[jira] [Updated] (SPARK-26205) Optimize InSet expression for bytes, shorts, ints, dates
[
https://issues.apache.org/jira/browse/SPARK-26205?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Anton Okolnychyi updated SPARK-26205:
-
Description:
{{In}} expressions are compiled into a sequence of if-else statements, which
results in O\(n\) time complexity. {{InSet}} is an optimized version of {{In}},
which is supposed to improve the performance if the number of elements is big
enough. However, {{InSet}} actually degrades the performance in many cases due
to various reasons (benchmarks were created in SPARK-26203 and solutions to the
boxing problem are discussed in SPARK-26204).
The main idea of this JIRA is to use Java {{switch}} statements to
significantly improve the performance of {{InSet}} expressions for bytes,
shorts, ints, dates. All {{switch}} statements are compiled into
{{tableswitch}} and {{lookupswitch}} bytecode instructions. We will have O\(1\)
time complexity if our case values are compact and {{tableswitch}} can be used.
Otherwise, {{lookupswitch}} will give us O\(log n\). Our local benchmarks show
that this logic is more than two times faster even on 500+ elements than using
primitive collections in {{InSet}} expressions. As Spark is using Scala
{{HashSet}} right now, the performance gain will be is even bigger.
See
[here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
and
[here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
for more information.
was:
Currently, {{In}} expressions are compiled into a sequence of if-else
statements, which results in O\(n\) time complexity. {{InSet}} is an optimized
version of {{In}}, which is supposed to improve the performance if the number
of elements is big enough. However, {{InSet}} actually degrades the performance
in many cases due to various reasons (benchmarks will be available in
SPARK-26203 and solutions are discussed in SPARK-26204).
The main idea of this JIRA is to make use of {{tableswitch}} and
{{lookupswitch}} bytecode instructions. In short, we can improve our time
complexity from O\(n\) to O\(1\) or at least O\(log n\) by using Java
{{switch}} statements. We will have O\(1\) time complexity if our case values
are compact and {{tableswitch}} can be used. Otherwise, {{lookupswitch}} will
give us O\(log n\).
An important benefit of the proposed approach is that we do not have to pay an
extra cost for autoboxing as in case of {{InSet}}. As a consequence, we can
substantially outperform {{InSet}} even on 250+ elements.
See
[here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
and
[here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
for more information.
> Optimize InSet expression for bytes, shorts, ints, dates
>
>
> Key: SPARK-26205
> URL: https://issues.apache.org/jira/browse/SPARK-26205
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Anton Okolnychyi
>Priority: Major
>
> {{In}} expressions are compiled into a sequence of if-else statements, which
> results in O\(n\) time complexity. {{InSet}} is an optimized version of
> {{In}}, which is supposed to improve the performance if the number of
> elements is big enough. However, {{InSet}} actually degrades the performance
> in many cases due to various reasons (benchmarks were created in SPARK-26203
> and solutions to the boxing problem are discussed in SPARK-26204).
> The main idea of this JIRA is to use Java {{switch}} statements to
> significantly improve the performance of {{InSet}} expressions for bytes,
> shorts, ints, dates. All {{switch}} statements are compiled into
> {{tableswitch}} and {{lookupswitch}} bytecode instructions. We will have
> O\(1\) time complexity if our case values are compact and {{tableswitch}} can
> be used. Otherwise, {{lookupswitch}} will give us O\(log n\). Our local
> benchmarks show that this logic is more than two times faster even on 500+
> elements than using primitive collections in {{InSet}} expressions. As Spark
> is using Scala {{HashSet}} right now, the performance gain will be is even
> bigger.
> See
> [here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
> and
> [here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
> for more information.
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[jira] [Updated] (SPARK-26205) Optimize InSet expression for bytes, shorts, ints, dates
[
https://issues.apache.org/jira/browse/SPARK-26205?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Anton Okolnychyi updated SPARK-26205:
-
Summary: Optimize InSet expression for bytes, shorts, ints, dates (was:
Optimize In expression for bytes, shorts, ints)
> Optimize InSet expression for bytes, shorts, ints, dates
>
>
> Key: SPARK-26205
> URL: https://issues.apache.org/jira/browse/SPARK-26205
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Anton Okolnychyi
>Priority: Major
>
> Currently, {{In}} expressions are compiled into a sequence of if-else
> statements, which results in O\(n\) time complexity. {{InSet}} is an
> optimized version of {{In}}, which is supposed to improve the performance if
> the number of elements is big enough. However, {{InSet}} actually degrades
> the performance in many cases due to various reasons (benchmarks will be
> available in SPARK-26203 and solutions are discussed in SPARK-26204).
> The main idea of this JIRA is to make use of {{tableswitch}} and
> {{lookupswitch}} bytecode instructions. In short, we can improve our time
> complexity from O\(n\) to O\(1\) or at least O\(log n\) by using Java
> {{switch}} statements. We will have O\(1\) time complexity if our case values
> are compact and {{tableswitch}} can be used. Otherwise, {{lookupswitch}} will
> give us O\(log n\).
> An important benefit of the proposed approach is that we do not have to pay
> an extra cost for autoboxing as in case of {{InSet}}. As a consequence, we
> can substantially outperform {{InSet}} even on 250+ elements.
> See
> [here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
> and
> [here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
> for more information.
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[jira] [Updated] (SPARK-26205) Optimize In expression for bytes, shorts, ints
[
https://issues.apache.org/jira/browse/SPARK-26205?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Anton Okolnychyi updated SPARK-26205:
-
Description:
Currently, {{In}} expressions are compiled into a sequence of if-else
statements, which results in O\(n\) time complexity. {{InSet}} is an optimized
version of {{In}}, which is supposed to improve the performance if the number
of elements is big enough. However, {{InSet}} actually degrades the performance
in many cases due to various reasons (benchmarks will be available in
SPARK-26203 and solutions are discussed in SPARK-26204).
The main idea of this JIRA is to make use of {{tableswitch}} and
{{lookupswitch}} bytecode instructions. In short, we can improve our time
complexity from O\(n\) to O\(1\) or at least O\(log n\) by using Java
{{switch}} statements. We will have O\(1\) time complexity if our case values
are compact and {{tableswitch}} can be used. Otherwise, {{lookupswitch}} will
give us O\(log n\).
An important benefit of the proposed approach is that we do not have to pay an
extra cost for autoboxing as in case of {{InSet}}. As a consequence, we can
substantially outperform {{InSet}} even on 250+ elements.
See
[here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
and
[here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
for more information.
was:
Currently, {{In}} expressions are compiled into a sequence of if-else
statements, which results in O\(n\) time complexity. {{InSet}} is an optimized
version of {{In}}, which is supposed to improve the performance if the number
of elements is big enough. However, {{InSet}} actually degrades the performance
in many cases due to various reasons (benchmarks will be available in
SPARK-26203 and solutions are discussed in SPARK-26204).
The main idea of this JIRA is to make use of {{tableswitch}} and
{{lookupswitch}} bytecode instructions. In short, we can improve our time
complexity from O\(n\) to O\(1\) or at least O\(log n\) by using Java
{{switch}} statements. We will have O\(1\) time complexity if our case values
are compact and {{tableswitch}} can be used. Otherwise, {{lookupswitch}} will
give us O\(log n\).
An important benefit of the proposed approach is that we do not have to pay an
extra cost for autoboxing as in case of {{InSet}}. As a consequence, we can
substantially outperform {{InSet}} even on 250+ elements.
See
[here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
and here for
[more|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
information.
> Optimize In expression for bytes, shorts, ints
> --
>
> Key: SPARK-26205
> URL: https://issues.apache.org/jira/browse/SPARK-26205
> Project: Spark
> Issue Type: Improvement
> Components: SQL
>Affects Versions: 3.0.0
>Reporter: Anton Okolnychyi
>Priority: Major
>
> Currently, {{In}} expressions are compiled into a sequence of if-else
> statements, which results in O\(n\) time complexity. {{InSet}} is an
> optimized version of {{In}}, which is supposed to improve the performance if
> the number of elements is big enough. However, {{InSet}} actually degrades
> the performance in many cases due to various reasons (benchmarks will be
> available in SPARK-26203 and solutions are discussed in SPARK-26204).
> The main idea of this JIRA is to make use of {{tableswitch}} and
> {{lookupswitch}} bytecode instructions. In short, we can improve our time
> complexity from O\(n\) to O\(1\) or at least O\(log n\) by using Java
> {{switch}} statements. We will have O\(1\) time complexity if our case values
> are compact and {{tableswitch}} can be used. Otherwise, {{lookupswitch}} will
> give us O\(log n\).
> An important benefit of the proposed approach is that we do not have to pay
> an extra cost for autoboxing as in case of {{InSet}}. As a consequence, we
> can substantially outperform {{InSet}} even on 250+ elements.
> See
> [here|https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-3.html#jvms-3.10]
> and
> [here|https://stackoverflow.com/questions/10287700/difference-between-jvms-lookupswitch-and-tableswitch]
> for more information.
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