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Posted to reviews@spark.apache.org by "cloud-fan (via GitHub)" <gi...@apache.org> on 2024/01/30 15:03:49 UTC
[PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
cloud-fan opened a new pull request, #44953:
URL: https://github.com/apache/spark/pull/44953
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### What changes were proposed in this pull request?
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This PR fixes two issues when dealing with runtime user errors:
- Recognize the runtime user errors (mostly ANSI errors) and do not retry tasks for them as it won't help.
- Throw well-defined errors (the errors with an error class) directly instead of treating it as the cause of the "job aborted" error.
### Why are the changes needed?
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1. If you propose a new API, clarify the use case for a new API.
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Avoid meaningless task retry and report errors better.
### Does this PR introduce _any_ user-facing change?
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Yes, now users can see the actual error directly instead of looking for the cause of "job aborted" error.
### How was this patch tested?
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new test
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No
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471568155
##########
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
##########
@@ -2895,7 +2901,7 @@ private[spark] class DAGScheduler(
/** Fails a job and all stages that are only used by that job, and cleans up relevant state. */
private def failJobAndIndependentStages(
job: ActiveJob,
- error: SparkException): Unit = {
+ error: Exception): Unit = {
Review Comment:
~Is this inevitable?~ Nvm. I found the reason.
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "srielau (via GitHub)" <gi...@apache.org>.
srielau commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1473070577
##########
common/utils/src/main/scala/org/apache/spark/SparkThrowableHelper.scala:
##########
@@ -74,6 +74,26 @@ private[spark] object SparkThrowableHelper {
errorClass.startsWith("INTERNAL_ERROR")
}
+ def isRuntimeUserError(e: Throwable): Boolean = {
Review Comment:
Aren't retriable/transient errors in the minority? Shouldn't we flag those instead?
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan closed pull request #44953: [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors
URL: https://github.com/apache/spark/pull/44953
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1475465033
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionAnsiErrorsSuite.scala:
##########
@@ -322,4 +329,71 @@ class QueryExecutionAnsiErrorsSuite extends QueryTest
"columnName" -> "`col`")
)
}
+
+ test("user-facing runtime errors") {
Review Comment:
nit (if you need to push some changes)
```suggestion
test("SPARK-46922: user-facing runtime errors") {
```
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on PR #44953:
URL: https://github.com/apache/spark/pull/44953#issuecomment-1932057249
thanks for the review, merging to master!
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "superdupershant (via GitHub)" <gi...@apache.org>.
superdupershant commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471739687
##########
common/utils/src/main/scala/org/apache/spark/SparkThrowableHelper.scala:
##########
@@ -74,6 +74,26 @@ private[spark] object SparkThrowableHelper {
errorClass.startsWith("INTERNAL_ERROR")
}
+ def isRuntimeUserError(e: Throwable): Boolean = {
Review Comment:
I don't know if "UserError" is right concept here. These are more so Data Dependent errors. I think all exceptions with an error class are user facing.
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "MaxGekk (via GitHub)" <gi...@apache.org>.
MaxGekk commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471611997
##########
common/utils/src/main/scala/org/apache/spark/SparkThrowableHelper.scala:
##########
@@ -74,6 +74,26 @@ private[spark] object SparkThrowableHelper {
errorClass.startsWith("INTERNAL_ERROR")
}
+ def isRuntimeUserError(e: Throwable): Boolean = {
+ e match {
+ case st: SparkThrowable if st.getErrorClass != null =>
+ st.getErrorClass match {
+ case "DIVIDE_BY_ZERO" | "INTERVAL_DIVIDED_BY_ZERO" => true
+ case "ARITHMETIC_OVERFLOW" | "BINARY_ARITHMETIC_OVERFLOW" | "CAST_OVERFLOW" |
+ "CAST_OVERFLOW_IN_TABLE_INSERT" | "DATETIME_OVERFLOW" |
+ "INTERVAL_ARITHMETIC_OVERFLOW" => true
+ case "CAST_INVALID_INPUT" | "NUMERIC_VALUE_OUT_OF_RANGE" | "CANNOT_PARSE_TIMESTAMP" =>
+ true
+ case "INVALID_ARRAY_INDEX" | "INVALID_ARRAY_INDEX_IN_ELEMENT_AT" |
+ "INVALID_INDEX_OF_ZERO" => true
+ // TODO: add more user-facing runtime errors (mostly ANSI errors).
Review Comment:
How about to create a `Map`, and to check the given error class in it. Code will be more maintainable and faster.
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "HyukjinKwon (via GitHub)" <gi...@apache.org>.
HyukjinKwon commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1475465792
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionAnsiErrorsSuite.scala:
##########
@@ -322,4 +329,71 @@ class QueryExecutionAnsiErrorsSuite extends QueryTest
"columnName" -> "`col`")
)
}
+
+ test("user-facing runtime errors") {
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> "true") {
+ var numTaskStarted = 0
+ val listener = new SparkListener {
+ override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = {
+ numTaskStarted += 1
+ }
+ }
+ sparkContext.addSparkListener(listener)
+ try {
+ val df1 = spark.range(0, 10, 1, 1).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ // If error is not user-facing, it will be wrapped by `SparkException` with "Job aborted".
+ val e1 = intercept[SparkException](df1.collect())
+ assert(e1.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times.
+ assert(numTaskStarted == 2)
+ numTaskStarted = 0
+
+ val df2 = spark.range(0, 10, 1, 2).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ val e2 = intercept[SparkException](df2.collect())
+ assert(e2.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times, the input data has 2 partitions, but
+ // only the first task will fail (contains value 0), so in total 3 tasks started.
+ assert(numTaskStarted == 3)
+ numTaskStarted = 0
+
+ val df3 = spark.range(0, 10, 1, 1).select(lit(1) / $"id")
+ checkError(
+ // If error is user-facing, it will be thrown directly.
+ exception = intercept[SparkArithmeticException](df3.collect()),
+ errorClass = "DIVIDE_BY_ZERO",
+ parameters = Map("config" -> ansiConf),
+ context = ExpectedContext(
+ fragment = "div",
+ callSitePattern = getCurrentClassCallSitePattern
+ )
+ )
+ sparkContext.listenerBus.waitUntilEmpty()
+ // TODO: Spark should not re-try this error.
+ assert(numTaskStarted == 2)
+ numTaskStarted = 0
+
+ val df4 = spark.range(0, 10, 1, 2).select(lit(1) / $"id")
+ checkError(
+ exception = intercept[SparkArithmeticException](df4.collect()),
+ errorClass = "DIVIDE_BY_ZERO",
+ parameters = Map("config" -> ansiConf),
+ context = ExpectedContext(
+ fragment = "div",
+ callSitePattern = getCurrentClassCallSitePattern
+ )
+ )
+ sparkContext.listenerBus.waitUntilEmpty()
+ // TODO: Spark should not re-try tasks this error.
Review Comment:
nit but should ideally file a JIRA for this e.g., `TODO(SPARK-XXXXX): ...`
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1473751219
##########
common/utils/src/main/scala/org/apache/spark/SparkThrowableHelper.scala:
##########
@@ -74,6 +74,26 @@ private[spark] object SparkThrowableHelper {
errorClass.startsWith("INTERNAL_ERROR")
}
+ def isRuntimeUserError(e: Throwable): Boolean = {
Review Comment:
Ideally I agree with you, but the current behavior is to retry all errors, and I'm afraid of introducing regressions by not retrying most of the errors, as it's hard to identify all the errors that need retry.
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1475468317
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionAnsiErrorsSuite.scala:
##########
@@ -322,4 +329,71 @@ class QueryExecutionAnsiErrorsSuite extends QueryTest
"columnName" -> "`col`")
)
}
+
+ test("SPARK-46922: user-facing runtime errors") {
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> "true") {
+ var numTaskStarted = 0
+ val listener = new SparkListener {
+ override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = {
+ numTaskStarted += 1
+ }
+ }
+ sparkContext.addSparkListener(listener)
+ try {
+ val df1 = spark.range(0, 10, 1, 1).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ // If error is not user-facing, it will be wrapped by `SparkException` with "Job aborted".
+ val e1 = intercept[SparkException](df1.collect())
+ assert(e1.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times.
+ assert(numTaskStarted == 2)
+ numTaskStarted = 0
+
+ val df2 = spark.range(0, 10, 1, 2).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ val e2 = intercept[SparkException](df2.collect())
+ assert(e2.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times, the input data has 2 partitions, but
+ // only the first task will fail (contains value 0), so in total 3 tasks started.
+ assert(numTaskStarted == 3)
+ numTaskStarted = 0
+
+ val df3 = spark.range(0, 10, 1, 1).select(lit(1) / $"id")
+ checkError(
+ // If error is user-facing, it will be thrown directly.
+ exception = intercept[SparkArithmeticException](df3.collect()),
+ errorClass = "DIVIDE_BY_ZERO",
+ parameters = Map("config" -> ansiConf),
+ context = ExpectedContext(
+ fragment = "div",
+ callSitePattern = getCurrentClassCallSitePattern
+ )
+ )
+ sparkContext.listenerBus.waitUntilEmpty()
+ // TODO: Spark should not re-try this error.
+ assert(numTaskStarted == 2)
+ numTaskStarted = 0
+
+ val df4 = spark.range(0, 10, 1, 2).select(lit(1) / $"id")
+ checkError(
+ exception = intercept[SparkArithmeticException](df4.collect()),
+ errorClass = "DIVIDE_BY_ZERO",
+ parameters = Map("config" -> ansiConf),
+ context = ExpectedContext(
+ fragment = "div",
+ callSitePattern = getCurrentClassCallSitePattern
+ )
+ )
+ sparkContext.listenerBus.waitUntilEmpty()
+ // TODO: Spark should not re-try tasks this error.
Review Comment:
```suggestion
// TODO (SPARK-46951): Spark should not re-try tasks for this error.
```
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "superdupershant (via GitHub)" <gi...@apache.org>.
superdupershant commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471748940
##########
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
##########
@@ -2831,10 +2831,16 @@ private[spark] class DAGScheduler(
failedStage.latestInfo.completionTime = Some(clock.getTimeMillis())
updateStageInfoForPushBasedShuffle(failedStage)
for (job <- dependentJobs) {
- failJobAndIndependentStages(
- job,
+ val finalException = exception.collect {
+ // If the error is well defined (has an error class and is not internal error), we treat
+ // it as user-facing, and expose this error to the end users directly.
Review Comment:
This includes more exception types than just those that match isRuntimeUserError() right? I think we might want a different name somewhere, people might get user-facing error and user error mixed up?
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "dongjoon-hyun (via GitHub)" <gi...@apache.org>.
dongjoon-hyun commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471568155
##########
core/src/main/scala/org/apache/spark/scheduler/DAGScheduler.scala:
##########
@@ -2895,7 +2901,7 @@ private[spark] class DAGScheduler(
/** Fails a job and all stages that are only used by that job, and cleans up relevant state. */
private def failJobAndIndependentStages(
job: ActiveJob,
- error: SparkException): Unit = {
+ error: Exception): Unit = {
Review Comment:
Is this inevitable?
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1475468233
##########
sql/core/src/test/scala/org/apache/spark/sql/errors/QueryExecutionAnsiErrorsSuite.scala:
##########
@@ -322,4 +329,71 @@ class QueryExecutionAnsiErrorsSuite extends QueryTest
"columnName" -> "`col`")
)
}
+
+ test("SPARK-46922: user-facing runtime errors") {
+ withSQLConf(SQLConf.ANSI_ENABLED.key -> "true") {
+ var numTaskStarted = 0
+ val listener = new SparkListener {
+ override def onTaskStart(taskStart: SparkListenerTaskStart): Unit = {
+ numTaskStarted += 1
+ }
+ }
+ sparkContext.addSparkListener(listener)
+ try {
+ val df1 = spark.range(0, 10, 1, 1).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ // If error is not user-facing, it will be wrapped by `SparkException` with "Job aborted".
+ val e1 = intercept[SparkException](df1.collect())
+ assert(e1.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times.
+ assert(numTaskStarted == 2)
+ numTaskStarted = 0
+
+ val df2 = spark.range(0, 10, 1, 2).map { v =>
+ if (v > 5) throw new RuntimeException("test error") else v
+ }
+ val e2 = intercept[SparkException](df2.collect())
+ assert(e2.getMessage.contains("Job aborted"))
+ sparkContext.listenerBus.waitUntilEmpty()
+ // In this test suite, Spark re-tries the task 2 times, the input data has 2 partitions, but
+ // only the first task will fail (contains value 0), so in total 3 tasks started.
+ assert(numTaskStarted == 3)
+ numTaskStarted = 0
+
+ val df3 = spark.range(0, 10, 1, 1).select(lit(1) / $"id")
+ checkError(
+ // If error is user-facing, it will be thrown directly.
+ exception = intercept[SparkArithmeticException](df3.collect()),
+ errorClass = "DIVIDE_BY_ZERO",
+ parameters = Map("config" -> ansiConf),
+ context = ExpectedContext(
+ fragment = "div",
+ callSitePattern = getCurrentClassCallSitePattern
+ )
+ )
+ sparkContext.listenerBus.waitUntilEmpty()
+ // TODO: Spark should not re-try this error.
Review Comment:
```suggestion
// TODO (SPARK-46951): Spark should not re-try tasks for this error.
```
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Re: [PR] [SPARK-46922][CORE][SQL] Do not wrap runtime user-facing errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on PR #44953:
URL: https://github.com/apache/spark/pull/44953#issuecomment-1922722902
UPDATE: I removed the task retry part, as I need to investigate more about which errors should be retried. Now this PR only contains the unwrap error part.
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "superdupershant (via GitHub)" <gi...@apache.org>.
superdupershant commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471749722
##########
core/src/main/scala/org/apache/spark/scheduler/TaskSetManager.scala:
##########
@@ -976,6 +976,14 @@ private[spark] class TaskSetManager(
info.id, taskSet.id, tid, ef.description))
return
}
+ if (ef.exception.exists(SparkThrowableHelper.isRuntimeUserError)) {
Review Comment:
This will be incredibly helpful!
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "cloud-fan (via GitHub)" <gi...@apache.org>.
cloud-fan commented on PR #44953:
URL: https://github.com/apache/spark/pull/44953#issuecomment-1917089267
cc @MaxGekk @srielau @dongjoon-hyun
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Re: [PR] [SPARK-46922][CORE][SQL] Better handling for runtime user errors [spark]
Posted by "srielau (via GitHub)" <gi...@apache.org>.
srielau commented on code in PR #44953:
URL: https://github.com/apache/spark/pull/44953#discussion_r1471513685
##########
common/utils/src/main/scala/org/apache/spark/SparkThrowableHelper.scala:
##########
@@ -74,6 +74,26 @@ private[spark] object SparkThrowableHelper {
errorClass.startsWith("INTERNAL_ERROR")
}
+ def isRuntimeUserError(e: Throwable): Boolean = {
Review Comment:
Would it make sense that this as an optional field to error-classes.json?
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