[ 
https://issues.apache.org/jira/browse/SPARK-41340?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17641442#comment-17641442
 ] 

Adam Binford commented on SPARK-41340:
--------------------------------------

Got added twice

> RocksDB State Store WriteBatch doesn't cleanup native memory
> ------------------------------------------------------------
>
>                 Key: SPARK-41340
>                 URL: https://issues.apache.org/jira/browse/SPARK-41340
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL, Structured Streaming
>    Affects Versions: 3.3.1
>            Reporter: Adam Binford
>            Priority: Major
>
> The RocksDB state store uses a WriteBatch to hold updates that get written in 
> a single transaction to commit. Somewhat indirectly abort is called after a 
> successful task which calls writeBatch.clear(), but the data for a writeBatch 
> is stored in a std::string in the native code. Not sure why it's stored as a 
> string, but it is. [rocksdb/write_batch.h at main · facebook/rocksdb · 
> GitHub|https://github.com/facebook/rocksdb/blob/main/include/rocksdb/write_batch.h#L491]
> writeBatch.clear simply calls rep_.clear() and rep._resize() 
> ([rocksdb/write_batch.cc at main · facebook/rocksdb · 
> GitHub|https://github.com/facebook/rocksdb/blob/main/db/write_batch.cc#L246-L247]),
>  neither of which actually releases the memory built up by a std::string 
> instance. The only way to actually release this memory is to delete the 
> WriteBatch object itself.
> Currently, all memory taken by all write batches will remain until the 
> RocksDB state store instance is closed, which never happens during the normal 
> course of operation as all partitions remain loaded on an executor after a 
> task completes.



--
This message was sent by Atlassian Jira
(v8.20.10#820010)

---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

Reply via email to