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https://issues.apache.org/jira/browse/FLINK-7289?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16956749#comment-16956749
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shengjk1 edited comment on FLINK-7289 at 10/22/19 7:11 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.
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.
{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)n
.setBlockSize(4 * 32 * 1024));
}
@Override
public OptionsFactory configure(Configuration configuration) {
return this;
}
}
{code}
> 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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