可以尝试的解决办法： - 调大 JM 内存 （如 Shawn Huang 所说） - 调整快照期间批读的大小，以降低 state 大小从而减轻 checkpiont 过程中 JM 内存压力
Best, Zhongqiang Gong wyk <wyk118...@163.com> 于2024年4月9日周二 16:56写道： > > 是的,分片比较大,有一万七千多个分片 > > jm内存目前是2g,我调整到4g之后还是会有这么问题,我在想如果我一直调整jm内存,后面增量的时候内存会有所浪费,在flink官网上找到了flink堆内存的相关参数,但是对这个不太了解,不知道具体该怎么调试合适,麻烦帮忙看一下如下图这些参数调整那个合适呢? > > flink官网地址为: > https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup_jobmanager/ > > > > > Component Configuration options Description > JVM Heap > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup_jobmanager/#configure-jvm-heap> > jobmanager.memory.heap.size > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-heap-size> > *JVM > Heap* memory size for job manager. > Off-heap Memory > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup_jobmanager/#configure-off-heap-memory> > jobmanager.memory.off-heap.size > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-off-heap-size> > *Off-heap* memory size for job manager. This option covers all off-heap > memory usage including direct and native memory allocation. > JVM metaspace > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup/#jvm-parameters> > jobmanager.memory.jvm-metaspace.size > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-jvm-metaspace-size> > Metaspace > size of the Flink JVM process > JVM Overhead jobmanager.memory.jvm-overhead.min > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-jvm-overhead-min> > jobmanager.memory.jvm-overhead.max > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-jvm-overhead-max> > jobmanager.memory.jvm-overhead.fraction > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/config/#jobmanager-memory-jvm-overhead-fraction> > Native > memory reserved for other JVM overhead: e.g. thread stacks, code cache, > garbage collection space etc, it is a capped fractionated component > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup/#capped-fractionated-components> > of > the total process memory > <https://nightlies.apache.org/flink/flink-docs-release-1.19/docs/deployment/memory/mem_setup/#configure-total-memory> > > > > > 在 2024-04-09 11:28:57，"Shawn Huang" <hx0...@gmail.com> 写道： > > > 从报错信息看，是由于JM的堆内存不够，可以尝试把JM内存调大，一种可能的原因是mysql表全量阶段分片较多，导致SourceEnumerator状态较大。 > > Best, > Shawn Huang > > > wyk <wyk118...@163.com> 于2024年4月8日周一 17:46写道： > >> >> >> 开发者们好: >> flink版本1.14.5 >> flink-cdc版本 2.2.0 >> >> 在使用flink-cdc-mysql采集全量的时候,全量阶段会做checkpoint,但是checkpoint的时候会出现oom问题,这个有什么办法吗? >> 具体报错如附件文本以及下图所示: >> >> >>
