Apache Spark RDD persistence only when exception is thrown
<p>I was considering caching one of my RDDs that took longer to process only if an exception was thrown and the job was killed. If I run the job again, I'd like it to continue where it failed, avoiding the processing of that RDD again.</p>

<p>Does it make sense? Would the same job start a different Spark context not being able to locate that cached RDD?</p>

<p>Thanks!</p>