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 You can find the JDBC-specific option and parameter documentation for reading tables via JDBC in
 https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-optionData Source Option in the version you use."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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       <img src="" class="logo" alt=""><h1>Create a SparkDataFrame representing the database table accessible via JDBC URL</h1>

       <div class="d-none name"><code>read.jdbc.Rd</code></div>
     </div>

     <div class="ref-description section level2">
     <p>Additional JDBC database connection properties can be set (...)
 You can find the JDBC-specific option and parameter documentation for reading tables via JDBC in
 <a href="https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option" class="external-link">https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option</a>Data Source Option in the version you use.</p>
     </div>

     <div class="section level2">
     <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">read.jdbc</span><span class="op">(</span></span>
 <span>  <span class="va">url</span>,</span>
 <span>  <span class="va">tableName</span>,</span>
 <span>  partitionColumn <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  lowerBound <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  upperBound <span class="op">=</span> <span class="cn">NULL</span>,</span>
 <span>  numPartitions <span class="op">=</span> <span class="fl">0L</span>,</span>
 <span>  predicates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>,</span>
 <span>  <span class="va">...</span></span>
 <span><span class="op">)</span></span></code></pre></div>
     </div>

     <div class="section level2">
     <h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
     <dl><dt>url</dt>
 <dd><p>JDBC database url of the form <code>jdbc:subprotocol:subname</code></p></dd>


 <dt>tableName</dt>
 <dd><p>the name of the table in the external database</p></dd>


 <dt>partitionColumn</dt>
 <dd><p>the name of a column of numeric, date, or timestamp type
 that will be used for partitioning.</p></dd>


 <dt>lowerBound</dt>
 <dd><p>the minimum value of <code>partitionColumn</code> used to decide partition stride</p></dd>


 <dt>upperBound</dt>
 <dd><p>the maximum value of <code>partitionColumn</code> used to decide partition stride</p></dd>


 <dt>numPartitions</dt>
 <dd><p>the number of partitions, This, along with <code>lowerBound</code> (inclusive),
 <code>upperBound</code> (exclusive), form partition strides for generated WHERE
 clause expressions used to split the column <code>partitionColumn</code> evenly.
 This defaults to SparkContext.defaultParallelism when unset.</p></dd>


 <dt>predicates</dt>
 <dd><p>a list of conditions in the where clause; each one defines one partition</p></dd>


 <dt>...</dt>
 <dd><p>additional JDBC database connection named properties.</p></dd>

 </dl></div>
     <div class="section level2">
     <h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>


 <p>SparkDataFrame</p>
     </div>
     <div class="section level2">
     <h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
     <p>Only one of partitionColumn or predicates should be set. Partitions of the table will be
 retrieved in parallel based on the <code>numPartitions</code> or by the predicates.</p>
 <p>Don't create too many partitions in parallel on a large cluster; otherwise Spark might crash
 your external database systems.</p>
     </div>
     <div class="section level2">
     <h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
     <p>read.jdbc since 2.0.0</p>
     </div>

     <div class="section level2">
     <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
     <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
 <span class="r-in"><span><span class="fu"><a href="sparkR.session.html">sparkR.session</a></span><span class="op">(</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">jdbcUrl</span> <span class="op">&lt;-</span> <span class="st">"jdbc:mysql://localhost:3306/databasename"</span></span></span>
 <span class="r-in"><span><span class="va">df</span> <span class="op">&lt;-</span> <span class="fu">read.jdbc</span><span class="op">(</span><span class="va">jdbcUrl</span>, <span class="st">"table"</span>, predicates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"field&lt;=123"</span><span class="op">)</span>, user <span class="op">=</span> <span class="st">"username"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="va">df2</span> <span class="op">&lt;-</span> <span class="fu">read.jdbc</span><span class="op">(</span><span class="va">jdbcUrl</span>, <span class="st">"table2"</span>, partitionColumn <span class="op">=</span> <span class="st">"index"</span>, lowerBound <span class="op">=</span> <span class="fl">0</span>,</span></span>
 <span class="r-in"><span>                 upperBound <span class="op">=</span> <span class="fl">10000</span>, user <span class="op">=</span> <span class="st">"username"</span>, password <span class="op">=</span> <span class="st">"password"</span><span class="op">)</span></span></span>
 <span class="r-in"><span><span class="op">}</span></span></span>
 </code></pre></div>
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	You can find the JDBC-specific option and parameter documentation for reading tables via JDBC in
	https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-optionData Source Option in the version you use."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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	<img src="" class="logo" alt=""><h1>Create a SparkDataFrame representing the database table accessible via JDBC URL</h1>

	<div class="d-none name"><code>read.jdbc.Rd</code></div>
	</div>

	<div class="ref-description section level2">
	<p>Additional JDBC database connection properties can be set (...)
	You can find the JDBC-specific option and parameter documentation for reading tables via JDBC in
	<a href="https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option" class="external-link">https://spark.apache.org/docs/latest/sql-data-sources-jdbc.html#data-source-option</a>Data Source Option in the version you use.</p>
	</div>

	<div class="section level2">
	<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
	<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">read.jdbc</span><span class="op">(</span></span>
	<span> <span class="va">url</span>,</span>
	<span> <span class="va">tableName</span>,</span>
	<span> partitionColumn <span class="op">=</span> <span class="cn">NULL</span>,</span>
	<span> lowerBound <span class="op">=</span> <span class="cn">NULL</span>,</span>
	<span> upperBound <span class="op">=</span> <span class="cn">NULL</span>,</span>
	<span> numPartitions <span class="op">=</span> <span class="fl">0L</span>,</span>
	<span> predicates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="op">)</span>,</span>
	<span> <span class="va">...</span></span>
	<span><span class="op">)</span></span></code></pre></div>
	</div>

	<div class="section level2">
	<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
	<dl><dt>url</dt>
	<dd><p>JDBC database url of the form <code>jdbc:subprotocol:subname</code></p></dd>


	<dt>tableName</dt>
	<dd><p>the name of the table in the external database</p></dd>


	<dt>partitionColumn</dt>
	<dd><p>the name of a column of numeric, date, or timestamp type
	that will be used for partitioning.</p></dd>


	<dt>lowerBound</dt>
	<dd><p>the minimum value of <code>partitionColumn</code> used to decide partition stride</p></dd>


	<dt>upperBound</dt>
	<dd><p>the maximum value of <code>partitionColumn</code> used to decide partition stride</p></dd>


	<dt>numPartitions</dt>
	<dd><p>the number of partitions, This, along with <code>lowerBound</code> (inclusive),
	<code>upperBound</code> (exclusive), form partition strides for generated WHERE
	clause expressions used to split the column <code>partitionColumn</code> evenly.
	This defaults to SparkContext.defaultParallelism when unset.</p></dd>


	<dt>predicates</dt>
	<dd><p>a list of conditions in the where clause; each one defines one partition</p></dd>


	<dt>...</dt>
	<dd><p>additional JDBC database connection named properties.</p></dd>

	</dl></div>
	<div class="section level2">
	<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>


	<p>SparkDataFrame</p>
	</div>
	<div class="section level2">
	<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
	<p>Only one of partitionColumn or predicates should be set. Partitions of the table will be
	retrieved in parallel based on the <code>numPartitions</code> or by the predicates.</p>
	<p>Don't create too many partitions in parallel on a large cluster; otherwise Spark might crash
	your external database systems.</p>
	</div>
	<div class="section level2">
	<h2 id="note">Note<a class="anchor" aria-label="anchor" href="#note"></a></h2>
	<p>read.jdbc since 2.0.0</p>
	</div>

	<div class="section level2">
	<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
	<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="cn">FALSE</span><span class="op">)</span> <span class="op">{</span></span></span>
	<span class="r-in"><span><span class="fu"><a href="sparkR.session.html">sparkR.session</a></span><span class="op">(</span><span class="op">)</span></span></span>
	<span class="r-in"><span><span class="va">jdbcUrl</span> <span class="op"><-</span> <span class="st">"jdbc:mysql://localhost:3306/databasename"</span></span></span>
	<span class="r-in"><span><span class="va">df</span> <span class="op"><-</span> <span class="fu">read.jdbc</span><span class="op">(</span><span class="va">jdbcUrl</span>, <span class="st">"table"</span>, predicates <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span><span class="st">"field<=123"</span><span class="op">)</span>, user <span class="op">=</span> <span class="st">"username"</span><span class="op">)</span></span></span>
	<span class="r-in"><span><span class="va">df2</span> <span class="op"><-</span> <span class="fu">read.jdbc</span><span class="op">(</span><span class="va">jdbcUrl</span>, <span class="st">"table2"</span>, partitionColumn <span class="op">=</span> <span class="st">"index"</span>, lowerBound <span class="op">=</span> <span class="fl">0</span>,</span></span>
	<span class="r-in"><span> upperBound <span class="op">=</span> <span class="fl">10000</span>, user <span class="op">=</span> <span class="st">"username"</span>, password <span class="op">=</span> <span class="st">"password"</span><span class="op">)</span></span></span>
	<span class="r-in"><span><span class="op">}</span></span></span>
	</code></pre></div>
	</div>
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