Ultimate access to all questions.
Upgrade Now 🚀
Sign in to unlock AI tutor
What are the key similarities and differences between the MEMORY_ONLY and MEMORY_AND_DISK storage levels in Spark?
MEMORY_ONLY
MEMORY_AND_DISK
A
The MEMORY_ONLY storage level will store as much data as possible in memory and will store any data that does on fit in memory on disk and read it as it's called. The MEMORY_AND_DISK storage level will store as much data as possible in memory and will recompute any data that does not fit in memory as it’s called.
B
The MEMORY_ONLY storage level will store as much data as possible in memory on two cluster nodes and will recompute any data that does not fit in memory as it’s called. The MEMORY_AND_DISK storage level will store as much data as possible in memory on two cluster nodes and will store any data that does on fit in memory on disk and read it as it's called.
C
The MEMORY_ONLY storage level will store as much data as possible in memory on two cluster nodes and will store any data that does on fit in memory on disk and read it as it's called. The MEMORY_AND_DISK storage level will store as much data as possible in memory on two cluster nodes and will recompute any data that does not fit in memory as it's called.
D
The MEMORY_ONLY storage level will store as much data as possible in memory and will recompute any data that does not fit in memory as it's called. The MEMORY_AND_DISK storage level will store as much data as possible in memory and will store any data that does on fit in memory on disk and read it as it's called.
E
The MEMORY_ONLY storage level will store as much data as possible in memory and will recompute any data that does not fit in memory as it’s called. The MEMORY_AND_DISK storage level will store half of the data in memory and store half of the memory on disk. This provides quick preview and better logical plan design.
