title: Partitioning in spark while reading from RDBMS via JDBC
body: <p>I am running spark in cluster mode and reading data from RDBMS via JDBC.</p>
  
  <p>As per Spark <a href="http://spark.apache.org/docs/latest/sql-programming-guide.html#jdbc-to-other-databases" rel="noreferrer">docs</a>, these partitioning parameters describe how to partition the table when reading in parallel from multiple workers:</p>
  
  <ul>
  <li><code>partitionColumn</code></li>
  <li><code>lowerBound</code></li>
  <li><code>upperBound</code></li>
  <li><code>numPartitions</code></li>
  </ul>
  
  <p><em>These are optional parameters.</em> </p>
  
  <p>What would happen if I don't specify these:</p>
  
  <ul>
  <li>Only 1 worker read the whole data?</li>
  <li>If it still reads parallelly, how does it partition data?</li>
  </ul>