Hi All, I know that Spark has integration with cassandra DB. Can the RDD be persisted into DB, be read back into the same state, on server boot ? If yes, are there any examples which would demonstrate how it's done ?
We have a requirement, where we are currently saving a snapshot of many rows into MS SQL Server DB, this snapshot is a readonly snapshot, since we are migrating our application to Spark, we were thinking of migrating this snapshot into Spark too, so that it can be referred whenever required and data can be processed within it. But to do so, i'm assuming we would have to first create this RDD at runtime which represents this snapshot, and then persist it in Spark ( either Filesystem or DB ). The reason DB looks more reasonable is because we don't have a HDFS ecosystem, and in that case would have to manage creation, archival & other aspects of persistance ourselves. Any thoughts in this regard will be really helpful. Thanks in Advance. Nitin -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Saving-RDD-into-DB-then-Reading-back-from-DB-tp18821.html Sent from the Apache Spark User List mailing list archive at Nabble.com. --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
