Why does Spillable class of spark only use onHeap memory?
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I read spark source code of master branch(2018/11), which will published in spark 2.5 version.
I don't understand the reason why Spillable class of spark does only use onHeap memory? I mean why it doesn't do it like ShuffleExternalSort, which can use offHeap after user enable spark.memory.offHeap.enabled and set spark.memory.offHeap.size available.
What will I need to pay attention if I change the code of Spillable class to use OffHeap or OnHeap which depends user's configuration like ShuffleExternalSort.
apache-spark
edited Nov 12 at 1:52
Cœur
17.3k9102142
asked Nov 12 at 1:43
yeshang
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I read spark source code of master branch(2018/11), which will published in spark 2.5 version.
I don't understand the reason why Spillable class of spark does only use onHeap memory? I mean why it doesn't do it like ShuffleExternalSort, which can use offHeap after user enable spark.memory.offHeap.enabled and set spark.memory.offHeap.size available.
What will I need to pay attention if I change the code of Spillable class to use OffHeap or OnHeap which depends user's configuration like ShuffleExternalSort.
apache-spark
edited Nov 12 at 1:52
Cœur
17.3k9102142
asked Nov 12 at 1:43
yeshang
1
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This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45
add a comment |
up vote
0
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up vote
0
down vote
favorite
I read spark source code of master branch(2018/11), which will published in spark 2.5 version.
I don't understand the reason why Spillable class of spark does only use onHeap memory? I mean why it doesn't do it like ShuffleExternalSort, which can use offHeap after user enable spark.memory.offHeap.enabled and set spark.memory.offHeap.size available.
What will I need to pay attention if I change the code of Spillable class to use OffHeap or OnHeap which depends user's configuration like ShuffleExternalSort.
apache-spark
edited Nov 12 at 1:52
Cœur
17.3k9102142
asked Nov 12 at 1:43
yeshang
1
I read spark source code of master branch(2018/11), which will published in spark 2.5 version.
I don't understand the reason why Spillable class of spark does only use onHeap memory? I mean why it doesn't do it like ShuffleExternalSort, which can use offHeap after user enable spark.memory.offHeap.enabled and set spark.memory.offHeap.size available.
What will I need to pay attention if I change the code of Spillable class to use OffHeap or OnHeap which depends user's configuration like ShuffleExternalSort.
apache-spark
apache-spark
edited Nov 12 at 1:52
Cœur
17.3k9102142
asked Nov 12 at 1:43
yeshang
1
edited Nov 12 at 1:52
Cœur
17.3k9102142
asked Nov 12 at 1:43
yeshang
1
edited Nov 12 at 1:52
Cœur
17.3k9102142
edited Nov 12 at 1:52
Cœur
17.3k9102142
edited Nov 12 at 1:52
Cœur
17.3k9102142
17.3k9102142
asked Nov 12 at 1:43
yeshang
1
asked Nov 12 at 1:43
yeshang
1
asked Nov 12 at 1:43
yeshang
1
1
2
This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45
add a comment |
2
This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45
2
2
This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45
This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45
add a comment |
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This is rather focused question that might make more sense for the Spark developers mailing list
– cricket_007
Nov 12 at 1:45