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https://issues.apache.org/jira/browse/FLINK-7289?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16107165#comment-16107165
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Vinay commented on FLINK-7289:
------------------------------

You are right about this "the memory pages will be replaced eventually when 
memory is requested or they will be dropped by cache replacement when there are 
new reads/writes to other files".

>From what I have observed from JVisualVm this is not happening, the memory 
>keeps on increasing when you run the job second time eventually resulting in 
>the TM to be killed.

Also to be clear the above case will occur when you cancel the job from Flink 
UI and rerun the job.

> 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: State Backends, Checkpointing
>    Affects Versions: 1.2.0, 1.3.0, 1.4.0
>            Reporter: Stefan Richter
>
> 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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