Storing RDD to disk is nothing but storing JVM byte code to disk (in case of Java or Scala). am I correct?
On Tue, Aug 23, 2016 12:55 PM, Nirav nira...@gmail.com wrote: You can store either in serialized form(butter array) or just save it in a string format like tsv or csv. There are different RDD save apis for that. Sent from my iPhone On Aug 23, 2016, at 12:26 PM, kant kodali < kanth...@gmail.com > wrote: ok now that I understand RDD can be stored to the disk. My last question on this topic would be this. Storing RDD to disk is nothing but storing JVM byte code to disk (in case of Java or Scala). am I correct? On Tue, Aug 23, 2016 12:19 PM, RK Aduri rkad...@collectivei.com wrote: On an other note, if you have a streaming app, you checkpoint the RDDs so that they can be accessed in case of a failure. And yes, RDDs are persisted to DISK. You can access spark’s UI and see it listed under Storage tab. If RDDs are persisted in memory, you avoid any disk I/Os so that any lookups will be cheap. RDDs are reconstructed based on a graph (DAG - available in Spark UI ) On Aug 23, 2016, at 12:10 PM, < srikanth.je...@gmail.com > < srikanth.je...@gmail.com > wrote: RAM or Virtual memory is finite, so data size needs to be considered before persist. Please see below documentation when to choose the persistency level. http://spark.apache.org/docs/latest/programming-guide.html#which-storage-level-to-choose Thanks, Sreekanth Jella From: kant kodali Sent: Tuesday, August 23, 2016 2:42 PM To: srikanth.je...@gmail.com Cc: user@spark.apache.org Subject: Re: Are RDD's ever persisted to disk? so when do we ever need to persist RDD on disk? given that we don't need to worry about RAM(memory) as virtual memory will just push pages to the disk when memory becomes scarce. On Tue, Aug 23, 2016 11:23 AM, srikanth.je...@gmail.com wrote:Hi Kant Kodali, Based on the input parameter to persist() method either it will be cached on memory or persisted to disk. In case of failures Spark will reconstruct the RDD on a different executor based on the DAG. That is how failures are handled. Spark Core does not replicate the RDDs as they can be reconstructed from the source (let’s say HDFS, Hive or S3 etc.) but not from memory (which is lost already). Thanks, Sreekanth Jella From: kant kodali Sent: Tuesday, August 23, 2016 2:12 PM To: user@spark.apache.org Subject: Are RDD's ever persisted to disk? I am new to spark and I keep hearing that RDD's can be persisted to memory or disk after each checkpoint. I wonder why RDD's are persisted in memory? In case of node failure how would you access memory to reconstruct the RDD? persisting to disk make sense because its like persisting to a Network file system (in case of HDFS) where a each block will have multiple copies across nodes so if a node goes down RDD's can still be reconstructed by the reading the required block from other nodes and recomputing it but my biggest question is Are RDD's ever persisted to disk? Collective[i] dramatically improves sales and marketing performance using technology, applications and a revolutionary network designed to provide next generation analytics and decision-support directly to business users. Our goal is to maximize human potential and minimize mistakes. In most cases, the results are astounding. We cannot, however, stop emails from sometimes being sent to the wrong person. If you are not the intended recipient, please notify us by replying to this email's sender and deleting it (and any attachments) permanently from your system. If you are, please respect the confidentiality of this communication's contents.
