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Posted to issues@spark.apache.org by "Nan Zhu (Jira)" <ji...@apache.org> on 2025/12/04 21:08:00 UTC
[jira] [Commented] (SPARK-54596) Burst-aware memoryOverhead Allocation Algorithm for Spark@K8S
[ https://issues.apache.org/jira/browse/SPARK-54596?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=18042895#comment-18042895 ]
Nan Zhu commented on SPARK-54596:
---------------------------------
SPIP coming soon
> Burst-aware memoryOverhead Allocation Algorithm for Spark@K8S
> -------------------------------------------------------------
>
> Key: SPARK-54596
> URL: https://issues.apache.org/jira/browse/SPARK-54596
> Project: Spark
> Issue Type: Improvement
> Components: Kubernetes, Spark Core
> Affects Versions: 4.2
> Reporter: Nan Zhu
> Priority: Major
>
> memoryOverhead is one of the most significant memory consumers for Spark workloads. Users tend to book a big chunk of such memory space to avoid triggering OOMKiller in the cluster environment.
> However, the usage of pattern of memoryOverhead space, such as se/deser, compress/decompress, direct memory, etc. , is usually bursty. As a result, users have to book the peak usage of memoryOverhead to ensure the reliability of their jobs while leaving a big chunk of this space unused in the majority of the job lifecycle.
> To resolve this problem in the context of Spark@K8S, we implemented the algorithm presented in the paper "Towards Resource Efficiency: Practical Insights into Large-Scale Spark Workloads at ByteDance" from ByteDance team ([https://www.vldb.org/pvldb/vol17/p3759-shi.pdf)] . We introduce a configurable parameter to split the user requested memoryOverhead space into two parts, guaranteed/shared. The guaranteed part is dedicated to a pod started by a spark job and shared part is used by multiple pods in a time-sharing fashion. Being specific to the K8S environment, the memory request of a pod will be user-requested on-heap space + guaranteed memoryOverhead and the memory limit will be user-requested on-heap space + guaranteed memoryOverhead + shared memoryOverhead .
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