What are the different levels of persistence in Spark?Databricks interview questions for experienced/Databricks Interview Questions and Answers for Freshers & Experienced

What are the different levels of persistence in Spark?

DISK_ONLY - Stores the RDD partitions only on the disk

MEMORY_ONLY_SER - Stores the RDD as serialized Java objects with a one-byte array per partition

MEMORY_ONLY - Stores the RDD as deserialized Java objects in the JVM. If the RDD is not able to fit in the memory available, some partitions won’t be cached

OFF_HEAP - Works like MEMORY_ONLY_SER but stores the data in off-heap memory

MEMORY_AND_DISK - Stores RDD as deserialized Java objects in the JVM. In case the RDD is not able to fit in the memory, additional partitions are stored on the disk

MEMORY_AND_DISK_SER - Identical to MEMORY_ONLY_SER with the exception of storing partitions not able to fit in the memory to the disk

Posted Date:- 2021-09-25 06:12:43

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