spark-instrumented-optimizer/core
Josh Rosen 6c2d894a2f [SPARK-13921] Store serialized blocks as multiple chunks in MemoryStore
This patch modifies the BlockManager, MemoryStore, and several other storage components so that serialized cached blocks are stored as multiple small chunks rather than as a single contiguous ByteBuffer.

This change will help to improve the efficiency of memory allocation and the accuracy of memory accounting when serializing blocks. Our current serialization code uses a ByteBufferOutputStream, which doubles and re-allocates its backing byte array; this increases the peak memory requirements during serialization (since we need to hold extra memory while expanding the array). In addition, we currently don't account for the extra wasted space at the end of the ByteBuffer's backing array, so a 129 megabyte serialized block may actually consume 256 megabytes of memory. After switching to storing blocks in multiple chunks, we'll be able to efficiently trim the backing buffers so that no space is wasted.

This change is also a prerequisite to being able to cache blocks which are larger than 2GB (although full support for that depends on several other changes which have not bee implemented yet).

Author: Josh Rosen <joshrosen@databricks.com>

Closes #11748 from JoshRosen/chunked-block-serialization.
2016-03-17 20:00:56 -07:00
..
src [SPARK-13921] Store serialized blocks as multiple chunks in MemoryStore 2016-03-17 20:00:56 -07:00
pom.xml [SPARK-13848][SPARK-5185] Update to Py4J 0.9.2 in order to fix classloading issue 2016-03-14 12:22:02 -07:00