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https://issues.apache.org/jira/browse/SPARK-22784?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Mikhail Erofeev updated SPARK-22784:
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Description:
Motivation:
Our Spark History Server spends most of the backfill time inside BufferedReader
and StringBuffer. It happens because average line size of our events is
~1.500.000 chars (due to a lot of partitions and iterations), whereas the
default buffer size is 2048 bytes. See the attached flame graph.
Implementation:
I've added logging of spent time and line size for each job.
Parametrised ReplayListenerBus with a new buffer size parameter.
Measured the best buffer size. x20 of the average line size (30mb) gives 32%
speedup in a local test.
Result:
Backfill of Spark History and reading to the cache will be up to 30% faster
after tuning.
was:
Motivation:
Our Spark History Server spends most of its warm-up time inside BufferedReader
and StringBuffer. It happens because average line size of our events is
~1.500.000 chars (due to a lot of partitions and iterations), whereas the
default buffer size is 2048 bytes. See the attached flame graph.
Implementation:
I've added logging of spent time and line size for each job.
Parametrised ReplayListenerBus with new buffer size parameter.
Measured best buffer size. x20 of average line size (30mb) gives 32% speedup in
a local test.
Result:
Warm-up of Spark History and reading to cache will be up to 30% faster after
tuning.
> Configure reading buffer size in Spark History Server
> -----------------------------------------------------
>
> Key: SPARK-22784
> URL: https://issues.apache.org/jira/browse/SPARK-22784
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core
> Affects Versions: 2.2.1
> Reporter: Mikhail Erofeev
> Priority: Minor
> Attachments: replay-baseline.svg
>
>
> Motivation:
> Our Spark History Server spends most of the backfill time inside
> BufferedReader and StringBuffer. It happens because average line size of our
> events is ~1.500.000 chars (due to a lot of partitions and iterations),
> whereas the default buffer size is 2048 bytes. See the attached flame graph.
> Implementation:
> I've added logging of spent time and line size for each job.
> Parametrised ReplayListenerBus with a new buffer size parameter.
> Measured the best buffer size. x20 of the average line size (30mb) gives 32%
> speedup in a local test.
> Result:
> Backfill of Spark History and reading to the cache will be up to 30% faster
> after tuning.
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