You are viewing a plain text version of this content. The canonical link for it is here.
Posted to issues@flink.apache.org by "Yun Tang (Jira)" <ji...@apache.org> on 2022/05/20 06:28:00 UTC

[jira] [Closed] (FLINK-27504) State compaction not happening with sliding window and incremental RocksDB backend

     [ https://issues.apache.org/jira/browse/FLINK-27504?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Yun Tang closed FLINK-27504.
----------------------------
    Resolution: Information Provided

> State compaction not happening with sliding window and incremental RocksDB backend
> ----------------------------------------------------------------------------------
>
>                 Key: FLINK-27504
>                 URL: https://issues.apache.org/jira/browse/FLINK-27504
>             Project: Flink
>          Issue Type: Bug
>          Components: Runtime / State Backends
>    Affects Versions: 1.14.4
>         Environment: Local Flink cluster on Arch Linux.
>            Reporter: Alexis Sarda-Espinosa
>            Priority: Major
>         Attachments: duration_trend_52ca77c.png, duration_trend_67c76bb.png, duration_trend_c5dd5d2.png, image-2022-05-06-10-34-35-007.png, size_growth_52ca77c.png, size_growth_67c76bb.png, size_growth_c5dd5d2.png
>
>
> Hello,
> I'm trying to estimate an upper bound for RocksDB's state size in my application. For that purpose, I have created a small job with faster timings whose code you can find on GitHub: [https://github.com/asardaes/flink-rocksdb-ttl-test]. You can see some of the results there, but I summarize here as well:
>  * Approximately 20 events per second, 10 unique keys for partitioning are pre-specified.
>  * Sliding window of 11 seconds with a 1-second slide.
>  * Allowed lateness of 11 seconds.
>  * State TTL configured to 1 minute and compaction after 1000 entries.
>  * Both window-specific and window-global state used.
>  * Checkpoints every 2 seconds.
>  * Parallelism of 4 in stateful tasks.
> The goal is to let the job run and analyze state compaction behavior with RocksDB. I should note that global state is cleaned manually inside the functions, TTL for those is in case some keys are no longer seen in the actual production environment.
> I have been running the job on a local cluster (outside IDE), the configuration YAML is also available in the repository. After running for approximately 1.6 days, state size is currently 2.3 GiB (see attachments). I understand state can retain expired data for a while, but since TTL is 1 minute, this seems excessive to me.



--
This message was sent by Atlassian Jira
(v8.20.7#820007)