[jira] [Resolved] (KAFKA-6603) Kafka streams off heap memory usage does not match expected values from configuration

["A. Sophie Blee-Goldman (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/KAFKA-6603?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

A. Sophie Blee-Goldman resolved KAFKA-6603.
-------------------------------------------
    Resolution: Fixed

> Kafka streams off heap memory usage does not match expected values from configuration
> -------------------------------------------------------------------------------------
>
>                 Key: KAFKA-6603
>                 URL: https://issues.apache.org/jira/browse/KAFKA-6603
>             Project: Kafka
>          Issue Type: Bug
>          Components: streams
>    Affects Versions: 1.0.0
>            Reporter: Igor Calabria
>            Priority: Minor
>
> Hi, I have a simple aggregation pipeline that's backed by the default state store(rocksdb). The pipeline works fine except that off heap the memory usage is way higher than expected. Following the [documention|https://docs.confluent.io/current/streams/developer-guide/config-streams.html#streams-developer-guide-rocksdb-config] has some effect(memory usage is reduced) but the values don't match at all. 
> The java process is set to run with just `-Xmx300m -Xms300m`  and rocksdb config looks like this
> {code:java}
> tableConfig.setCacheIndexAndFilterBlocks(true);
> tableConfig.setBlockCacheSize(1048576); //1MB
> tableConfig.setBlockSize(16 * 1024); // 16KB
> options.setTableFormatConfig(tableConfig);
> options.setMaxWriteBufferNumber(2);
> options.setWriteBufferSize(8 * 1024); // 8KB{code}
> To estimate memory usage, I'm using this formula  
> {noformat}
> (block_cache_size + write_buffer_size * write_buffer_number) * segments * partitions{noformat}
> Since my topic has 25 partitions with 3 segments each(it's a windowed store), off heap memory usage should be about 76MB. What I'm seeing in production is upwards of 300MB, even taking in consideration  extra overhead from rocksdb compaction threads, this seems a bit high (especially when the disk usage for all files is just 1GB) 



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