Hi Madhu, I don't think you can reuse the persistent RDD the next time you run the program, because the folder for RDD materialization will be changed, also Spark will lose the information of how to retrieve the previous persisted RDD.
AFAIK Spark has fault tolerance mechanism, node failure will lead to recomputation of the affected partitions. Thanks Jerry From: Jahagirdar, Madhu [mailto:madhu.jahagir...@philips.com] Sent: Tuesday, July 08, 2014 10:16 AM To: user@spark.apache.org Subject: Spark RDD Disk Persistance Should i use Disk based Persistance for RDD's and if the machine goes down during the program execution, next time when i rerun the program would the data be intact and not lost ? Regards, Madhu Jahagirdar ________________________________ The information contained in this message may be confidential and legally protected under applicable law. The message is intended solely for the addressee(s). If you are not the intended recipient, you are hereby notified that any use, forwarding, dissemination, or reproduction of this message is strictly prohibited and may be unlawful. If you are not the intended recipient, please contact the sender by return e-mail and destroy all copies of the original message.
