[
https://issues.apache.org/jira/browse/SPARK-35500?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Yahui Liu updated SPARK-35500:
------------------------------
Description:
Reproduce steps:
# create a new table with array type: create table test_code_gen(a array<int>);
# Add
log4j.logger.org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator =
DEBUG to log4j.properties;
# Enter spark-shell, fire a query: spark.sql("select * from
test_code_gen").collect
# Everytime, Dataset.collect is called, SpecificSafeProjection class is
generated, but the code for the class cannot be reused because everytime the id
for two variables in the generated class is changed: MapObjects_loopValue and
MapObjects_loopIsNull. So even the class generated before has been cached, new
code cannot match the cache key so that new code need to be compiled again
which cost some time.
{code:java}
object MapObjects {
private val curId = new java.util.concurrent.atomic.AtomicInteger()
val id = curId.getAndIncrement()
val loopValue = s"MapObjects_loopValue$id"
val loopIsNull = if (elementNullable) {
s"MapObjects_loopIsNull$id"
} else {
"false"
}
{code}
First time run:
#
# The time cost for compile is increasing with the growth of column number,
for wide table, this cost can more than 2s.
#
First time run:
class SpecificSafeProjection extends
org.apache.spark.sql.catalyst.expressions.codegen.BaseProjection {
private int MapObjects_loopValue{color:#FF0000}1{color};
private boolean
MapObjects_loopIsNull{color:#FF0000}1{color};
private UTF8String
MapObjects_loopValue{color:#FF0000}2{color};
private boolean
MapObjects_loopIsNull{color:#FF0000}2{color};
}
Second time run:
class SpecificSafeProjection extends
org.apache.spark.sql.catalyst.expressions.codegen.BaseProjection {
private int MapObjects_loopValue{color:#FF0000}3{color};
private boolean
MapObjects_loopIsNull{color:#FF0000}3{color};
private UTF8String
MapObjects_loopValue{color:#FF0000}4{color};
private boolean
MapObjects_loopIsNull{color:#FF0000}4{color};
}
was:
Reproduce steps:
# create a new table with array type: create table test_code_gen(a array<int>);
# Add
log4j.logger.org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator =
DEBUG to log4j.properties;
# Enter spark-shell, fire a query: spark.sql("select * from
test_code_gen").collect
# Everytime, Dataset.collect is called, SpecificSafeProjection class is
generated, but the code for the class cannot be reused because everytime the id
for two variables in the generated class is changed: MapObjects_loopValue and
MapObjects_loopIsNull. So even the class generated before has been cached, new
code cannot match the cache key so that new code need to be compiled again
which cost some time.
object MapObjects {
private val curId = new java.util.concurrent.atomic.AtomicInteger()
# The time cost for compile is increasing with the growth of column number,
for wide table, this cost can more than 2s.
> GenerateSafeProjection.generate will generate SpecificSafeProjection class,
> but if column is array type or map type, the code cannot be reused which
> impact the query performance
> ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
>
> Key: SPARK-35500
> URL: https://issues.apache.org/jira/browse/SPARK-35500
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Yahui Liu
> Priority: Minor
> Labels: codegen
>
> Reproduce steps:
> # create a new table with array type: create table test_code_gen(a
> array<int>);
> # Add
> log4j.logger.org.apache.spark.sql.catalyst.expressions.codegen.CodeGenerator
> = DEBUG to log4j.properties;
> # Enter spark-shell, fire a query: spark.sql("select * from
> test_code_gen").collect
> # Everytime, Dataset.collect is called, SpecificSafeProjection class is
> generated, but the code for the class cannot be reused because everytime the
> id for two variables in the generated class is changed: MapObjects_loopValue
> and MapObjects_loopIsNull. So even the class generated before has been
> cached, new code cannot match the cache key so that new code need to be
> compiled again which cost some time.
> {code:java}
> object MapObjects {
> private val curId = new java.util.concurrent.atomic.AtomicInteger()
> val id = curId.getAndIncrement()
> val loopValue = s"MapObjects_loopValue$id"
> val loopIsNull = if (elementNullable) {
> s"MapObjects_loopIsNull$id"
> } else {
> "false"
> }
> {code}
> First time run:
> #
> # The time cost for compile is increasing with the growth of column number,
> for wide table, this cost can more than 2s.
> #
>
> First time run:
> class SpecificSafeProjection extends
> org.apache.spark.sql.catalyst.expressions.codegen.BaseProjection {
> private int MapObjects_loopValue{color:#FF0000}1{color};
> private boolean
> MapObjects_loopIsNull{color:#FF0000}1{color};
> private UTF8String
> MapObjects_loopValue{color:#FF0000}2{color};
> private boolean
> MapObjects_loopIsNull{color:#FF0000}2{color};
> }
> Second time run:
> class SpecificSafeProjection extends
> org.apache.spark.sql.catalyst.expressions.codegen.BaseProjection {
> private int MapObjects_loopValue{color:#FF0000}3{color};
> private boolean
> MapObjects_loopIsNull{color:#FF0000}3{color};
> private UTF8String
> MapObjects_loopValue{color:#FF0000}4{color};
> private boolean
> MapObjects_loopIsNull{color:#FF0000}4{color};
> }
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