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| <h1 class="title">TDB Optimizer</h1> |
| |
| <p>Query execution in TDB involves both static and dynamic |
| optimizations. Static optimizations are transformations of the |
| SPARQL algebra performed before query execution begins; dynamic |
| optimizations involve deciding the best execution approach during |
| the execution phase and can take into account the actual data so |
| far retrieved.</p> |
| <p>The optimizer has a number of strategies: a statistics based |
| strategy, a fixed strategy and a strategy of no reordering.</p> |
| <p>For the preferred statistics strategy, the TDB optimizer uses |
| information captured in a per-database statistics file. The file |
| takes the form of a number of rules for approximate matching counts |
| for triple patterns. The statistic file can be automatically |
| generated. The user can add and modify rules to tune the database |
| based on higher level knowledge, such as inverse function |
| properties.</p> |
| <h2 id="contents">Contents</h2> |
| <ul> |
| <li><a href="#quickstart">Quickstart</a></li> |
| <li><a href="#running-tdbstats">Running tdbstats</a></li> |
| <li><a href="#choosing-the-optimizer-strategy">Choosing the optimizer strategy</a></li> |
| <li><a href="#filter-placement">Filter placement</a></li> |
| <li><a href="#investigating-what-is-going-on">Investigating what is going on</a></li> |
| <li><a href="#statistics-rule-file">Statistics Rule File</a> |
| <ul> |
| <li><a href="#statistics-rule-language">Statistics Rule Language</a></li> |
| <li><a href="#abbreviated-rule-form">Abbreviated Rule Form</a></li> |
| <li><a href="#defaults">Defaults</a></li> |
| </ul> |
| </li> |
| <li><a href="#generating-a-statistics-file">Generating a statistics file</a> |
| <ul> |
| <li><a href="#generating-statistics-for-union-graphs">Generating statistics for Union Graphs</a></li> |
| </ul> |
| </li> |
| <li><a href="#writing-rules">Writing Rules</a></li> |
| </ul> |
| <p>The commands look for file <code>log4j2.properties</code> in the current directory, as well |
| as the usual log4j2 initialization with property <code>log4j.configurationFile</code> and |
| looking for classpath resource <code>log4j2.properties</code>; there is a default setup of |
| log4j2 built-in.</p> |
| <h2 id="quickstart">Quickstart</h2> |
| <p>This section provides a practical how-to.</p> |
| <ol> |
| <li>Load data.</li> |
| <li>Generate the statistics file. Run tdbstats.</li> |
| <li>Place the file generated in the database directory with the |
| name stats.opt.</li> |
| </ol> |
| <h2 id="running-tdbstats">Running <code>tdbstats</code></h2> |
| <p>Usage:</p> |
| <pre><code> tdbstats --loc=DIR|--desc=assemblerFile [--graph=URI] |
| </code></pre> |
| <h2 id="choosing-the-optimizer-strategy">Choosing the optimizer strategy</h2> |
| <p>TDB chooses the basic graph pattern optimizer by the presence of a |
| file in the database directory.</p> |
| <p>Optimizer control files</p> |
| <table> |
| <thead> |
| <tr> |
| <th>File name</th> |
| <th>Effect</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td><code>none.opt</code></td> |
| <td>No reordering - execute triple patterns in the order in the query</td> |
| </tr> |
| <tr> |
| <td><code>fixed.opt</code></td> |
| <td>Use a built-in reordering based on the number of variables in a triple pattern.</td> |
| </tr> |
| <tr> |
| <td><code>stats.opt</code></td> |
| <td>The contents of this file are the weighing rules (see below).</td> |
| </tr> |
| </tbody> |
| </table> |
| <p>The contents of the files <code>none.opt</code> and <code>fixed.opt</code> are not read |
| and don’t matter. They can be zero-length files.</p> |
| <p>If more then one file is found, the choice is made: <code>stats.opt</code> |
| over <code>fixed.opt</code> over <code>none.opt</code>.</p> |
| <p>The “no reorder” strategy can be useful in investigating the |
| effects. Filter placement still takes place.</p> |
| <h2 id="filter-placement">Filter placement</h2> |
| <p>One of the key optimization is of filtered basic graph patterns. |
| This optimization decides the best order of triple patterns in a |
| basic graph pattern and also the best point at which to apply the |
| filters within the triple patterns.</p> |
| <p>Any filter expression of a basic graph pattern is placed |
| immediately after all it’s variables will be bound. Conjunctions at |
| the top level in filter expressions are broken into their |
| constituent pieces and placed separately.</p> |
| <h2 id="investigating-what-is-going-on">Investigating what is going on</h2> |
| <p>TDB can optionally log query execution details. This is controlled |
| by two setting: the logging level and a context setting. Having two |
| setting means it is possible to log some queries and not others.</p> |
| <p>The logger used is called <code>org.apache.jena.arq.exec</code>. Messages are |
| sent at level “INFO”. So for log4j2, the following can be set in the |
| log4j2.properties file:</p> |
| <pre><code># Execution logging |
| logger.arq-exec.name = org.apache.jena.arq.exec |
| logger.arq-exec.level = INFO |
| |
| logger.arq-info.name = org.apache.jena.arq.exec |
| logger.arq-info.level = INFO |
| </code></pre> |
| <p>The context setting is for key (Java constant) <code>ARQ.symLogExec</code>. To |
| set globally:</p> |
| <pre><code>ARQ.getContext().set(ARQ.symLogExec,true) ; |
| </code></pre> |
| <p>and it may also be set on an individual query execution using its |
| local context.</p> |
| <pre><code>try(QueryExecution qExec = QueryExecution.dataset(dataset) |
| .query(query) |
| .set(ARQ.symLogExec,true) |
| .build() ) { |
| ResultSet rs = qExec.execSelect() ; |
| } |
| </code></pre> |
| <p>On the command line:</p> |
| <pre><code> tdbquery --set arq:logExec=true --file queryfile |
| </code></pre> |
| <h2 id="explanation-levels">Explanation Levels</h2> |
| <table> |
| <thead> |
| <tr> |
| <th>Level</th> |
| <th>Effect</th> |
| </tr> |
| </thead> |
| <tbody> |
| <tr> |
| <td>INFO</td> |
| <td>Log each query</td> |
| </tr> |
| <tr> |
| <td>FINE</td> |
| <td>Log each query and it’s algebra form after optimization</td> |
| </tr> |
| <tr> |
| <td>ALL</td> |
| <td>Log query, algebra and every database access (can be expensive)</td> |
| </tr> |
| <tr> |
| <td>NONE</td> |
| <td>No information logged</td> |
| </tr> |
| </tbody> |
| </table> |
| <p>These can be specified as string, to the command line tools, or |
| using the constants in <code>Explain.InfoLevel</code>.</p> |
| <pre><code> qExec.getContext().set(ARQ.symLogExec,Explain.InfoLevel.FINE) ; |
| </code></pre> |
| <h2 id="tdbquery---explain">tdbquery –explain</h2> |
| <p>The <code>--explain</code> parameter can be used for understanding the query execution. |
| An execution can detail the query, algebra and every point at which the |
| dataset is touched.</p> |
| <p>For example, given the sample query execution with <code>tdbquery</code> below</p> |
| <pre><code>tdbquery --loc=DB "SELECT * WHERE { ?a ?b ?c }" |
| </code></pre> |
| <p>we can include the <code>--explain</code> parameter to the command</p> |
| <pre><code>tdbquery --explain --loc=DB "SELECT * WHERE { ?a ?b ?c }" |
| </code></pre> |
| <p>and increase the logging levels, in order to output more information about |
| the query execution.</p> |
| <pre><code># log4j2.properties |
| log4j.rootLogger=INFO, stdlog |
| log4j.appender.stdlog=org.apache.log4j.ConsoleAppender |
| log4j.appender.stdlog.layout=org.apache.log4j.PatternLayout |
| log4j.appender.stdlog.layout.ConversionPattern=%d{HH:mm:ss} %-5p %-25c{1} :: %m%n |
| |
| status = error |
| name = PropertiesConfig |
| filters = threshold |
| filter.threshold.type = ThresholdFilter |
| filter.threshold.level = INFO |
| |
| appender.console.type = Console |
| appender.console.name = STDOUT |
| appender.console.layout.type = PatternLayout |
| appender.console.layout.pattern = %d{HH:mm:ss} %-5p %-15c{1} :: %m%n |
| |
| rootLogger.level = INFO |
| rootLogger.appenderRef.stdout.ref = STDOUT |
| |
| # the query execution logger |
| |
| # Execution logging |
| logger.arq-exec.name = org.apache.jena.arq.exec |
| logger.arq-exec.level = INFO |
| </code></pre> |
| <p>The command output will be similar to this one.</p> |
| <pre><code>00:05:20 INFO exec :: QUERY |
| SELECT * |
| WHERE |
| { ?a ?b ?c } |
| 00:05:20 INFO exec :: ALGEBRA |
| (quadpattern (quad <urn:x-arq:DefaultGraphNode> ?a ?b ?c)) |
| 00:05:20 INFO exec :: TDB |
| (quadpattern (quad <urn:x-arq:DefaultGraphNode> ?a ?b ?c)) |
| 00:05:20 INFO exec :: Execute :: (?a ?b ?c) |
| </code></pre> |
| <p>The logging operation can be expensive, so try to limit it when possible.</p> |
| <h2 id="statistics-rule-file">Statistics Rule File</h2> |
| <p>The syntax is <code>SSE</code>, a simple format that uses |
| <a href="http://www.w3.org/TeamSubmission/turtle/" title="http://www.w3.org/TeamSubmission/turtle/">Turtle</a>-syntax |
| for RDF terms, keywords for other terms (for example, the stats |
| marks a statistics data structure), and forms a tree data |
| structure.</p> |
| <p>The structure of a statistics file takes the form:</p> |
| <pre><code>(prefix ... |
| (stats |
| (meta ...) |
| rule |
| rule |
| )) |
| </code></pre> |
| <p>that is, a <code>meta</code> block and a number of pattern rules.</p> |
| <p>A simple example:</p> |
| <pre><code>(prefix ((: <http://example/)) |
| (stats |
| (meta |
| (timestamp "2008-10-23T10:35:19.122+01:00"^^<http://www.w3.org/2001/XMLSchema#dateTime>) |
| (run@ "2008/10/23 10:35:19") |
| (count 11)) |
| (:p 7) |
| (<http://example/q> 7) |
| )) |
| </code></pre> |
| <p>This example statistics file contains some metadata about |
| statistics (time and date the file was generated, size of graph), |
| the frequence count for two predicates |
| <code>http://example/p</code> (written |
| using a prefixed name) and |
| <code>http://example/q</code> (written in |
| full).</p> |
| <p>The numbers are the estimated counts. They do not have to be exact</p> |
| <ul> |
| <li>they guide the optimizer in choosing one execution plan over |
| another. They do not have to exactly up-to-date providing the |
| relative counts are representative of the data.</li> |
| </ul> |
| <h3 id="statistics-rule-language">Statistics Rule Language</h3> |
| <p>A rule is made up of a triple pattern and a count estimation for |
| the approximate number of matches that the pattern will yield. This |
| does have to be exact, only an indication.</p> |
| <p>In addition, the optimizer considers which variables will be bound |
| to RDF terms by the time a triplepatetrn is reached in the |
| execution plan being considered. For example, in the basic graph |
| pattern:</p> |
| <pre><code>{ ?x :identifier 1234 . |
| ?x :name ?name . |
| } |
| </code></pre> |
| <p>then ?x will be bound in pattern ?x :name ?name to an RDF term if |
| executed after the pattern ?x :identifier 1234.</p> |
| <p>A rule is of the form:</p> |
| <pre><code>( (subj pred obj) count) |
| </code></pre> |
| <p>where <em>subj</em>, <em>pred</em>, <em>obj</em> are either RDF terms or one of the |
| tokens in the following table:</p> |
| <h3 id="statistic-rule-tokens">Statistic rule tokens</h3> |
| <p>Token | Description |
| TERM | Matches any RDF term (URI, Literal, Blank node) |
| VAR | Matches a named variable (e.g. ?x) |
| URI | Matches a URI |
| LITERAL | Matches an RDF literal |
| BNODE | Matches an RDF blank node (in the data) |
| ANY |Matches anything - a term or variable</p> |
| <p>From the example above, <code>(VAR :identifier TERM)</code> will match |
| <code>?x :identifier 1234</code>.</p> |
| <p><code>(TERM :name VAR)</code> will match <code>?x :name ?name</code> when in a potential plan |
| where the <code>:identifier</code> triple pattern is first because <code>?x</code> will be a |
| bound term at that point but not if this triple pattern is |
| considered first.</p> |
| <p>When searching for a weighting of a triple pattern, the first rule |
| to match is taken.</p> |
| <p>The rule which says an RDF graph is a set of triples:</p> |
| <pre><code>((TERM TERM TERM) 1) |
| </code></pre> |
| <p>is always implicitly present.</p> |
| <p>BNODE does not match a blank node in the query (which is a variable |
| and matches VAR) but in the data, if it is known that slot of a |
| triple pattern is a blank node.</p> |
| <h3 id="abbreviated-rule-form">Abbreviated Rule Form</h3> |
| <p>While a complete rule is of the form:</p> |
| <pre><code>( (subj pred obj) count) |
| </code></pre> |
| <p>there is an abbreviated form:</p> |
| <pre><code>(predicate count) |
| </code></pre> |
| <p>The abbreviated form is equivalent to writing:</p> |
| <pre><code>((TERM predicate ANY) X) |
| ((ANY predicate TERM) Y) |
| ((ANY predicate ANY) count) |
| </code></pre> |
| <p>where for small graphs (less that 100 triples) X=2, Y=4 but Y=40 if |
| the predicate is rdf:type and 2, 10, 1000 for large graphs. Use of |
| “VAR rdf:type Class” can be a quite unselective triple pattern and |
| so there is a preference to move it later in the order of execution |
| to allow more selective patterns reduce the set of possibilities |
| first. The astute reader may notice that ontological information |
| may render it unnecessary (the domain or range of another property |
| implies the class of some resource). TDB does not currently perform |
| this optimization.</p> |
| <p>These number are merely convenient guesses and the application can |
| use the full rules language for detailed control of pattern |
| weightings.</p> |
| <h3 id="defaults">Defaults</h3> |
| <p>A rule of the form:</p> |
| <pre><code>(other number) |
| </code></pre> |
| <p>is used when no matches from other rules (abbreviated or full) when |
| matching a triple pattern that has a URI in the predicate position. |
| If a rule of this form is absent, the default is to place the |
| triple pattern after all known triple patterns; this is the same as |
| specifying -1 as the number. To declare that the rules are complete |
| and no other predicates occur in the data, set this to 0 (zero) |
| because the triple pattern can not match the data (the predicate |
| does not occur).</p> |
| <h2 id="generating-a-statistics-file">Generating a statistics file</h2> |
| <p>The command line <code>tdbstats</code> will scan the data and produce a rules |
| file based on the frequency of properties. The output should first |
| go to a temporary file, then that file moved into the database |
| location.</p> |
| <p>Practical tip: Don’t feed the output of this command directly to |
| <em>location</em>/stats.opt because when the command starts it will find |
| an empty statistics file at that location.</p> |
| <h3 id="generating-statistics-for-union-graphs">Generating statistics for Union Graphs</h3> |
| <p>By default <code>tdbstats</code> only processes the default graph of a dataset. However |
| in some circumstances it is desirable to have the statistics generated |
| over Named Graphs in the dataset.</p> |
| <p>The <code>tdb:unionDefaultGraph</code> option will cause TDB to synthesize a default |
| graph for SPARQL queries, from the union of all Named Graphs in the |
| dataset.</p> |
| <p>Ideally the statistics file should be generated against this |
| union graph. This can be achieved using the <code>--graph</code> option as follows:</p> |
| <pre><code> tdbstats --graph urn:x-arq:UnionGraph --loc /path/to/indexes |
| </code></pre> |
| <p>The <code>graph</code> parameter uses a built-in TDB <a href="/documentation/tdb/datasets.html#special-graph-names">special graph name</a></p> |
| <h2 id="writing-rules">Writing Rules</h2> |
| <p>Rule for an inverse functional property:</p> |
| <pre><code>((VAR :ifp TERM) 1 ) |
| </code></pre> |
| <p>and even if a property is only approximately identifying for |
| resources (e.g. date of birth in a small dataset of people), it is |
| useful to indicate this. Because the counts needed are only |
| approximations so the optimizer can choose one order over another, |
| and does not need to predicate exact counts, rules that are usually |
| right but may be slightly wrong are still useful overall.</p> |
| <p>Rules involving rdf:type can be useful where they indicate whether |
| a particular class is common or not. In some datasets</p> |
| <pre><code>((VAR rdf:type class) ...) |
| </code></pre> |
| <p>may help little because a property whose domain is that class, or a |
| subclass, may be more elective. SO a rule like:</p> |
| <pre><code>((VAR :property VAR) ...) |
| </code></pre> |
| <p>is more selective.</p> |
| <p>In other datasets, there may be many classes, each with a small |
| number of instances, in which case</p> |
| <pre><code>((VAR rdf:type class) ...) |
| </code></pre> |
| <p>is a useful selective rule.</p> |
| |
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