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https://issues.apache.org/jira/browse/SPARK-13183?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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dylanzhou updated SPARK-13183:
------------------------------
Description:
When I used sparkstreamimg and sparksql, i cache the table,found that old gen
increases very fast and full GC is very frequent, running for a period of time
will be out of memory, after analysis of heap memory, found that there are a
large number of org.apache.spark.sql.columnar.ColumnBuilder[38] @ 0xd022a0b8,
takes up 90% of the space, look at the source is HeapByteBuffer occupy, don't
know why these objects are not released, had been waiting for GC to recycle;if
i donot use cache table, there will be no this problem, but I need to
repeatedly query this table do
was:
When I used sparkstreamimg and sparksql, found that old gen increases very fast
and full GC is very frequent, running for a period of time will be out of
memory, after analysis of heap memory, found that there are a large number of
org.apache.spark.sql.columnar.ColumnBuilder[38] @ 0xd022a0b8, takes up 90% of
the space, look at the source is HeapByteBuffer occupy, don't know why these
objects are not released, had been waiting for GC to recycle
Component/s: SQL
> Bytebuffers occupy a large amount of heap memory
> ------------------------------------------------
>
> Key: SPARK-13183
> URL: https://issues.apache.org/jira/browse/SPARK-13183
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.4.1
> Reporter: dylanzhou
>
> When I used sparkstreamimg and sparksql, i cache the table,found that old gen
> increases very fast and full GC is very frequent, running for a period of
> time will be out of memory, after analysis of heap memory, found that there
> are a large number of org.apache.spark.sql.columnar.ColumnBuilder[38] @
> 0xd022a0b8, takes up 90% of the space, look at the source is HeapByteBuffer
> occupy, don't know why these objects are not released, had been waiting for
> GC to recycle;if i donot use cache table, there will be no this problem, but
> I need to repeatedly query this table do
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