[jira] [Comment Edited] (FLINK-7289) Memory allocation of RocksDB can be problematic in container environments

["shengjk1 (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-7289?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16956749#comment-16956749 ] 

shengjk1 edited comment on FLINK-7289 at 10/22/19 7:09 AM:
-----------------------------------------------------------

 I also rebuild flink and use writeBufferManager. For one specific job I'm working on, I went from a OOM kill every 5-7 hours to at least 20 hours of no OOM events . But finally it still OOM . So I think maybe we also need other parameters which easy to use to solve it.
{code:java}

class BackendOptions implements ConfigurableOptionsFactory {
   //
   private static final WriteBufferManager writeBufferManager = new WriteBufferManager(1 << 30, new LRUCache(1 << 18));
   
   @Override
   public DBOptions createDBOptions(DBOptions currentOptions) {
      return currentOptions
            .setMaxBackgroundJobs(4)
            .setUseFsync(false)
            .setMaxBackgroundFlushes(3)
            .setWriteBufferManager(writeBufferManager);
   }
   
   @Override
   public ColumnFamilyOptions createColumnOptions(ColumnFamilyOptions currentOptions) {
      return currentOptions
            .setLevelCompactionDynamicLevelBytes(true)
            .setMinWriteBufferNumberToMerge(2)
            .setMaxWriteBufferNumber(5)
            
            .setOptimizeFiltersForHits(true)
            .setMaxWriteBufferNumberToMaintain(3)
            .setTableFormatConfig(
                  new BlockBasedTableConfig()
                        .setCacheIndexAndFilterBlocks(true)
                        .setCacheIndexAndFilterBlocksWithHighPriority(true)
                        .setBlockCacheSize(256 * 1024 * 1024)
//                      increases read amplification but decreases memory useage and space amplification
                        .setBlockSize(4 * 32 * 1024))
            ;
   }
   
   @Override
   public OptionsFactory configure(Configuration configuration) {
      return this;
   }
}
{code}
 


was (Author: shengjk1):
 I also rebuild flink and use writeBufferManager. For one specific job I'm working on, I went from a OOM kill every 5-7 hours to at least 20 hours of no OOM events . But finally it still OOM . So I think maybe we also need other parameters which easy to use to solve it.
class BackendOptions implements ConfigurableOptionsFactory \{
   //
   private static final WriteBufferManager writeBufferManager = new WriteBufferManager(1 << 30, new LRUCache(1 << 18));
   
   @Override
   public DBOptions createDBOptions(DBOptions currentOptions) {
      return currentOptions
            .setMaxBackgroundJobs(4)
            .setUseFsync(false)
            .setMaxBackgroundFlushes(3)
            .setWriteBufferManager(writeBufferManager);
   }
   
   @Override
   public ColumnFamilyOptions createColumnOptions(ColumnFamilyOptions currentOptions) \{
      return currentOptions
            .setLevelCompactionDynamicLevelBytes(true)
            .setMinWriteBufferNumberToMerge(2)
            .setMaxWriteBufferNumber(5)
            
            .setOptimizeFiltersForHits(true)
            .setMaxWriteBufferNumberToMaintain(3)
            .setTableFormatConfig(
                  new BlockBasedTableConfig()
                        .setCacheIndexAndFilterBlocks(true)
                        .setCacheIndexAndFilterBlocksWithHighPriority(true)
                        .setBlockCacheSize(256 * 1024 * 1024)
                        .setBlockSize(4 * 32 * 1024))
            ;
   }
   
   @Override
   public OptionsFactory configure(Configuration configuration) \{
      return this;
   }
}

> Memory allocation of RocksDB can be problematic in container environments
> -------------------------------------------------------------------------
>
>                 Key: FLINK-7289
>                 URL: https://issues.apache.org/jira/browse/FLINK-7289
>             Project: Flink
>          Issue Type: Improvement
>          Components: Runtime / State Backends
>    Affects Versions: 1.2.0, 1.3.0, 1.4.0, 1.7.2, 1.8.2, 1.9.0
>            Reporter: Stefan Richter
>            Priority: Major
>             Fix For: 1.10.0
>
>         Attachments: completeRocksdbConfig.txt
>
>
> Flink's RocksDB based state backend allocates native memory. The amount of allocated memory by RocksDB is not under the control of Flink or the JVM and can (theoretically) grow without limits.
> In container environments, this can be problematic because the process can exceed the memory budget of the container, and the process will get killed. Currently, there is no other option than trusting RocksDB to be well behaved and to follow its memory configurations. However, limiting RocksDB's memory usage is not as easy as setting a single limit parameter. The memory limit is determined by an interplay of several configuration parameters, which is almost impossible to get right for users. Even worse, multiple RocksDB instances can run inside the same process and make reasoning about the configuration also dependent on the Flink job.
> Some information about the memory management in RocksDB can be found here:
> https://github.com/facebook/rocksdb/wiki/Memory-usage-in-RocksDB
> https://github.com/facebook/rocksdb/wiki/RocksDB-Tuning-Guide
> We should try to figure out ways to help users in one or more of the following ways:
> - Some way to autotune or calculate the RocksDB configuration.
> - Conservative default values.
> - Additional documentation.



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