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https://issues.apache.org/jira/browse/SPARK-23598?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16391709#comment-16391709
]
David Vogelbacher edited comment on SPARK-23598 at 3/8/18 6:41 PM:
-------------------------------------------------------------------
[~mgaido] {{HashAggregateExec}} calls {{addNewFunction}}, which calls
{{addNewFunctionInternal}} which uses that flag and checks if the current size
is bigger than {{GENERATED_CLASS_SIZE_THRESHOLD}}
([see|https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala#L478])
I just compiled develop with {{GENERATED_CLASS_SIZE_THRESHOLD}} set to -1 and
was able to reproduce (cc [~hvanhovell]) . I applied the following diff before
compiling:
{noformat}
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
index 793824b0b0..7fad817d89 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
@@ -1167,7 +1167,7 @@ object CodeGenerator extends Logging {
// limit, 65,536. We cannot know how many constants will be inserted for a
class, so we use a
// threshold of 1000k bytes to determine when a function should be inlined
to a private, inner
// class.
- final val GENERATED_CLASS_SIZE_THRESHOLD = 1000000
+ final val GENERATED_CLASS_SIZE_THRESHOLD = -1
// This is the threshold for the number of global variables, whose types are
primitive type or
// complex type (e.g. more than one-dimensional array), that will be placed
at the outer class
(END)
{noformat}
Then, I executed a simple groupBy-Aggregate in the spark-shell and got the same
error:
{noformat}
➜ spark git:(master) ✗ ./bin/spark-shell
18/03/08 18:30:24 WARN Utils: Your hostname, dvogelbac resolves to a loopback
address: 127.0.0.1; using 10.111.11.111 instead (on interface en0)
18/03/08 18:30:24 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another
address
18/03/08 18:30:24 WARN NativeCodeLoader: Unable to load native-hadoop library
for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
Spark context Web UI available at http://10.111.11.111:4040
Spark context available as 'sc' (master = local[*], app id =
local-1520533829643).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.0-SNAPSHOT
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_121)
Type in expressions to have them evaluated.
Type :help for more information.
scala> spark.conf.set("spark.sql.codegen.wholeStage", true)
scala> val df_pet_age = Seq(
| (8, "bat"),
| (5, "bat"),
| (15, "bat"),
| (30, "mouse"),
| (15, "mouse"),
| (23, "mouse"),
| (8, "horse"),
| (-5, "horse")
| ).toDF("age", "name")
df_pet_age: org.apache.spark.sql.DataFrame = [age: int, name: string]
scala> df_pet_age.groupBy("name").avg("age").show()
18/03/08 18:31:20 ERROR Executor: Exception in task 1.0 in stage 0.0 (TID 1)
java.lang.IllegalAccessError: tried to access method
org.apache.spark.sql.execution.BufferedRowIterator.stopEarly()Z from class
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1$agg_NestedClass1
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1$agg_NestedClass1.agg_doAggregateWithKeys$(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:616)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at
org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
18/03/08 18:31:20 ERROR Executor: Exception in task 5.0 in stage 0.0 (TID 5)
{noformat}
It is actually failing trying to invoke a different method in
{{BufferedRowIterator}} now ({{stopEarly}}), but it is the same problem. That
method is also declared {{protected}} and can't be accessed.
was (Author: dvogelbacher):
[~mgaido] {{HashAggregateExec}} calls {{addNewFunction}}, which calls
{{addNewFunctionInternal}} which uses that flag and checks if the current size
is bigger than {{GENERATED_CLASS_SIZE_THRESHOLD}}
([see|https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala#L478])
I just compiled develop with {{GENERATED_CLASS_SIZE_THRESHOLD}} set to -1 and
was able to reproduce (cc [~hvanhovell]) . I applied the following diff before
compiling:
{noformat}
diff --git
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
index 793824b0b0..7fad817d89 100644
---
a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
+++
b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala
@@ -1167,7 +1167,7 @@ object CodeGenerator extends Logging {
// limit, 65,536. We cannot know how many constants will be inserted for a
class, so we use a
// threshold of 1000k bytes to determine when a function should be inlined
to a private, inner
// class.
- final val GENERATED_CLASS_SIZE_THRESHOLD = 1000000
+ final val GENERATED_CLASS_SIZE_THRESHOLD = -1
// This is the threshold for the number of global variables, whose types are
primitive type or
// complex type (e.g. more than one-dimensional array), that will be placed
at the outer class
(END)
{noformat}
Then, I executed a simple groupBy-Aggregate in the spark-shell and got the same
error:
{noformat}
➜ spark git:(master) ✗ ./bin/spark-shell
18/03/08 18:30:24 WARN Utils: Your hostname, dvogelbac56-mac resolves to a
loopback address: 127.0.0.1; using 10.224.86.161 instead (on interface en0)
18/03/08 18:30:24 WARN Utils: Set SPARK_LOCAL_IP if you need to bind to another
address
18/03/08 18:30:24 WARN NativeCodeLoader: Unable to load native-hadoop library
for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use
setLogLevel(newLevel).
Spark context Web UI available at http://10.224.86.161:4040
Spark context available as 'sc' (master = local[*], app id =
local-1520533829643).
Spark session available as 'spark'.
Welcome to
____ __
/ __/__ ___ _____/ /__
_\ \/ _ \/ _ `/ __/ '_/
/___/ .__/\_,_/_/ /_/\_\ version 2.4.0-SNAPSHOT
/_/
Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_121)
Type in expressions to have them evaluated.
Type :help for more information.
scala> spark.conf.set("spark.sql.codegen.wholeStage", true)
scala> val df_pet_age = Seq(
| (8, "bat"),
| (5, "bat"),
| (15, "bat"),
| (30, "mouse"),
| (15, "mouse"),
| (23, "mouse"),
| (8, "horse"),
| (-5, "horse")
| ).toDF("age", "name")
df_pet_age: org.apache.spark.sql.DataFrame = [age: int, name: string]
scala> df_pet_age.groupBy("name").avg("age").show()
18/03/08 18:31:20 ERROR Executor: Exception in task 1.0 in stage 0.0 (TID 1)
java.lang.IllegalAccessError: tried to access method
org.apache.spark.sql.execution.BufferedRowIterator.stopEarly()Z from class
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1$agg_NestedClass1
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1$agg_NestedClass1.agg_doAggregateWithKeys$(Unknown
Source)
at
org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
Source)
at
org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at
org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$11$$anon$1.hasNext(WholeStageCodegenExec.scala:616)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at
org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
18/03/08 18:31:20 ERROR Executor: Exception in task 5.0 in stage 0.0 (TID 5)
{noformat}
It is actually failing trying to invoke a different method in
{{BufferedRowIterator}} now ({{stopEarly}}), but it is the same problem. That
method is also declared {{protected}} and can't be accessed.
> WholeStageCodegen can lead to IllegalAccessError calling append for
> HashAggregateExec
> --------------------------------------------------------------------------------------
>
> Key: SPARK-23598
> URL: https://issues.apache.org/jira/browse/SPARK-23598
> Project: Spark
> Issue Type: Bug
> Components: Spark Core
> Affects Versions: 2.4.0
> Reporter: David Vogelbacher
> Priority: Major
>
> Got the following stacktrace for a large QueryPlan using WholeStageCodeGen:
> {noformat}
> java.lang.IllegalAccessError: tried to access method
> org.apache.spark.sql.execution.BufferedRowIterator.append(Lorg/apache/spark/sql/catalyst/InternalRow;)V
> from class
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7$agg_NestedClass
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7$agg_NestedClass.agg_doAggregateWithKeysOutput$(Unknown
> Source)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage7.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$10$$anon$1.hasNext(WholeStageCodegenExec.scala:614)
> at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
> at
> org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
> at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at
> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345){noformat}
> After disabling codegen, everything works.
> The root cause seems to be that we are trying to call the protected _append_
> method of
> [BufferedRowIterator|https://github.com/apache/spark/blob/master/sql/core/src/main/java/org/apache/spark/sql/execution/BufferedRowIterator.java#L68]
> from an inner-class of a sub-class that is loaded by a different
> class-loader (after codegen compilation).
> [https://docs.oracle.com/javase/specs/jvms/se7/html/jvms-5.html#jvms-5.4.4]
> states that a protected method _R_ can be accessed only if one of the
> following two conditions is fulfilled:
> # R is protected and is declared in a class C, and D is either a subclass of
> C or C itself. Furthermore, if R is not static, then the symbolic reference
> to R must contain a symbolic reference to a class T, such that T is either a
> subclass of D, a superclass of D, or D itself.
> # R is either protected or has default access (that is, neither public nor
> protected nor private), and is declared by a class in the same run-time
> package as D.
> 2.) doesn't apply as we have loaded the class with a different class loader
> (and are in a different package) and 1.) doesn't apply because we are
> apparently trying to call the method from an inner class of a subclass of
> _BufferedRowIterator_.
> Looking at the Code path of _WholeStageCodeGen_, the following happens:
> # In
> [WholeStageCodeGen|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/WholeStageCodegenExec.scala#L527],
> we create the subclass of _BufferedRowIterator_, along with a _processNext_
> method for processing the output of the child plan.
> # In the child, which is a
> [HashAggregateExec|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/aggregate/HashAggregateExec.scala#L517],
> we create the method which shows up at the top of the stack trace (called
> _doAggregateWithKeysOutput_ )
> # We add this method to the compiled code invoking _addNewFunction_ of
> [CodeGenerator|https://github.com/apache/spark/blob/master/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/codegen/CodeGenerator.scala#L460]
> In the generated function body we call the _append_ method.|
> Now, the _addNewFunction_ method states that:
> {noformat}
> If the code for the `OuterClass` grows too large, the function will be
> inlined into a new private, inner class
> {noformat}
> This indeed seems to happen: the _doAggregateWithKeysOutput_ method is put
> into a new private inner class. Thus, it doesn't have access to the protected
> _append_ method anymore but still tries to call it, which results in the
> _IllegalAccessError._
> Possible fixes:
> * Pass in the _inlineToOuterClass_ flag when invoking the _addNewFunction_
> * Make the _append_ method public
> * Re-declare the _append_ method in the generated subclass (just invoking
> _super_). This way, inner classes should have access to it.
>
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