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https://issues.apache.org/jira/browse/SPARK-12473?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Andrew Or updated SPARK-12473:
------------------------------
Description:
After commit de02782 of page rank regressed from 242s to 260s, about 7%.
The commit added 26 types to register every time we create a Kryo serializer
instance. I ran a small microbenchmark to prove that this is noticeably
expensive:
{code}
import org.apache.spark.serializer._
import org.apache.spark.SparkConf
def makeMany(num: Int): Long = {
val start = System.currentTimeMillis
(1 to num).foreach { _ => new KryoSerializer(new SparkConf).newKryo() }
System.currentTimeMillis - start
}
// before commit de02782, averaged over multiple runs
makeMany(5000) == 1500
// after commit de02782, averaged over multiple runs
makeMany(5000) == 2750
{code}
Since we create multiple serializer instances per partition, this means a
5000-partition stage will unconditionally see an increase of > 1s for the
stage. In page rank, we may run many such stages.
We should explore the alternative of reusing thread-local serializer instances,
which would lead to much fewer calls to `kryo.register`.
was:
After commit de02782 of page rank regressed from 242s to 260s, about 7%.
The commit added 26 types to register every time we create a Kryo serializer
instance. I ran a small microbenchmark to prove that this is noticeably
expensive:
{code}
import org.apache.spark.serializer._
import org.apache.spark.SparkConf
def makeMany(num: Int): Long = {
val start = System.currentTimeMillis
(1 to num).foreach { _ => new KryoSerializer(new SparkConf).newKryo() }
System.currentTimeMillis - start
}
// before commit de02782, averaged over multiple runs
makeMany(5000) == 1500
// after commit de02782, averaged over multiple runs
makeMany(5000) == 2750
{code}
Since we create multiple serializer instances per partition, this means a
5000-partition stage will unconditionally see an increase of > 1s for the
stage. In page rank, we may run many such stages.
> Reuse serializer instances for performance
> ------------------------------------------
>
> Key: SPARK-12473
> URL: https://issues.apache.org/jira/browse/SPARK-12473
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 1.6.0
> Reporter: Andrew Or
> Assignee: Andrew Or
>
> After commit de02782 of page rank regressed from 242s to 260s, about 7%.
> The commit added 26 types to register every time we create a Kryo serializer
> instance. I ran a small microbenchmark to prove that this is noticeably
> expensive:
> {code}
> import org.apache.spark.serializer._
> import org.apache.spark.SparkConf
> def makeMany(num: Int): Long = {
> val start = System.currentTimeMillis
> (1 to num).foreach { _ => new KryoSerializer(new SparkConf).newKryo() }
> System.currentTimeMillis - start
> }
> // before commit de02782, averaged over multiple runs
> makeMany(5000) == 1500
> // after commit de02782, averaged over multiple runs
> makeMany(5000) == 2750
> {code}
> Since we create multiple serializer instances per partition, this means a
> 5000-partition stage will unconditionally see an increase of > 1s for the
> stage. In page rank, we may run many such stages.
> We should explore the alternative of reusing thread-local serializer
> instances, which would lead to much fewer calls to `kryo.register`.
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