# Parallel processing-OOM killer due to high memory

**URL:** <https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034>\
**Category:** Uncategorized\
**Created:** [October 26, 2022, 8:17pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034 "2022-10-26T20:17:24Z")\
**Posts on this page:** 6\
**Page:** 1

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**Author:** ![mlguy89](https://avatars.discourse-cdn.com/v4/letter/m/a9a28c/32.png) [@mlguy89](https://discuss.ray.io/u/mlguy89)\
**Post date:** [October 26, 2022, 8:17pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/1 "2022-10-26T20:17:24Z")

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I am using ray to run two functions in parallel,i get error message"Worker unexpectedly exits with a connection error code 2"The process killed by SGKILL by OOM killer due to high memory

check python-core-worker-\*.log. , where do i find this log file ? i am working in a anaconda environment

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**Author:** ![cade](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/cade/32/3837_2.png) [@cade](https://discuss.ray.io/u/cade)\
**Post date:** [October 31, 2022, 7:46pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/2 "2022-10-31T19:46:11Z")

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What version of Ray are you running? Ray 2.0 has `ray logs` which shows all the files available, including the `python-core-worker-*.log`.

@Clarence_Ng knows more about dealing with OOMs, is there anything else to be done?

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**Author:** ![cade](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/cade/32/3837_2.png) [@cade](https://discuss.ray.io/u/cade)\
**Post date:** [October 31, 2022, 7:49pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/3 "2022-10-31T19:49:31Z")

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Also, it’s expected that Ray will kill a task that is consuming too much heap memory. Otherwise, it will cause the machine to crash or experience severe performance degradation. What is the workload you are running? Do you expect it to consume all heap memory available?

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**Author:** ![ClarenceNg](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/clarenceng/32/3108_2.png) [@ClarenceNg](https://discuss.ray.io/u/ClarenceNg)\
**Post date:** [October 31, 2022, 9:21pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/4 "2022-10-31T21:21:50Z")

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@mlguy89 thanks for filing the report. Typically the worker crash also contains stacktrace of the error - does it have anything interesting / useful ?

The log file by default lives in /tmp/ray/session\_latest/logs for the latest cluster, let us know if the documentation isn’t clear or where you think needs improvement : [Logging — Ray 2.0.1](https://docs.ray.io/en/latest/ray-observability/ray-logging.html#logging-directory-structure)

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**Author:** ![ClarenceNg](https://sea2.discourse-cdn.com/flex020/user_avatar/discuss.ray.io/clarenceng/32/3108_2.png) [@ClarenceNg](https://discuss.ray.io/u/ClarenceNg)\
**Post date:** [November 3, 2022, 5:35am UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/5 "2022-11-03T05:35:35Z")

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@mlguy89 did you get to try finding the logs?

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**Author:** ![mlguy89](https://avatars.discourse-cdn.com/v4/letter/m/a9a28c/32.png) [@mlguy89](https://discuss.ray.io/u/mlguy89)\
**Post date:** [November 4, 2022, 6:29pm UTC](https://discuss.ray.io/t/parallel-processing-oom-killer-due-to-high-memory/8034/6 "2022-11-04T18:29:14Z")

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After reducing one feature don’t face any memory issue