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<h1 class="title">Jena Transactions API</h1>
<ul>
<li><a href="#api-for-transactions">API for Transactions</a>
<ul>
<li><a href="#read-transactions">Read transactions</a></li>
<li><a href="#write-transactions">Write transactions</a></li>
<li><a href="#types-modes-promotion">Transaction promotion</a></li>
</ul>
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<li><a href="txn.html">Txn</a> - A higher level API to transactions</li>
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<h2 id="api-for-transactions">API for Transactions</h2>
<p>This page describes the basic transaction API in Jena (3.1.0 and later).</p>
<p>There is also a <a href="txn.html">higher-level API</a> useful in many situations
but sometimes it is necessary to use the basic transaction API described here.</p>
<h3 id="read-transactions">Read transactions</h3>
<p>These are used for SPARQL queries and code using the Jena API
actions that do not change the data. The general pattern is:</p>
<pre><code> dataset.begin(ReadWrite.READ) ;
try {
...
} finally { dataset.end() ; }
</code></pre>
<p>The <code>dataset.end()</code> declares the end of the read transaction. Applications may also call
<code>dataset.commit()</code> or <code>dataset.abort()</code> which all have the same effect for a read transaction.</p>
<p>This example has two queries - no updates between or during the queries will be seen by
this code even if another thread commits changes in the lifetime of this transaction.</p>
<pre><code> Dataset dataset = ... ;
dataset.begin(ReadWrite.READ) ;
try {
String qs1 = &quot;SELECT * {?s ?p ?o} LIMIT 10&quot; ;
try(QueryExecution qExec = QueryExecution.create(qs1, dataset)) {
ResultSet rs = qExec.execSelect() ;
ResultSetFormatter.out(rs) ;
}
String qs2 = &quot;SELECT * {?s ?p ?o} OFFSET 10 LIMIT 10&quot; ;
try(QueryExecution qExec = QueryExecution.create(qs2, dataset)) {
rs = qExec.execSelect() ;
ResultSetFormatter.out(rs) ;
}
} finally { dataset.end() ; }
</code></pre>
<h3 id="write-transactions">Write transactions</h3>
<p>These are used for SPARQL queries, SPARQL updates and any Jena API
actions that modify the data. Beware that large <code>model.read</code>
operations to change a dataset may consume large amounts of temporary space.</p>
<p>The general pattern is:</p>
<pre><code> dataset.begin(ReadWrite.WRITE) ;
try {
...
dataset.commit() ;
} finally {
dataset.end() ;
}
</code></pre>
<p>The <code>dataset.end()</code> will abort the transaction is there was no call to
<code>dataset.commit()</code> or <code>dataset.abort()</code> inside the write transaction.</p>
<p>Once <code>dataset.commit()</code> or <code>dataset.abort()</code> is called, the application
needs to start a new transaction to perform further operations on the
dataset.</p>
<pre><code> Dataset dataset = ... ;
dataset.begin(TxnType.WRITE) ;
try {
Model model = dataset.getDefaultModel() ;
// API calls to a model in the dataset
// Make some changes via the model ...
model.add( ... )
// A SPARQL query will see the new statement added.
try (QueryExecution qExec = QueryExecution.create(
&quot;SELECT (count(?s) AS ?count) { ?s ?p ?o} LIMIT 10&quot;,
dataset)) {
ResultSet rs = qExec.execSelect() ;
ResultSetFormatter.out(rs) ;
}
// ... perform a SPARQL Update
String sparqlUpdateString = StrUtils.strjoinNL(
&quot;PREFIX . &lt;http://example/&gt;&quot;,
&quot;INSERT { :s :p ?now } WHERE { BIND(now() AS ?now) }&quot;
) ;
UpdateRequest request = UpdateFactory.create(sparqlUpdateString) ;
UpdateExecution.dataset(dataset).update(request).execute();
// Finally, commit the transaction.
dataset.commit() ;
// Or call .abort()
} finally {
dataset.end() ;
}
</code></pre>
<h2 id="types-modes-promotion">Transaction Types, Modes and Promotion.</h2>
<p>Transaction have a type (enum <code>TxnType</code>) and a mode (enum <code>ReadWrite</code>).
<code>TxnType.READ</code> and <code>TxnType.Write</code> start the transaction in
that mode and the mode is fixed for the transaction&rsquo;s lifetime. A <code>READ</code>
transaction can never update the data of the transactional object it is
acting on.</p>
<p>Transactions can have type <code>TxnType.READ_PROMOTE</code> or
<code>TxnType.READ_COMMITTED_PROMOTE</code>. These start in mode <code>READ</code> but can
become mode <code>WRITE</code>, either implicitly by attempting an update, or
explicitly by calling <code>promote</code>.</p>
<p><code>READ_PROMOTE</code> only succeeds if no writer has made any changes since
this transaction started. It gives full isolation.</p>
<p><code>READ_COMMITTED_PROMOTE</code> always succeeds because it changes the view of
the data to include any changes made up to that point (it is &ldquo;read
committed&rdquo;). Applications should be aware that data they have read up
until the point of promotion (the first call or <code>.promote</code> or first
update made) may now be invalid. For this reason, <code>READ_PROMOTE</code> is preferred.</p>
<p><code>begin()</code>, the method with no arguments, is equivalent to
<code>begin(TxnType.READ_PROMOTE)</code>.</p>
<h2 id="multi-threaded-use">Multi-threaded use</h2>
<p>Each dataset object has one transaction active at a time per thread.
A dataset object can be used by different threads, with independent transactions.</p>
<p>The usual idiom within multi-threaded applications is to have
one dataset, and so there is one transaction per thread.</p>
<p>Either:</p>
<pre><code> // Create a dataset and keep it globally.
static Dataset dataset = TDBFactory.createDataset(location) ;
</code></pre>
<p>Thread 1:</p>
<pre><code> dataset.begin(TxnType.WRITE) ;
try {
...
dataset.commit() ;
} finally { dataset.end() ; }
</code></pre>
<p>Thread 2:</p>
<pre><code> dataset.begin(TxnType.READ) ;
try {
...
} finally { dataset.end() ; }
</code></pre>
<p>It is possible (in TDB) to create different dataset objects to the same location.</p>
<p>Thread 1:</p>
<pre><code> Dataset dataset = TDBFactory.createDataset(location) ;
dataset.begin(TxnType.WRITE) ;
try {
...
dataset.commit() ;
} finally { dataset.end() ; }
</code></pre>
<p>Thread 2:</p>
<pre><code> Dataset dataset = TDBFactory.createDataset(location) ;
dataset.begin(TxnType.READ) ;
try {
...
} finally { dataset.end() ; }
</code></pre>
<p>Each thread has a separate <code>dataset</code> object; these safely share the
same storage and have independent transactions.</p>
<h2 id="multi-jvm">Multi JVM</h2>
<p>Multiple applications, running in multiple JVMs, using the same file
databases is not supported and has a high risk of data corruption. Once
corrupted a database cannot be repaired and must be rebuilt from the
original source data. Therefore there <strong>must</strong> be a single JVM
controlling the database directory and files. From 1.1.0 onwards TDB
includes automatic prevention against multi-JVM which prevents this
under most circumstances.</p>
<p>Use our <a href="../fuseki2/">Fuseki</a> component to provide a
database server for multiple applications. Fuseki supports
<a href="http://www.w3.org/TR/sparql11-query/">SPARQL Query</a>,
<a href="http://www.w3.org/TR/sparql11-update/">SPARQL Update</a> and the
<a href="http://www.w3.org/TR/sparql11-http-rdf-update/">SPARQL Graph Store protocol</a>.</p>
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