the workload, starting a transaction may take a long period of time. In order to prevent API calls from being blocked indefinitely, the RESTful API will cancel a request and report an error if the transaction cannot be acquired within a predetermined time period (which is currently hard-coded to two seconds).

14.2.5. Explicit Connection Management

The /connections key can be used to manage server connections, and the /datastores/<DSTRNAME>/connections key is used to manage connections to data store <DSTRNAME>. Both provide exactly the same API, so all examples in the rest of this section are presented for the latter connection type. All examples assume that a data store called myStore has been created in the server.

The following request creates a connection to data store called myStore. The connection is identified by a identifier, which is returned in the Location response header. The newly created connection is associated with the role specified in the request; that is, if provided, the Authorization header specifies the role name and password, and otherwise the guest role is used. The response will also contain a RDFox-Authentication-Token header, which will contain another random value that be used for authentication on the connection as described below; since this value is used for authentication, measures should be taken to keep it secret.

Request

POST /datastores/myStore/connections HTTP/1.1
Host: localhost

Response

HTTP/1.1 201 Created
RDFox-Authentication-Token: 11111222223333344444
Location: /datastores/myStore/connections/DSC01234567890123456789

Any RESTful API request that requires a data store connection can now be performed on a specific connection by including the connection ID as the value of the connection request parameter. For example, the following request will import the data into the data store using the connection created above.

Request

POST /datastores/myStore/content?connection=DSC01234567890123456789 HTTP/1.1
Host: localhost

[The facts/rules to be added in a format supported by RDFox]

Response

HTTP/1.1 200 OK

[Response body as usual]

All such requests are performed with the role associated with the connection. RDFox provides two ways of making sure that such requests are indeed issued by the appropriate user.

  • One can use basic authentication to supply a role name and password. For the request to succeed, the role name must match the name of the role logged into the connection, and the password must be valid for the role at the time the request is serviced.

  • Alternatively, one can use RDFox authentication scheme by including the header Authorization: RDFox <token>, where <token> is the authentication token returned when the connection was created. For example, the above request can be issued as follows:

Request

POST /datastores/myStore/content?connection=DSC01234567890123456789 HTTP/1.1
Host: localhost
Authorization: RDFox 11111222223333344444

[The facts/rules to be added in a format supported by RDFox]

Created connections can be managed using the /datastores/<DSTRNAME>/connections/<DSCONN> key. A GET request on the connection provides information about the connection. The response is written as the output of a SPARQL query that binds the variable ?Property to the property name, variable ?Value to the property value, and variable ?Mutable to true if the value of the property can be changed and to false otherwise. At present, role-name is the only property associated with the connection, and its value reflects the name of the role associated with the connection.

Request

GET /datastores/myStore/connections/DSC01234567890123456789 HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value,Mutable
role-name,guest,false

A connection can be deleted using a DELETE request.

Request

DELETE /datastores/myStore/connections/DSC01234567890123456789 HTTP/1.1
Host: localhost
Authorization: RDFox 11111222223333344444

Response

HTTP/1.1 204 No Content

A PATCH request can be used to check the password of the role associated with the connection, to interrupt another request currently running on the connection, or to duplicate the connection. The type of request is specified in the operation request parameter. When checking the role password, the request body specifies the password of the new role. The remaining connection operations accept no parameters and the request body must be empty.

Request

PATCH /datastores/myStore/connections/DSC01234567890123456789?operation=check-password HTTP/1.1
Host: localhost

Password

Response

HTTP/1.1 204 No Content

Request

PATCH /datastores/myStore/connections/DSC01234567890123456789?operation=interrupt HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Request

PATCH /datastores/myStore/connections/DSC01234567890123456789?operation=duplicate HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content
Location: //datastores/myStore/connections/DSC98765432109876543210

Finally, GET on /datastores/myStore/connections lists the connections to data store myStore. The response is written as the output of a SPARQL query that binds the variable ?Name to the connection identifier.

Request

GET /datastores/myStore/connections HTTP/1.1
Host: localhost

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

?Name
DSC01234567890123456789
DSC98765432109876543210

Server connections are managed in exactly the same way.

14.2.5.1. Connections and Concurrency

Access to connections in the RESTful API is serialised: if two requests attempts to access the same connection, one of request will fail in order to safeguard the integrity of the RDFox server. To use RDFox concurrently from multiple requests, one should use distinct connections. Without explicit connection management, this is automatically achieved by creating a temporary connection to service each request.

14.2.5.2. Connection Expiry

Since the RESTful API is connectionless, there is no way to associate a data store or server connection with a physical network connection to the server. In order to avoid situations where a connection is created but never deleted, the RESTful API will delete a connection if it has not been used (i.e., no HTTP request accessed it) for a period longer than the value of the object-expiry-time endpoint parameter. That is, a connection will remain valid for at least that much time (but it may actually remain valid slightly longer).

14.3. Formats and MIME Types

Various API calls either require input or produce output in one of the several formats, each of which is identified by a MIME type. Each format falls in one of the following two groups.

14.3.1. Formats Encoding Data Store Content

The first group contains formats that encode the content of a data store, such as Triples and/or rules. These formats can be used in API calls that update the data store, or that return data store content. In the RESTful API, these calls are available using the /content API keys. Specifically, the following formats are supported. These are also listed when typing help into the shell.

  • The N-Triples format has MIME type application/n-triples.

  • The Turtle format has MIME type text/turtle.

  • The N-Quads format has MIME type application/n-quads.

  • The TriG format has MIME type application/trig.

  • The OWL 2 Functional-Style Syntax format has the MIME type text/owl-functional.

  • RDFox supports proprietary formats application/x.gen-n-triples, text/x.gen-turtle, application/x.gen-n-quads, and application/x.gen-trig which extend the corresponding standard formats by support for generalised triples and quads (i.e., triples/quads where any component can be an IRI, a blank node, or a literal).

  • RDFox uses a proprietary format described in Section 6.4 to capture datalog rules and facts. The MIME type of this format is application/x.datalog.

14.3.2. Formats Encoding SPARQL Query Results

The second group contains formats that encode results of SPARQL queries. Data in these formats is produced by API calls on the /sparql keys, as well as GET API calls that retrieve various information (see Section 14.2.3).

  • The SPARQL 1.1 TSV Format has MIME type text/tab-separated-values.

  • The SPARQL 1.1 CSV Format has MIME type text/csv.

  • The SPARQL 1.1 XML Format has MIME type application/sparql-results+xml.

  • The SPARQL 1.1 JSON Format has MIME type application/sparql-results+json.

  • The proprietary format with MIME type application/x.sparql-results+turtle outputs each query answer in a single line that resembles Turtle. If the query has exactly three answer variables, then query answers in this format can be passed to API calls that expect Turtle data.

  • Proprietary formats with MIME types text/x.tab-separated-values-abbrev, text/x.csv-abbrev, application/x.sparql-results+xml-abbrev, application/x.sparql-results+json-abbrev, and application/x.sparql-results+turtle-abbrev follow the same structure as the formats mentioned above, with the difference that all IRIs are abbreviated using prefixes supplied in the query. Hence, these formats provide a more user-friendly representation of query results.

  • The proprietary format with MIME type application/x.sparql-results+resourceid is a simple binary format designed to speed up RDFox usage in client-server scenarios. The output of a query is serialised as follows. First, a 64-bit dictionary generation counter is output. Next, the number of answer variables is output as a 64-bit value. Next, the name of each variable in UTF-8 is output: first, a 64-bit length of the name encoded in UTF-8 is output, followed by the UTF-8 encoding of the variable name (without a zero terminator. Next, for each query answer, a nonzero 64-bit answer multiplicity (i.e., an integer specifying how many times should a particular row appears in the answer) is output, followed by a 64-bit value is output for each answer variable (where a value of zero means that the answer variable is unbound, and a nonzero value identifies a resource that can be resolved to a value using the dictionary). Finally, after all answers have been output, a single 64-bit zero multiplicity is output, thus signaling the end of the answer set. By caching dictionary values on the client, one can considerably reduce network communication overheads; however, the client should clear the cache when the dictionary generation counter changes. This format is not available in GET calls that retrieve various lists (see Section 14.2.3).

  • The proprietary format with MIME type application/x.sparql-results+null simply discards all answers. This can be useful in situations such as query benchmarking, where one may want to measure the speed of query processing without taking into account often considerable overhead of serializing query results and transporting them over the network.

  • Each format from Section 14.3.1 for triples/quads can be used as a query answer format for queries that return variables ?S, ?P, ?O, and optionally ?G. In such a case, each query answer is serialised as one triple/quad (where an answer is interpreted as a quad whenever variable ?G is bound).

14.4. Managing Servers

This section describes the API calls responsible for managing an RDFox server.

14.4.1. Retrieving Server Properties

The following request retrieves standard properties of a server. The response is written as the output of a SPARQL query that binds the variable ?Property to the property name, variable ?Value to the property value, and variable ?Mutable to true if the value of the property can be changed and to false otherwise. The names of all properties specified at the time the server was created are prefixed with parameters. so that they can be identified in the output.

Request

GET / HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value,Mutable
num-threads,8,true
parameters.max-memory,100000000,false

The Java API provides various getter functions on ServerConnection to retrieve the properties of a server.

Java API

int numThreads = sConn.getNumberOfThreads();
// ...

14.4.2. Setting Server Properties

The following request updates the server properties using the values specified in the request. Only properties names returned in a GET call from the previous section are supported, and only mutable properties can be changed.

Request

PATCH /?num-threads=5 HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

The Java API provides various setter functions on ServerConnection to set the properties of a server.

Java API

int numberOfThreads = ...;
sConn.setNumberOfThreads(numberOfThreads);

14.5. Managing Data Stores

This section describes the API calls responsible for managing data stores of an RDFox server.

14.5.1. Listing Available Data Stores

The following request retrieves the list of data stores available at a server. The response is written as an output of a SPARQL query that binds variable ?Name to the names of the available data stores.

Request

GET /datastores HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name
myStore
yourStore
theirStore

Java API

List<DataSourceInfo> dataStoreInfos = sConn.listDataStores();

14.5.2. Creating a Data Store

The following request creates a new data store. The data store name is specified as part of the request URL, and key-value pairs can be supplied as request parameters to determine various data store options. The type parameter must be provided, and it specifies the type of the new data store. The location of the new store is returned in the Location header.

Request

POST /datastores/myStore?type=par-complex-nn&key1=val1&key2=val2 HTTP/1.1
Host: localhost

Response

HTTP/1.1 201 CREATED
Location: /datastores/myStore

Java API

Map<String, String> parameters = new HashMap<String, String>();
parameters.put("key1", "val1");
parameters.put("key2", "val2");
sConn.createDataStore("myStore", "par-complex-nn", parameters);

14.5.3. Deleting a Data Store

The following request deletes a data store.

Request

DELETE /datastores/myStore HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

sConn.deleteDataStore("myStore");

Deleting a data store invalidates all connections to it — that is, any request made on the connection will result in an error. However, all connections to the deleted data store must still be explicitly closed in order to release all system resources.

14.5.4. Retrieving Data Store Properties

The following request retrieves standard properties of the data store. The response is written as an output of a SPARQL query that binds the variable ?Property to the property name, variable ?Value to the property value, and variable ?Mutable to true if the value of the property can be changed and to false otherwise. The exact properties and their values are dependent on the type of the data store. The names of all properties specified at the time the data store was created are prefixed with parameters. so that they can be identified in the output.

Request

GET /datastores/myStore HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value,Mutable
name,TestDataStore,false
unique-id,01234567890
type,par-complex-nn,false
parameters.by-levels,true,false
parameters.equality,off,false
parameters.use-DRed,false,false
concurrent,true,false
equality-axiomatization,off,false
generation-counter,0,false
requires-incremental-reasoning,false,false

The Java API provides various getter functions on DataStoreConnection to retrieve the basic properties of a data store.

Java API

String type = dsConn.getType();
String uniqueID = dsConn.getUniqueID();
// ...

14.5.5. Manage Data Store Content

The PATCH request can be used to alter the content of a data store or how the data store is persisted. The query parameter operation should be set to one of the operation values given in the table below.

Operation

Description

clear

Removes all facts, axioms and rules from the data store. Equivalent to the shell command clear

clear-rules-explicate-facts

Clears all rules and makes all facts explicit. Equivalent to the shell command clear rules-explicate-facts.

clear-facts-keep-rules

Clears all facts but keeps all rules currently loaded into the data store. Equivalent to the shell command clear facts-keep-rules.

compact

Compacts all facts in the data store, reclaiming the space used by the deleted facts in the process and persistent storage. Equivalent to the shell command compact.

recompile-rules

Recompiles the rules in the current data store according to the current statistics. Equivalent to the shell command recompilerules.

recompute-materialization

Performs a full, from-scratch materialization within the data store. Equivalent to the shell command remat.

update-materialization

Explicitly updates the set of materialized facts in the data store. Unlike recompute-materialization, this option will use incremental reasoning unless it is the first time reasoning has run within the data store. Since materialization is updated automatically when a transaction is committed, this command should be used only inside transactions. Equivalent to the shell command mat.

Request

PATCH /datastores/myStore?operation=clear-rules-explicate-facts HTTP/1.1
Host: localhost
Accept: */*

Response

HTTP/1.1 204 No Content

Java API

dsConn.clearRulesExplicateFacts();

14.5.6. Retrieving and Modifying Data Store Content

The content of a data store can be modified using the /content key. All modification is transactional — that is, a transaction is started before the call and it is committed (if modification is successful) or rolled back (if there is an error) before the call returns. All reasoning (if any is needed) is performed before the transaction is committed. The /content key implements the SPARQL 1.1 Graph Store HTTP Protocol. However, since this protocol does not support incremental deletion, the /content key also supports a proprietary extension for incremental updates. All of these functions are applied to a data store as a whole — that is, the default and graph=uri request parameters of SPARQL 1.1 Graph Store HTTP Protocol are ignored. A subset of the data store (e.g., just one named graph) can be retrieved using CONSTRUCT queries, and arbitrary updates can be implemented using DELETE/INSERT queries. The /content key also implements a proprietary protocol extension, which can be used to receive errors and/or warnings while the content is being parsed, as well as summary information about the size of the import.

The formats that RDFox supports for encoding triples and/or rules are described in Section 14.3 and are identified using MIME types. In RESTful API calls that retrieve data store content, the format determines which part of the content is being retrieved or updated. For example, a request to output data store content using the Turtle format (MIME type text/turtle) retrieves all triples from the default graph, whereas a request to output the content using the datalog format (MIME type application/x.datalog) retrieves all rules and no triples. As another example, an incremental addition request that uses the Turtle format will update the triples in the default graph.

RDFox can usually detect the format of input data, so the Content-Type specification in update requests can generally be omitted. However, if the Content-Type header is present, it must match the type of the content or the update is rejected.

14.5.6.1. Retrieving Data Store Content

The following request retrieves the content of the data store. The media type specified using the Accept header determines which subset of the store is retrieved. Depending on the format, different request parameters can be specified to customize the data returned.

When retrieving facts in the application/n-triples, text/turtle, application/n-quads, or application/trig formats, the only supported parameter is fact-domain, and its value is the fact domain (9.2) that determines which facts are exported. The default fact domain is EDB.

When retrieving rules in the application/x.datalog format, the only supported parameter is rule-domain and its value is the rule domain (4.6) that determines which rules are exported. The default rule domain is user.

Request

GET /datastores/myStore/content?fact-domain=IDB HTTP/1.1
Host: localhost
Accept: text/turtle; charset=UTF-8

Response

HTTP/1.1 200 OK

[The content of the store formatted according to the Turtle 1.1 standard]

Java API

OutputStream output = ...;
Map<String, String> parameters = ...;
dsConn.exportData(prefixes, output, "text/turtle", parameters);

14.5.6.2. Incrementally Adding Data Store Content

The PATCH request can be used to incrementally add content to a data store. The query parameter operation should be set to add-content. The type of content added is determined in one of the following two ways:

  • if the Content-Type header is absent, then the type of content is inferred automatically from the supplied content; and

  • if the Content-Type header is present, then the supplied content must be of that type, or the request is rejected.

Query parameter default-graph-name can be used to specify the name of the default graph. That is, if this parameter is specified, then triples that would normally be imported into the default graph will instead be imported into the graph with the specified name.

RDFox will provide information about this operation as follows.

  • If the Accept header identifies a SPARQL answer format, then the response body is structured as an answer to a SPARQL query with variables ?Type, ?Line, ?Column, ?Description, and ?Value. For each error or warning, an answer is emitted where the value of ?Type identifies the notification type (e.g., "error" or "warning", but other notification types are possible too), the values of ?Line and ?Column may identify the place in the input where the error was detected, and the value of ?Description describes the error or warning. Moreover, the following answers will summarize information about the importation:

    • For each prefix definition encountered during importation, one answer will be emitted where the value of ?Type is "prefix", the value of ?Description is the prefix name (which ends with :), and the value of ?Value is the prefix URI. This allows the client to retrieve the prefixes from the submitted input.

    • An answer with ?Type equal to "information", ?Description equal to "#aborted", and ?Value a Boolean value specifies whether the import was aborted prematurely.

    • Answers with ?Type equal to "information", ?Description equal to "#errors" and "#warnings", and ?Value integers specify the number of errors and warnings, respetively, encountered during import.

    • Aanswers with ?Type equal to "information", ?Description equal to "#processed-facts" and "#changed-facts", and ?Value integers specify the number of facts processed in the input and facts actually added to or deleted from the data store, respectively.

    • Aanswers with ?Type equal to "information", ?Description equal to "#processed-rules" and "#changed-rules", and ?Value integers specify the number of rules processed in the input and rules actually added to or deleted from the data store, respectively.

    • Aanswers with ?Type equal to "information", ?Description equal to "#processed-axioms" and "#changed-axioms", and ?Value integers specify the number of axioms processed in the input and axioms actually added to or deleted from the data store, respectively.

  • If the Accept header is either absent or has value text/plain, then the Content-Type header of the response is then set to text/plain, and the response body contains a human-readable description of the same information as in the previous case.

RDFox also uses a proprietary header Notify-Immediately to determine how to return information about the operation to the client, which also determines the status codes used.

  • If the request does not include the Notify-Immediately header, then the entire request is processed before the response is returned to the client. The response will indicate success or failure by using one of the following status codes (which are compatible with the SPARQL 1.1 Graph Store HTTP Protocol):

    • 400 Bad Request indicates that at least one error has been encountered,

    • 204 No Content indicates that no additional information is provided so the response body is empty, and

    • 200 OK indicates that no errors have been encountered, but the response body contains additional information (which can be information about warnings, or summary information in the extended format).

  • If the request includes the Notify-Immediately: true header, then notifications about errors and warnings are sent to the client as soon as they are available, possibly even before the client has finished sending the request body, thus allowing the client to take appropriate action early on. For example, a client may decide to stop sending the rest of the request body after receiving an error. This option increases the flexibility of the RESTful API, but at the expense of added complexity.

    • The client must keep reading the notifications while it is still sending the request body. In particular, the notification produced and sent eagerly by RDFox can fill the TCP/IP buffers on the sender and receiver side, in which case RDFox will wait for client to read the notifications and thus free the buffers. But then, if the client is not reading the notifications, a deadlock will occur where the client is waiting for RDFox to process the request content, and RDFox is waiting for the client to read the notifications.

    • If a warning is generated before an error, RDFox must start producing the response without knowing whether the entire operation will succeed (i.e., errors can be generated later during the process). In such situations, RDFox uses the 202 Accepted status code in the response to indicate that the status of the operation is not yet know. In such situations, the operation succeeds if and only if the response body contains no errors.

The following is an example of a successful request that follows the SPARQL 1.1 Graph Store HTTP Protocol.

Request

PATCH /datastores/myStore/content?operation=add-content HTTP/1.1
Host: localhost

[The facts/rules to be added in a format supported by RDFox]

Response

HTTP/1.1 200 OK

prefix: pref: = http://www.test.com/test#
information: #aborted = false
information: #errors = 0
information: #warnings = 0
information: #processed-facts = 9
information: #changed-facts = 8
information: #processed-rules = 0
information: #changed-rules = 0
information: #processed-axioms = 0
information: #changed-axioms = 0

The following is an example of an unsuccessful request where errors are returned in text format.

Request

PATCH /datastores/myStore/content?operation=add-content HTTP/1.1
Host: localhost

a b c .

Response

HTTP/1.1 400 Bad Request
Content-Type: text/plain; charset=UTF-8
Transfer-Encoding: chunked

XX
error: line 1: column 3: Resource expected.
information: #aborted = false
information: #errors = 1
information: #warnings = 0
information: #processed-facts = 0
information: #changed-facts = 0
information: #processed-rules = 0
information: #changed-rules = 0
information: #processed-axioms = 0
information: #changed-axioms = 0

0

The following is an example of a request where errors are returned in a SPARQL answer format.

Request

PATCH /datastores/myStore/content?operation=add-content HTTP/1.1
Content-Type: text/csv

@prefix pref: <http://www.test.com/test#> .
pref:a pref:b pref:c .
a b c .

Response

HTTP/1.1 400 Bad Request
Content-Type: text/csv; charset=UTF-8
Transfer-Encoding: chunked

XX
Type,Line,Column,Description,Value
error,3,3,Resource expected.,
prefix,,,pref:,http://www.test.com/test#
information,,,#aborted,false
information,,,#errors,1
information,,,#warnings,0
information,,,#processed-facts,1
information,,,#changed-facts,1
information,,,#processed-rules,0
information,,,#changed-rules,0
information,,,#processed-axioms,0
information,,,#changed-axioms,0

0

In the Java API, notifications are received by passing an instance implementing the ImportNotificationMonitor interface.

Java API

InputStream input = ...;
ImportNotificationMonitor importNotificationMonitor = ...;
ImportResult result = dsConn.importData(UpdateType.ADD, prefixes, input, "", importNotificationMonitor);

14.5.6.3. Incrementally Deleting Data Store Content

The following request incrementally deletes content from a data store. The request and response formats follow the same structure as in the case of incremental addition however the operation query parameter should be set to delete-content. Query parameter default-graph-name can be used to specify the name of the default graph in the same way as in incremental addition.

Request

PATCH /datastores/myStore/content?operation=delete-content HTTP/1.1
Host: localhost

[The facts/rules to be deleted in a format supported by RDFox]

Response

HTTP/1.1 204 No Content

Java API

InputStream input = ...;
ImportNotificationMonitor importNotificationMonitor = ...;
ImportResult result = dsConn.importData(UpdateType.DELETE, prefixes, input, importNotificationMonitor);

14.5.6.4. Deleting All Data Store Content

The following request clears all data store content — that is, it removes all triples (in the default graph and all named graphs), all facts in all tuple tables, and all rules.

Request

DELETE /datastores/myStore/content HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

dsConn.clear();

14.5.6.5. Replacing All Data Store Content

The following request clears all data store content — that is, it removes all triples (in the default graph and all named graphs), all facts in all tuple tables, and all rules — and then adds the specified content to the data store. The request and response formats follow the same structure as in the case of incremental addition. Query parameter default-graph-name can be used to specify the name of the default graph in the same way as in incremental addition.

Request

PUT /datastores/myStore/content HTTP/1.1
Host: localhost

[The facts/rules in a format supported by RDFox]

Response

HTTP/1.1 204 No Content

The Java API does not have a separate ‘replace content’ primitive.

14.5.6.6. Adding/Deleting OWL Axioms From Triples

As explained in Section 6.6, RDFox can be instructed to analyse the triples of one named graph, parse them into a set of OWL axioms, and add these axioms to another named graph. An analogous operation can be used to remove the axioms from a named graph. The named graph being analysed and the named graph to which the axioms are added may, but need not be the same.

In the RESTful API, the operation is invoked using the PATCH verb. The source and destination graphs are specified using the source-graph-name and destination-graph-name query parameters, respectively. If either of the two parameters can be omitted, the default graph is used as a default. The operation query parameter can be set to add-axioms or delete-axioms. Finally, the assertions query parameter can be set to true, in which case ABox assertions are extracted as well, or to false, in which case only the TBox (i.e., schema) axioms are extracted. For example, the following request imports the axioms from triple in named graph called SG and stores the axioms into the named graph called DG.

Request

PATCH /datastores/myStore/content?operation=add-axioms&source-graph-name=SG&destination-graph-name=DG HTTP/1.1
Host: localhost

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8
Transfer-Encoding: chunked

XX
information,,,#processed-axioms,2
information,,,#changed-axioms,2

0

Java API

dsConn.importAxiomsFromTriples("SG", false, "DG", UpdateType.ADDITION);

14.5.7. In-Depth Diagnostic Information

RDFox can report extensive diagnostic information about its internal components, which is often useful during performance tuning and debugging. Please note that this call is intended for diagnostic purposes only. The information provided is determined by RDFox internals and is likely to change in future versions of RDFox. Thus, applications should not rely on this information being stable.

Diagnostic information can be retrieved at the level of the server (by querying the / key) or for a specific data store (by querying the appropriate subkey of /datastores). In either case, the component-info request parameter can be specified with values short or extended to determine whether a shortened or an extended report should be returned. The result is organized in a tree of hierarchical components. The component at the root of this tree represents a data store, and it contains a number of subcomponents that represent various parts of the data store. For example, there is a subcomponent representing the data store dictionary, a subcomponent for each tuple table, a subcomponent for each registered data source, and so on. The structure of the component tree is determined by the data store type. The state of each component in the tree is described using a list of property/value pairs, where values can be strings or numeric values.

To output this complex data structure, the RESTful API converts the component tree into a list as follows. Each component in the tree is assigned an integer component ID using depth-first traversal (with root being assigned ID one). Then, the tree is serialised as a result of a query containing three variables. In each result to the query, variable ?ComponentID contains the ID of the component, variable ?Property contains the name of the property describing the component with the ID stored in ?ComponentID, and variable ?Value represents the property value. For each component, the result contains a row with ?Property="Component name" and where ?Value contains the name of the component. Finally, for each component other than the root, the result contains a row with ?Property="Parent component ID" and where ?Value contains the ID of the parent component.

Request

GET /datastores/myStore?component-info=extended HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

ComponentID,Property,Value
1,Component name,RDFStore
1,Name,TestDataStore
1,Unique ID,0123456789
1,Type,par-complex-nn
1,Concurrent,yes
... etc ...
2,Component name,Parameters
2,Parent component ID,1
2,by-levels,true
2,equality,off
2,use-DRed,false
... etc ...
3,Component name,Dictionary
3,Parent component ID,1
3,Resource mapping size,704
3,Aggregate size,12586653
... etc ...

In the above example, diagnostic information is requested for data store myStore. The root result is component with ID 1 that represents the data store. Properties such as Name, Unique ID, and so on provide information about the data store. Component with ID 2 is a subcomponent of the data store. It provides information about the parameters that the data store was created with, such as by-levels and equality. Analogously, subcomponent with ID 3 of the data store provides information the data store dictionary such as Resource mapping and Aggregate size.

Java API

ComponentInfo componentInfo = sConn.getComponentInfo(true);
... or ...
ComponentInfo componentInfo = dsConn.getComponentInfo(true);

14.5.8. Managing Statistics

Like most databases, RDFox needs in its operation various statistics about the data it contains. These are mainly used for query planning: when determining how to efficiently evaluate a query, RDFox consults information gathered from the data in a data store in order to estimate which query evaluation plan is more likely to be efficient. These statistics can be managed explicitly through the core and REST APIs. Configuring the available statistics is largely of interest for system administrator. Moreover, after large updates (e.g., after a large amount of data is added to the system), it is advisable to update the statistics — that is, to request RDFox to recompute all summaries from the data currently available in the system.

14.5.8.1. Listing the Available Statistics

The following request retrieves the list of statistics currently available in a data store. The response is written as an output of a SPARQL query that binds variable ?Name to the name of the statistics, and variable ?Parameters to a string describing the data source parameters (with all key-value pairs concatenated as in a query string).

Request

GET /datastores/myStore/stats HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name,Parameters
column-counts,
[...]

Java API

List<StatisticsInfo> statisticsInfos = dsConn.listStatistics();

14.5.8.2. Creating Statistics

The following request creates new statistics. One can supply to the request a number of key-value pairs that govern how the statistics are generated. The location of the new statistics is returned in the Location header.

Request

POST /datastores/myStore/stats/column-counts HTTP/1.1
Host: localhost

Response

HTTP/1.1 201 CREATED
Location: /datastores/myStore/stats/column-counts

Java API

Map<String, String> parameters = new HashMap<String, String>();
dsConn.createStatistics("column-counts", parameters);

14.5.8.3. Deleting Statistics

The following request deletes the statistics with the given name.

Request

DELETE /datastores/myStore/stats/column-counts HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

dsConn.deleteStatistics("column-counts");

14.5.8.4. Retrieving Information About Statistics

The following request retrieves information about statistics. The response is written as an output of a SPARQL query that binds variables ?Property and ?Value. The exact properties and values are determined by the statistics.

Request

GET /datastores/myStore/stats/column-counts HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value
name,column-counts

The statisticsInfo class encapsulates information about the statistics in the Java API. Instances of this class are immutable.

Java API

StatisticsInfo statisticsInfo = dsConn.describestatistics("column-counts");

14.5.9. Updating Statistics

The following request updates all statistics currently present in the data store.

Request

PUT /datastores/myStore/stats HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

StatisticsInfo statisticsInfo = dsConn.updateStatistics();

The following request updates only the statistics with the given name.

Request

PUT /datastores/myStore/stats/column-counts HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

StatisticsInfo statisticsInfo = dsConn.updateStatistics("column-counts");

14.5.10. Accessing the Dictionary

The main purpose of a data store dictionary is to resolve resources (i.e., IRIs, strings, integers, dates, and so on) into integer resource IDs, which are then used internally to store facts. These IDs are immutable as long as a data store is not reinitialized. Although many users never need to use the dictionary directly, exposing the dictionary allows for more efficient communication. In particular, in the proprietary format SPARQL answer format with MIME type application/sparql-results+resourceid, each query answer is written out as a sequence of 64-bit resource IDs, each corresponding to a resource in the dictionary. By caching resource IDs between calls, an application can considerably reduce the communication overheads.

Resource IDs can be resolved in the RESTful API by submitting a GET request to the /dictionary key of a data store. The IDs to be resolved are submitted as a comma-separated list in the id or ids request parameter (i.e., the two parameters are synonyms). The result of dictionary lookup is written as an output of a SPARQL query that binds variable ?ResourceID to the resource ID, ?LexicalForm to the lexical form of the resource, and variable ?DatatypeID to an ID representing the datatype. The order of the resources in the response matches the order of resource in the ids parameter. Moreover, if a particular resource ID is not in the dictionary, then the resource ID occurs in the answer with ?LexicalForm and ?DatatypeID unbound. Finally, datatypes are encoded as IDs as shown in the following table (note that datatype ID with value zero stands for a special datatype whose only value represents the unbound value):

DatatypeID

Datatype

0

Unbound value

1

Blank node

2

IRI reference

3

http://www.w3.org/2000/01/rdf-schema#Literal

4

http://www.w3.org/2001/XMLSchema#anyURI

5

http://www.w3.org/2001/XMLSchema#string

6

http://www.w3.org/1999/02/22-rdf-syntax-ns#PlainLiteral

7

http://www.w3.org/2001/XMLSchema#boolean

8

http://www.w3.org/2001/XMLSchema#dateTime

9

http://www.w3.org/2001/XMLSchema#dateTimeStamp

10

http://www.w3.org/2001/XMLSchema#time

11

http://www.w3.org/2001/XMLSchema#date

12

http://www.w3.org/2001/XMLSchema#gYearMonth

13

http://www.w3.org/2001/XMLSchema#gYear

14

http://www.w3.org/2001/XMLSchema#gMonthDay

15

http://www.w3.org/2001/XMLSchema#gDay

16

http://www.w3.org/2001/XMLSchema#gMonth

17

http://www.w3.org/2001/XMLSchema#duration

18

http://www.w3.org/2001/XMLSchema#yearMonthDuration

19

http://www.w3.org/2001/XMLSchema#dayTimeDuration

20

http://www.w3.org/2001/XMLSchema#double

21

http://www.w3.org/2001/XMLSchema#float

22

http://www.w3.org/2001/XMLSchema#decimal

23

http://www.w3.org/2001/XMLSchema#integer

24

http://www.w3.org/2001/XMLSchema#nonNegativeInteger

25

http://www.w3.org/2001/XMLSchema#nonPositiveInteger

26

http://www.w3.org/2001/XMLSchema#negativeInteger

27

http://www.w3.org/2001/XMLSchema#positiveInteger

28

http://www.w3.org/2001/XMLSchema#long

29

http://www.w3.org/2001/XMLSchema#int

30

http://www.w3.org/2001/XMLSchema#short

31

http://www.w3.org/2001/XMLSchema#byte

32

http://www.w3.org/2001/XMLSchema#unsignedLong

33

http://www.w3.org/2001/XMLSchema#unsignedInt

34

http://www.w3.org/2001/XMLSchema#unsignedShort

35

http://www.w3.org/2001/XMLSchema#usignedByte

Request

GET /datastores/myStore/dictionary?ids=3,9,6,5000 HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK

ResourceID,LexicalForm,DatatypeID
3,Peter,2
9,42,5
6,Stewie,3
5000,,

Java API

long[] resourceIDs = new long[] { 3, 6, 9, 5000 }
GroundTerm[] groundTerms = new GroundTerm[4];
dsConn.getGroundTerms(resourceIDs, groundTerms);

14.6. Managing Data Sources

RDFox can access external data stored in different kinds of data sources. Currently, a data source can be a CSV/TSV file, a PostgreSQL database, ODBC database, or an Apache Solr index. For an overview of how RDFox manages data sources, see Section 10.

All modification functions described in this sections are not transactional: they are applied immediately, and in fact their invocation fails if the connection has an active transaction. Consequently, there is no way to rollback the effects of these functions.

14.6.1. Listing the Registered Data Sources

The following request retrieves the list of data sources registered with a data store. The response is written as an output of a SPARQL query that binds variable ?Name to the name of the data source, variable ?Type to the data source type, variable ?Parameters to a string describing the data source parameters (with all key-value pairs concatenated as in a query string), and variable ?NumberOfTables to the number of tables in the data source.

Request

GET /datastores/myStore/datasources HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name,Type,Parameters,NumberOfTables
F1,PostgreSQL,connection-string=postgresql://user:pw@localhost:5432/DB,2
DBpedia,DelimitedFile,"file=/table.csv&delimiter=,",1
[...]

Java API

List<DataSourceInfo> dataSourceInfos = dsConn.listDataSources();

14.6.2. Registering a Data Source

The following request registers a new data source. The data source name is encoded in the URI, and it also accepts request parameters that include the data source type and a number of key-value pairs determining the data source options.

Request

POST /datastores/myStore/datasources/mySource?type=PostgreSQL&key1=val1&key2=val2 HTTP/1.1
Host: localhost

Response

HTTP/1.1 201 CREATED
Location: /datastores/myStore/datasources/mySource

Java API

Map<String, String> parameters = new HashMap<String, String>();
parameters.put("key1", "val1");
parameters.put("key2", "val2");
dsConn.registerDataSource("mySource", "PostgreSQL", parameters);

14.6.3. Deregistering a Data Source

The following request deregisters a data source. The request succeeds if no tuple tables are mounted on the data source. Thus, to delete a data source, one must first delete all rules mentioning any tuple tables of the data source, and then delete all tuple tables mounted from the data source.

Request

DELETE /datastores/myStore/datasources/mySource HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

dsConn.deregisterDataSource("mySource");

14.6.4. Retrieving Information About a Data Source

The following request retrieves information about a data source. The response is written as an output of a SPARQL query that binds variables ?Property and ?Value. What exact properties and values are supported depends on the data source. The names of all parameters specified at the time the tuple table was created are prefixed with parameters.

Request

GET /datastores/myStore/datasources/mySource HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value
name,mySource
type,PostgreSQL
tables,3
... etc ...

The DataSourceInfo class encapsulates information about a data source in the Java API. Instances of this class are immutable.

Java API

DataSourceInfo dataSourceInfo = dsConn.describeDataSource("mySource");

14.6.5. Listing the Data Source Tables of a Data Source

The following request retrieves the list of data source tables of a data source. The response is written as an output of a SPARQL query that binds variable ?Name to the name of a data source table, variable ?NumberOfColumns to the number of columns in the table, and variable ?Columns to a percent-encoded string describing the table columns using the form name1=dt1&name2=dt2&... where namei is the column name, and dti is the column datatype.

Request

GET /datastores/myStore/datasources/mySource/tables HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name,NumberOfColumns,Columns
drivers,2,id=integer&name=string
constructors,3,key=integer&name=string&address=string

Java API

List<DataSourceTableInfo> dataSourceTableInfos = dsConn.listDataSourceTables("mySource");

14.6.6. Retrieving Information About a Data Source Table

The following request retrieves information about a data source table. The response is written as an output of a SPARQL query that binds variable ?Column to the integer referencing a column of a data source, variable ?Name to the column name, and variable ?Datatype to the name of the RDFox datatype that best corresponds to the datatype of the the column in the data source.

Request

GET /datastores/myStore/datasources/mySource/tables/drivers HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Column,Name,Datatype
1,id,http://www.w3.org/2001/XMLSchema#name
2,first_name,http://www.w3.org/2001/XMLSchema#string
3,last_name,http://www.w3.org/2001/XMLSchema#string
... etc ...

The DataSourceTableInfo class encapsulates information about a data source table in the Java API. Instances of this class are immutable.

Java API

DataSourceTableInfo dataSourceTableInfo = dsConn.describeDataSourceTable("mySource", "drivers");

14.6.7. Sampling a Data Source Table

The following request retrieves a sample of data from a data source table. The response is written as an output of a SPARQL query that binds the variable corresponding to column names to the values in the columns. The limit=n request parameter would determine how many rows are to be returned. RDFox supports a configurable, system-wide maximum limit on the number of returned rows, which can be used to avoid accidentally requesting large portions of a data source. The main purpose of this API is not to provide access to the data, but only provide a sample of the data so that clients can see roughly what the source contains and then mount the corresponding tuple table.

Request

GET /datastores/myStore/datasources/mySource/tables/drivers/data?limit=20 HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

id,first_name,last_name
1,Ayrton,Senna
2,Michael,Schumacher
... etc ...

Data from data source tables is returned using cursors in the Java API. These cursors are always full — that is, all relevant data is retrieved before the call finishes. The result is unaffected by the transaction that may be associated with the connection: RDFox does not support transactions over data sources.

Java API

Cursor data = dsConn.getDataSourceTableData("mySource", "drivers", 20);

14.7. Managing Tuple Tables

Both types of tuple tables are managed using the same API, which is described in this section. All modification functions described in this sections are not transactional: they are applied immediately, and in fact their invocation fails if the connection has an active transaction. Consequently, there is no way to rollback the effects of these functions.

14.7.1. Listing the Available Tuple Tables

The following request retrieves the list of tuple tables currently available in a data store. The response is written as an output of a SPARQL query that binds variable ?Name to the name of the tuple table, variable ?ID to a unique integer ID of the tuple table, and variables ?MinArity and ?MinArity to the minimum and maximum numbers of arguments of atoms that refer to the tuple table.

Request

GET /datastores/myStore/tupletables HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name,ID,NumberOfColumns,Columns,DataSource
internal:triple,1,3,s&p&o
[...]

Java API

List<TupleTableInfo> tupleTableInfos = dsConn.listTupleTables();

14.7.2. Creating a Tuple Table

The following request creates a new tuple table, which can be either an in-memory tuple table or a tuple table backed by a data source. Creating a tuple table requires specifying the table name as part of the URI, and supplying request parameters that determine the table arity and a number of key-value pairs that either specify indexing options for in-memory tuple tables, or parameters used to mount a tuple table from a data source.

Request

POST /datastores/myStore/tupletables/myTable?arity=2&key1=val1&key2=val2 HTTP/1.1
Host: localhost

Response

HTTP/1.1 201 CREATED
Location: /datastores/myStore/tupletables/myTable

Java API

Map<String, String> parameters = new HashMap<String, String>();
parameters.put("key1", "val1");
parameters.put("key2", "val2");
dsConn.createTupleTable("myTable", parameters);

14.7.3. Deleting a Tuple Table

The following request deletes a tuple table, which can be either an in-memory tuple table or a tuple table backed by a data source. The request succeeds only if a tuple table is not used in a rule currently loaded in the data store.

Request

DELETE /datastores/myStore/tupletables/myTable HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

dsConn.deleteTupleTable("myTable");

14.7.4. Retrieving Information About a Tuple Table

The following request retrieves information about a tuple table. The response is written as an output of a SPARQL query that binds variables ?Property and ?Value. The exact properties and values are determined by the tuple table type.

Request

GET /datastores/myStore/tupletables/myTable HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value
name,internal:triple
ID,1
min-arity,3
max-arity,3
... etc ...

The TupleTableInfo class encapsulates information about a tuple table in the Java API. Instances of this class are immutable.

Java API

TupleTableInfo tupleTableInfo = dsConn.describeTupleTable("myTable");

14.8. Evaluating Queries

The /sparql key exposes a SPARQL 1.1 endpoint implemented exactly as in the specification. Both GET and POST request methods are supported. Moreover, SELECT/ASK, CONSTRUCT, and DELETE/INSERT queries are supported. Query evaluation in RDFox can be influenced using a number of parameters, which can be passed as key-value pairs. The query result is encoded according to the required format, and a request fails if the format does not match the query type (e.g., if a request specifies a SELECT query and the Turtle answer format).

The following is an example of a query request.

Request

GET /datastores/myStore/sparql?query=SELECT+%3FX+%3FY+%3FZ+WHERE+{+%3FX+%3FY+%3FZ+} HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK

X,Y,Z
[...result of the query...]

Java API

Map<String, String> parameters = new HashMap<String, String>();
// Query evaluation supports a bunch of parameters that govern how
// queries are compiled. The RESTful API would use the default parameters,
// but the Java API would allow finer control.
parameters.set(..., ...);
// While one can specify a set of prefixes in a query, it is often useful
// in applications to maintain a global set of prefixes that does not need
// to be explicitly set and parsed every time. Thus, query evaluation accepts
// a set of prefixes that can be used in the query and that will be used to
// serialize the results.
Prefixes prefixes = ...;
// The final two parameters determine the output format. Query evaluation
// can return these kinds of results:
//
// * a set of rows in case of SELECT/ASK queries,
// * an RDF graph in case of CONSTRUCT queries, or
// * nothing in the case of UPDATE queries.
//
// It seems useful to have an API that can evaluate any query, regardless of
// its type. Therefore, the following function requires three parameters:
//
// * an output stream to which answers are written (if there are any),
// * the name of a SPARQL answer format (in case of SELECT/ASK queries), and
// * the name of an RDF format (in case of CONSTRUCT queries).
//
// If the caller is sure of the query type, they can supply unused parameters as null.
OutputStream output = ...;
dsConn.evaluateQuery(prefixes, "SELECT ?X ?Y ?Z WHERE { ?X ?Y ?Z }", parameters, output, "text/csv", null);

SPARQL supports pagination of query results using OFFSET and LIMIT query clauses; however, evaluating the same query while varying its OFFSET/LIMIT clauses may be inefficient because the query in each request is evaluated from scratch.

In the RESTful API, including the offset=m;limit=n parameters into a query request has the same effect as adding the OFFSET m LIMIT n clauses to the query. However, doing the former can be more efficient when

  • a user makes a query request with offset=m1;limit=n1,

  • the same user makes another request for exactly the same query (i.e., a query that is character-for-character identical as the previous one) with offset=m2;limit=n2 where m2 = m1 + n1 + 1, and

  • the data store has not been updated between these two requests.

RDFox provides no hard efficiency guarantees, but will try to process requests containing offset=m;limit=n as efficiently as possible. Therefore, applications should use this approach to result pagination whenever possible. The endpoint.object-expiry-time option specifies the rough amount of time between two such requests for the same query during which RDFox will aim to speed up query evaluation.

SPARQL queries can be long in some applications, so sending the same query multiple times can be a considerable source of overhead. In such cases, applications can consider using cursors (See Section 14.10), where a query is submitted for execution just once. These APIs, however, must be used within a transaction and are thus described in Section 12.

14.9. Working with Transactions

14.9.1. Transactions in the Java API

In the Java API, each transaction is associated with one data store connection. The DataStoreConnection class provides beginTransaction(), commitTransaction(), and rollbackTransaction() functions, which respectively start, commit, and roll back a transaction.

If no transaction is associated with a connection, then data store modification functions and query evaluation functions start a transaction that is committed or rolled back before the function finishes. In contrast, if a transaction is started on a connection when a modification/query function is called, then the operation is evaluated within the context of that transaction.

A transaction remains open in the Java API as long as it is not explicitly committed or rolled back. Closing a connection with a running transaction will rollback the transaction first.

Data store connections are single-threaded objects: attempting to use the same object in parallel from multiple threads will result in unpredictable behavior and is likely to crash the system. (However, the same data store connection object can be used from different threads at distinct time points — that is, there is no affinity between connection objects and threads.) In order to access RDFox concurrently, one should use distinct connections, each running a separate transaction.

14.9.2. Transactions in the RESTful API

The RESTfull API follows the same principles and associates transactions with data store connections. To use transactions in the RESTful API, one must use explicitly create a connection (see Section 14.2.5). To start, commit, or rollback a transaction, one can issue a PATCH request to the /datastores/<DSTRNAME>/connections/<DSCONN>/transaction key with the operation request parameter set to begin-read-only-transaction, begin-read-write-transaction, commit-transaction, or rollback-transaction. After this, any operation evaluated on this connection (which can be achieved by including the connection request parameter) will be evaluated inside the transaction associated with the connection.

For example, the following sequence of requests creates a connection and starts a read/write transaction (in one request to save the round-trip to the server), import data twice, and commits the transaction. Please note that, although the transaction has been committed, the connection persists after the last request.

Request

PATCH /datastores/myStore/connections/DSC01234567890123456789/transaction&operation=begin-read-write-transaction HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Request

POST /datastores/myStore/content?connection=DSC01234567890123456789 HTTP/1.1
Host: localhost

[First batch of facts/rules]

Response

HTTP/1.1 200 OK

[Response body as usual]

Request

POST /datastores/myStore/content?connection=DSC01234567890123456789 HTTP/1.1
Host: localhost

[Second batch of facts/rules]

Response

HTTP/1.1 200 OK

[Response body as usual]

Request

PATCH /datastores/myStore/connections/DSC01234567890123456789/transaction&operation=commit-transaction HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

At any point, one can see whether a connection is associated with a transaction as follows. The response is written as the output of a SPARQL query that binds the variable ?Property to the property name, variable ?Value to the property value, and variable ?Mutable to true if the value of the property can be changed and to false otherwise.

Request

GET /datastores/myStore/connections/DSC01234567890123456789/transaction HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value,Mutable
transaction-state,read-write,false
transaction-requires-rollback,false,false
last-transaction-data-store-version,5,false

14.10. Cursors

As already mentioned in Section 14.8, RDFox supports efficient APIs for paginating query results using cursors, which provide a view into the results of a query evaluated on a ‘frozen’ snapshot of data. The concept of cursors is used in slightly different ways in the Core and the RESTful APIs, so this section discusses first the former and then the latter.

14.10.1. Cursors in the Java API

The Java API uses cursors to provide access to answers to queries. A cursor goes through the following life cycle.

  • When a cursor is created, it is in an unopened state.

  • Before it is used, a cursor must be opened, which positions the cursor on the first answer tuple, or at the answer end if there are no answer tuples. Opening the cursor returns the multiplicity of the current answer, or zero if there are no answers.

  • Advancing a cursor returns the multiplicity of the next row. Cursors cannot go backwards — all movement is forward.

  • A cursor can at any point be reopened, in which case the query underlying the cursor is reevaluated afresh. By creating cursors for queries that are evaluated many times, applications can speed up query processing by avoiding the overhead of parsing and compiling the query in each request.

  • When a cursor is no longer needed, it must be closed so that any resources associated with it can be released. This must be done even when cursors are read to the end. In Java, the Cursor class implements the AutoCloseable interface so that it can be used in a try-with-resources statement.

The reason why rows have multiplicities is because SPARQL has bag semantics, and if an answer contains the same tuple n times, it can be more efficient to return the tuple once and say that the tuple’s multiplicity is n. The Java API supports cursors for SELECT/ASK and CONSTRUCT queries. A cursor for a CONSTRUCT query behaves as a cursor for a SELECT/ASK query retuning variables ?S, ?P, and ?O for each constructed triple.

Each cursor is associated with a data store connection that it is created on. Moreover, all operations on a cursor are evaluated in the context of a connection transaction. For example, if a transaction is running on the connection when a cursor is opened, then opening the cursor is performed within this transaction. Moreover, if no transaction is running on the connection when a cursor is opened, a temporary read-only transaction is started, the cursor is opened, and the transaction is rolled back. A cursor is advanced analogously, possibly starting a temporary transaction each time it is advanced.

The use of temporary transactions opens a potential consistency problem, which is illustrated by the following sequence of actions.

  • Create a cursor on a connection not associated with a transaction.

  • Open a cursor (which implicitly creates a temporary transaction for the duration of the operation).

  • Modify the content on the data store using a different connection. Since the cursor’s connection is not associated with a transaction, modification is possible, and it can affect the results of the query produced by the cursor.

  • Advance the cursor. At this point, RDFox will detect that the data store has changed since the cursor was opened, and, to inform the user of this fact, it would throw StaleCursorException. In this way, RDFox prevents users from possibly overlooking the effects of updates applied to the data store while the cursor is being used. Please note that RDFox will throw StaleCursorException even if the update does not affect the cursor’s result — that is, RDFox’s consistency mechanism is pessimistic.

Please note that StaleCursorException can happen only if the cursor uses temporary transactions in open and advance. In other words, the the cursor is opened and advanced within a single, uninterrupted transaction, then StaleCursorException cannot happen.

Cursors are typically used in the Java API as follows.

Map<String, String> parameters = new HashMap<String, String>();
// Initialize parameters that govern query evaluation.
parameters.set(..., ...);
// Initialize the prefixes the may now
Prefixes prefixes = ...;
// Create the cursor.
Cursor crs = dsConn.createCursor(prefixes, "SELECT ?X ?Y ?Z WHERE { ?X ?Y ?Z }", parameters);
for (long multiplicity = crs.open(); multiplicity != 0; multiplicity = crs.advance()) {
    // Read the current answer
}
crs.close();

14.10.2. Cursors in the RESTful API

The RESTful API supports efficient query result pagination using the offset=m;limit=n request parameters (see Section 14.8). However, this style of result pagination requires resending the same query in each request, which can be inefficient. Moreover, applications relying on the RESTful API might also benefit from precompiling common queries into cursors that are managed explicitly.

To support such use cases, the RESTful API cupports explicit cursor management that mimics the cursor Java API. Each cursor is identified by an ID exposed under the /datastores/<DSTRNAME>/connections/<DSCONN>/cursors key; note that this arrangement reflects the fact that each cursor is associated with a specific data store connection. When a data store connection is deleted, all cursors associated with the connection are deleted as well. Each cursor exposed by the RESTful API maintains its position, and there is an API allowing users to query the current cursor position.

14.10.2.1. Listing Available Cursors

The following request retrieves the list of cursors available on a server transaction. The response is written as an output of a SPARQL query that binds variable ?CursorID to the cursor ID.

Request

GET /datastores/myStore/connections/DSC01234567890123456789/cursors HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

CursorID
CRS101
CRS102

14.10.2.2. Creating a Cursor

A cursor is created by submitting the query to the /cursors key using the POST method of the SPARQL 1.1 Protocol. The location of the new cursor is returned in the Location header.

Request

POST /datastores/myStore/connections/DSC01234567890123456789/cursors HTTP/1.1
Host: localhost
Content-Type: application/sparql-query
Content-Length: 34

SELECT ?X ?Y ?Z WHERE { ?X ?Y ?Z }

Response

HTTP/1.1 201 CREATED
Location: /datastores/myStore/connections/DSC01234567890123456789/cursors/CRS101

14.10.2.3. Opening and Advancing a Cursor

a POST request on the cursor opens or advances the cursor; to distinguish the two, the operation request parameter must be included with value open or advance. Moreover, request can include limit=n parameter determining how many rows should be returned; if this parameter is absent, all remaining rows are returned. Parameter limit=0 can be used to specify that no answers should be returned (and so the request just validates the cursor). The request updates the cursor position and so such a request is not idempotent; consequently, the request method is POST. In all such cases, the request must specify an Accept header to determine the format of the returned data. Different requests on the same cursor can request different result formats. If the cursor has already returned all results, the response includes a proprietary X-Cursor-Exhausted: true header.

Request

POST /datastores/myStore/connections/DSC01234567890123456789/cursors/CRS101?operation=open&limit=10 HTTP/1.1
Host: localhost
Accept: text/csv

Response

HTTP/1.1 200 OK

[The first 10 answers to the query in CSV format]

14.10.2.4. Retrieving Cursor Information

The following request retrieves information about a specific cursor. The response is written as an output of a SPARQL query that binds variable ?Property to the name of a cursor property, and variable ?Value to property value.

Request

GET /datastores/myStore/connections/DSC01234567890123456789/cursors/CRS101 HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value
ID,CRS1
position,10

14.10.2.5. Deleting a Cursor

The following request closes/deletes the cursor.

Request

DELETE /datastores/myStore/connections/DSC01234567890123456789/cursors/CRS101 HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

14.11. Handling Concurrent Updates

Many applications of RDFox need to gracefully handle concurrent updates by different users. Although RDFox provides transactions to ensure consistency of parallel updates, such a construct may be insufficient in examples such as the following.

  • A graph-like visualisation of an RDF dataset may initially show just a handful of RDF resources, and allow users to interactively explore and expand the neighbourhood of each resource. Clearly, it is desirable to show to each user a consistent view of the data at any given point in time. However, opening a read-only transaction for the duration of each user’s interaction is ill-advised as it would prevent the data store from being updated. Instead, the application might want to detect when the underlying data has changed and notify the user and/or refresh the view appropriately.

  • A common pattern to updating data in applications involves reading current data, showing the data to the user and allowing them to make changes, and then writing the data back to the data store. Such operations involves user interaction, which can take significant time. As a result, it is usually not desirable to wrap the entire operation in a read/write transaction. Instead, many applications use ‘optimistic’ concurrency control, where the update succeeds only if the data store was not updated since the data was shown to the user; otherwise, the entire process is restarted.

This section describes aspects of the RDFox API that aim to address these two problems.

14.11.1. Detecting Updates

Each data store is associated with a 20-digit ID that, at any point in time, uniquely identifies a data store in the server. Also, RDFox aims to assign different unique IDs to data stores created at different point in time.

Each data store also maintains a data store version, which is a positive integer. Each time a data store is updated, the version of the data store is incremented.

Jointly, a data store unique ID and a data store version identify a particular state of a data store. That is, if these values are the same between two API calls, then we know that the data store has not been updated. The converse does not hold necessarily: even if an update request fails, the version may be incremented before the failure is detected. Nevertheless, differing unique ID and/or versions between two API calls indicate with a high degree of probability that the data store has been updated.

14.11.1.1. Java API

The DataStoreConnection class in Java API provides a getUniqueID() and getDataStoreVersion() methods that allow users to retrieve the unique ID and the data store version, respectively. Moreover, the getLastTransactionDataStoreVersion() method returns the version of the data store at the point the last transaction was successfully evaluated on this connection (or 0 if no transaction has been evaluated on this connection). Thus, by recording the unique ID and the data store version and comparing them with the values in subsequent requests, an application can detect that a data store has been updated. Note that the unique ID of a data store never changes during the lifetime of a data store. Moreover, each data store connection is associated with just one data store, and so a unique ID can never change on one connection.

14.11.1.2. RESTful API

The RESTful API exposes these pieces of information as ETags, which are strings of the form "uniqueID-version". For HTTP request operating on a data store or any of its parts, the response will contain a header of the form ETag: "uniqueID-version" indicating the version of the data store upon request’s completion. The following example illustrates this on the example of data importation.

Request

POST /datastores/myStore/content HTTP/1.1
Host: localhost

[The facts/rules to be added in a format supported by RDFox]

Response

HTTP/1.1 200 OK
ETag: "01234567890123456789-2"

[Response body as usual]

In HTTP, an ETag is considered specific to each resource. In RDFox, however, the same ETag is generated for all resources of a particular data store. Thus, in the above example, ETag "01234567890123456789-2" applies not only to resource /datastores/myStore/content, but also to /datastores/myStore and every resource underneath (such as, say, /datastores/myStore/content/tupletables). In other words, importing the data into the data store using /datastores/myStore/content changes the ETags of all parts of the data store.

In HTTP, it is customary to return an ETag only on successful responses. In RDFox, however, an ETag will be returned even in some error respones. This is in order to keep the user informed about the current data store version as much as possible. Specifically, most requests are processed as follows.

  • A request is first checked to conform to the RESTful API syntax. For example, some requests must specify certain request parameters, some requests may not admit a request body, and so on. In most cases, an ETag will not be sent if a request cannot be validated properly. The rationale behind this is that syntactically malformed requests do not match to well-defined RDFox operations.

  • A request is then submitted for execution. If this step fails (e.g., because the data in an update request is malformed), an ETag will in most cases be sent in the error response. The rationale behind this is that the request matches to well-defined RDFox operations, and so knowing the current data store version might actually be used to recover from failure.

14.11.2. Conditional Requests

RDFox can evaluate all operations conditionally — that is, an operation succeeds only if the data store unique ID and version match specific values before the request is processed. Note that a naive solution, where a user reads and compares the data store version before each request, is incorrect: a data store version can change in the interval between the user reading the version and issuing the request. RDFox addresses this by integrating these checks with its transaction processing.

14.11.2.1. Java API

To support version checking, the DataStoreConnection class in Java API provides the setTransactionMustMatchDataStoreVersion() and setTransactionMustNotMatchDataStoreVersion() methods. Both methods take an integer argument, which configure the connection to expect or not expect a specific version on next request. Please note that version validation is not done in these methods themselves; rather, the version is validated on next request executed in a transaction. If the validation fails, the request will throw a DataStoreVersionDoesNotMatchException or DataStoreVersionMatchesException.

DataStoreConnection dsConn = ...
// Use the data store connection...
...
// Save the data store version after the last transaction.
long savedDataStoreVersion = dsConn.getLastTransactionDataStoreVersion();
// Use the data store connection some more...
...
// Configure the connection to expect savedDataStoreVersion in next transaction.
// The following call will not check the version!
dsConn.setTransactionMustMatchDataStoreVersion(savedDataStoreVersion);
// The following call fails if the version at the point of execution is
// different from savedDataStoreVersion.
dsConn.importData(...);
// The following switches data store validation off.
dsConn.setTransactionMustMatchDataStoreVersion(0);

Once an expected version has been set on the connection, the value remains active until setTransactionMustMatchDataStoreVersion() is called with argument 0. Moreover, if the connection is configured to expect a particular version and a data store update is successful, the data store version will be incremented and the resulting value will be set as the next expected data store version. In this way, users can processing subsequent updates on the connection without having to update an expected version.

The setTransactionMustNotMatchDataStoreVersion() method is analogous, but it configures the connection to not accept a specific version. This can be used, for example, to avoid reevaluating a complex query unless the data store has changed. Successful updates will not change this parameter of the connection.

14.11.2.2. RESTful API

In the RESTful API, conditional requests are supported using standard HTTP If-Match and If-None-Match headers. Specifically, if a request contains an If-Match header with a particular ETag, the request will succeed only if the version of the data store matches the ETag when the request is executed. This is illustrated by the following example, where the request (presumably) fails because of a version mismatch.

Request

POST /datastores/myStore/content HTTP/1.1
Host: localhost
If-Match: "01234567890123456789-2"

[The facts/rules to be added in a format supported by RDFox]

Response

HTTP/1.1 412 Precondition Failed
ETag: "01234567890123456789-5"
Content-Type: text/plain; charset=UTF-8
Content-Length: XX

DataStoreVersionDoesNotMatchException: Data store version is 5, which is different from the expected version 2.

Note that the response in the above example contains the current ETag of the data store. Thus, an application can try to use this ETag in any subsequent request, which will succeed only if the data store has not been modified in the meanwhile.

The If-None-Match header is analogous, but it ensures that the request succeeds only if the version is different from the given one. This is illustrated by the following request.

Request

GET /datastores/myStore/sparql?query=SELECT+%3FX+%3FY+%3FZ+WHERE+{+%3FX+%3FY+%3FZ+} HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8
If-None-Match: "01234567890123456789-5"

Response

HTTP/1.1 304 Not Modified
ETag: "01234567890123456789-5"
Content-Type: text/plain; charset=UTF-8
Content-Length: XX

DataStoreVersionMatchesException: Data store version is equal to 5.

Conditional requests in RDFox differ from HTTP in the following minor ways.

  • ETags are opaque values in HTTP that must match exactly. RDFox, however, allows for partial matches. In particular, the value of If-Match and If-None-Match headers can have the form "uniqueID-version" where uniqueID and version can either be specific values or the wildcard character *. Thus, "01234567890123456789-*" matches any data store whose unique ID is 01234567890123456789, regardless of the current data store version. Analogously, "*-5" matches any data store whose version is 5, and "*-*" matches any data store.

  • HTTP allows one to specify more than one ETag in the If-Match or If-None-Match headers. However, RDFox will reject such requests: the allowed values for these headers are * (which means ‘match any’ in HTTP) or a single ETag (possibly containing wildcard characters as explained above).

14.12. Managing Roles

This section describes the API calls responsible for managing the roles defined within an RDFox server. For an introduction to RDFox’s access control model see Section 11.

14.12.1. Listing Roles

The following request retrieves the list of roles defined within the server. The response is written as an output of a SPARQL query that binds variable ?Name to the names of the available roles.

Request

GET /roles HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name
admin
group
user1

Java API

List<String> roleNames = sConn.listRoles();

14.12.2. Creating a Role

The following request creates a new role. The role name is specified as part of the request URL and the password as a text/plain body. The type query parameter can be used to specify the whether the role should be created using a password (if type is not specified or set to password) or password hash (if type is set to hash).The location of the new role is returned in the Location header.

Request

POST /roles/user2 HTTP/1.1
Host: localhost
Content-Type: text/plain
Content-Length: 14

user2's secret

Response

HTTP/1.1 201 Created
Location: /roles/user2

Java API

sConn.createRole("user2", "user2's secret");

14.12.3. Deleting a Role

The following request deletes a role.

Request

DELETE /roles/user2 HTTP/1.1
Host: localhost

Response

HTTP/1.1 204 No Content

Java API

sConn.deleteRole("user2");

14.12.4. Listing Role Information

The following request lists information about an existing role. The response is written as an output of a SPARQL query that returns one answer per property of the role. For each answer, the variable ?Name contains a name of the parameter and the variable ?Value holds its value.

Request

GET /roles/admin HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Property,Value
name,admin
password-hash,"$argon2i$v=19$m=208651,t=3,p=16$xNWat7TDiKEGGU2W66u/Pw$h9ObPGi855ypuDBI7Nr2zeWAa6f2VBmIrFRs32gEXHY"

Java API

String passwordHash = sConn.getRolePasswordHash("user1");

14.12.5. Listing Privileges

The following request lists the privileges of an existing role. The response is written as an output of a SPARQL query that returns one answer per resource specifier over which the role has any privileges. For each answer, the variable ?AllowedAccessTypes contains a comma-separated list of access types the role is allowed to perform over the resources specified by the resource specifier in the ?ResourceSpecifier variable.

Request

GET /roles/user1/privileges HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

ResourceSpecifier,AllowedAccessTypes
>datastores,"read,write"
|roles,read

Java API

Map<String, Byte> privileges = sConn.listPrivileges("user1");

14.12.6. Granting Privileges to a Role

The following request grants the read and write privileges over the data store list to an existing role.

Request

PATCH /roles/user1/privileges?operation=add HTTP/1.1
Host: localhost
Content-Length: 54
Content-Type: application/x-www-form-urlencoded

resource-specifier=|datastores&access-types=read,write

Response

HTTP/1.1 204 No Content

Java API

sConn.grantPrivileges("user1", "|datastores", (byte)(ServerConnection.ACCESS_TYPE_READ | ServerConnection.ACCESS_TYPE_WRITE));

14.12.7. Revoking Privileges from a Role

The following request revokes the write privilege over the data store list from an existing role.

Request

PATCH /roles/user1/privileges?operation=delete HTTP/1.1
Host: localhost
Content-Length: 49
Content-Type: application/x-www-form-urlencoded

resource-specifier=|datastores&access-types=write

Response

HTTP/1.1 204 No Content

Java API

sConn.revokePrivileges("user1", "|datastores", (byte)(ServerConnection.ACCESS_TYPE_WRITE));

14.12.8. Listing Memberships

The following request lists the roles of which the specified role is a member. The response is written as an output of a SPARQL query that binds variable ?Name to the names of the role’s super roles.

Request

GET /roles/user1/memberships HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name
group

Java API

List<String> memberships = sConn.listRoleMemberships("user1");

14.12.9. Granting Memberships

The following request grants membership of the role group to an existing role.

Request

PATCH /roles/user1/memberships?operation=add HTTP/1.1
Host: localhost
Content-Length: 19
Content-Type: application/x-www-form-urlencoded

super-role-name=group

Response

HTTP/1.1 204 No Content

Java API

sConn.grantRole("user1", "group");

14.12.10. Revoking Memberships

The following request revokes membership of the role group from an existing role.

Request

PATCH /roles/user1/memberships?operation=delete HTTP/1.1
Host: localhost
Content-Length: 19
Content-Type: application/x-www-form-urlencoded

super-role-name=group

Response

HTTP/1.1 204 No Content

Java API

sConn.revokeRole("user1", "group");

14.12.11. Listing Members

The following request lists the roles which are members of the specified role. The response is written as an output of a SPARQL query that binds variable ?Name to the names of the role’s members.

Request

GET /roles/group/members HTTP/1.1
Host: localhost
Accept: text/csv; charset=UTF-8

Response

HTTP/1.1 200 OK
Content-Type: text/csv; charset=UTF-8

Name
user1

Java API

List<String> members = sConn.listRoleMembers("user1");

14.12.12. Changing Passwords

The following request sets the password for the authenticated role. The request body must contain the old and the new passwords separated by a single \n (CR) character.

Request

PUT /password HTTP/1.1
Host: localhost
Authorization: Basic dXNlcjE6dXNlcjE=
Content-Type: text/plain
Content-Length: 20

user1's old password
user1's new password

Response

HTTP/1.1 204 No Content

Java API

sConn.changeRolePassword("user1's old password", "user1's new password");

14.13. Checking Endpoint Health

The following request may be used to test that the endpoint is healthy (able to respond to requests). Note that no authorization is required, irrespective of the server’s access control policy.

Request

GET /health HTTP/1.1

Response

HTTP/1.1 204 No Content

There is no equivalent of this API in Java.