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Posted to issues@iceberg.apache.org by "jakelong95 (via GitHub)" <gi...@apache.org> on 2024/01/18 22:41:12 UTC
[I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
jakelong95 opened a new issue, #9518:
URL: https://github.com/apache/iceberg/issues/9518
### Apache Iceberg version
1.4.2
### Query engine
Spark
### Please describe the bug 🐞
While testing upgrading from EMR 6.14 to EMR 7 (Iceberg 1.3.1 -> Iceberg 1.4.2, Spark 3.4.1 -> 3.5.0) a query started failing with the following stack trace:
```
org.apache.spark.SparkException: [INTERNAL_ERROR] The Spark SQL phase optimization failed with an internal error. You hit a bug in Spark or the Spark plugins you use. Please, report this bug to the corresponding communities or vendors, and provide the full stack trace.
at org.apache.spark.SparkException$.internalError(SparkException.scala:107)
at org.apache.spark.sql.execution.QueryExecution$.toInternalError(QueryExecution.scala:615)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:627)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$1(QueryExecution.scala:256)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.QueryExecution.executePhase(QueryExecution.scala:255)
at org.apache.spark.sql.execution.QueryExecution.optimizedPlan$lzycompute(QueryExecution.scala:157)
at org.apache.spark.sql.execution.QueryExecution.optimizedPlan(QueryExecution.scala:153)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$writePlans$4(QueryExecution.scala:340)
at org.apache.spark.sql.catalyst.plans.QueryPlan$.append(QueryPlan.scala:716)
at org.apache.spark.sql.execution.QueryExecution.writePlans(QueryExecution.scala:340)
at org.apache.spark.sql.execution.QueryExecution.toString(QueryExecution.scala:357)
at org.apache.spark.sql.execution.QueryExecution.org$apache$spark$sql$execution$QueryExecution$$explainString(QueryExecution.scala:311)
at org.apache.spark.sql.execution.QueryExecution.explainString(QueryExecution.scala:289)
at org.apache.spark.sql.execution.SQLExecution$.executeQuery$1(SQLExecution.scala:121)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$9(SQLExecution.scala:165)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:108)
at org.apache.spark.sql.execution.SQLExecution$.withTracker(SQLExecution.scala:255)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$8(SQLExecution.scala:165)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:276)
at org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:164)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:900)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:70)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:4399)
at org.apache.spark.sql.Dataset.head(Dataset.scala:3370)
at org.apache.spark.sql.Dataset.take(Dataset.scala:3593)
at org.apache.spark.sql.Dataset.getRows(Dataset.scala:282)
at org.apache.spark.sql.Dataset.showString(Dataset.scala:317)
at org.apache.spark.sql.Dataset.show(Dataset.scala:883)
at org.apache.spark.sql.Dataset.show(Dataset.scala:842)
at org.apache.spark.sql.Dataset.show(Dataset.scala:851)
... 47 elided
Caused by: java.lang.AssertionError: assertion failed
at scala.Predef$.assert(Predef.scala:208)
at org.apache.spark.sql.execution.datasources.v2.PushablePredicate$.$anonfun$unapply$1(DataSourceV2Strategy.scala:667)
at scala.Option.map(Option.scala:230)
at org.apache.spark.sql.execution.datasources.v2.PushablePredicate$.unapply(DataSourceV2Strategy.scala:666)
at org.apache.spark.sql.execution.datasources.v2.DataSourceV2Strategy$.translateLeafNodeFilterV2(DataSourceV2Strategy.scala:560)
at org.apache.spark.sql.execution.datasources.v2.DataSourceV2Strategy$.translateFilterV2WithMapping(DataSourceV2Strategy.scala:613)
at org.apache.spark.sql.execution.datasources.v2.PushDownUtils$.$anonfun$pushFilters$3(PushDownUtils.scala:88)
at scala.collection.immutable.List.foreach(List.scala:431)
at org.apache.spark.sql.execution.datasources.v2.PushDownUtils$.pushFilters(PushDownUtils.scala:85)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$$anonfun$pushDownFilters$1.applyOrElse(V2ScanRelationPushDown.scala:74)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$$anonfun$pushDownFilters$1.applyOrElse(V2ScanRelationPushDown.scala:61)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:503)
at org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(origin.scala:76)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:503)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1288)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1287)
at org.apache.spark.sql.catalyst.plans.logical.Project.mapChildren(basicLogicalOperators.scala:99)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1288)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1287)
at org.apache.spark.sql.catalyst.plans.logical.LocalLimit.mapChildren(basicLogicalOperators.scala:1952)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1288)
at org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1287)
at org.apache.spark.sql.catalyst.plans.logical.GlobalLimit.mapChildren(basicLogicalOperators.scala:1931)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:508)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:33)
at org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:479)
at org.apache.spark.sql.catalyst.trees.TreeNode.transform(TreeNode.scala:447)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.pushDownFilters(V2ScanRelationPushDown.scala:61)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.$anonfun$apply$3(V2ScanRelationPushDown.scala:45)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.$anonfun$apply$8(V2ScanRelationPushDown.scala:52)
at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
at scala.collection.immutable.List.foldLeft(List.scala:91)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:51)
at org.apache.spark.sql.execution.datasources.v2.V2ScanRelationPushDown$.apply(V2ScanRelationPushDown.scala:38)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:239)
at scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
at scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
at scala.collection.immutable.List.foldLeft(List.scala:91)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeBatch$1(RuleExecutor.scala:236)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$6(RuleExecutor.scala:319)
at scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.catalyst.rules.RuleExecutor$RuleExecutionContext$.withContext(RuleExecutor.scala:368)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$5(RuleExecutor.scala:319)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$5$adapted(RuleExecutor.scala:309)
at scala.collection.immutable.List.foreach(List.scala:431)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:309)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:195)
at org.apache.spark.sql.catalyst.optimizer.BaseOptimizer.super$execute(BaseOptimizer.scala:28)
at org.apache.spark.sql.catalyst.optimizer.BaseOptimizer.$anonfun$execute$1(BaseOptimizer.scala:28)
at org.apache.spark.sql.catalyst.optimizer.OptimizationContext$.withOptimizationContext(OptimizationContext.scala:80)
at org.apache.spark.sql.catalyst.optimizer.BaseOptimizer.execute(BaseOptimizer.scala:28)
at org.apache.spark.sql.catalyst.optimizer.BaseOptimizer.execute(BaseOptimizer.scala:23)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:191)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:182)
at org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:108)
at org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:182)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:161)
at org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:219)
at org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:256)
at org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:625)
... 75 more
```
I was able to narrow down and simplify the query to show exactly where we hit the issue - `select * from table where nullif(column, '') is null`. I'm able to work around this error by changing the where clause to be `column = '' or column is null`
I believe the issue is in Iceberg and not Spark, as I hit this same error when testing on EMR 6.15 (Iceberg 1.4.0, Spark 3.4.1).
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "singhpk234 (via GitHub)" <gi...@apache.org>.
singhpk234 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1908896193
was able to replicate :
```
@TestTemplate
public void testProjectionBug() {
List<Object[]> expected = ImmutableList.of(row(1L), row(2L), row(3L));
assertEquals("Should return all expected rows", expected, sql("SELECT id FROM %s where nullif(data, '') is not null", tableName));
}
```
let me debug the issue :), thanks for reporting @jakelong95 !
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 closed issue #9518: Query optimization fails after upgrading to 1.4.0+ with nullif in predicate
URL: https://github.com/apache/iceberg/issues/9518
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "singhpk234 (via GitHub)" <gi...@apache.org>.
singhpk234 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1900807210
This is interesting can you please share the table schema as well ? looks like we are now hitting an Assetion / Precondition which essentially means we are pushing something down which was not intended to ?
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1900986922
Here's the obfuscated schema from `explain` -
```
column1,timestamp
column2,timestamp
column3,timestamp
column4,string
this_is_the_problem_column,string
column6,string
column7,string
column8,string
column8,string
column9,string
column10,string
column11,string
column12,string
column13,string
column14,string
column15,string
column16,timestamp
column17,string
column18,string
column19,string
column20,int
column21,int
column22,float
column23,int
column24,int
column25,int
column26,float
column27,int
column28,string
column29,int
column30,int
column31,int
column32,string
column33,int
column34,float
column35,int
column35,int
column36,int
column37,float
column38,int
```
The column I hit this issue with in the query is renamed to `this_is_the_problem_column`. Note that this table does not have any partitioning scheme or sorting.
---
Not sure how helpful this is, but I just created a test table with a single string column and inserted a row with `''` and a row `null`, and run `select * from test.iceberg_bug_test where nullif(test, '') is null` and did not hit the issue.
I'll try and do some more digging on my end to see if we hit this issue anywhere else and if it's something wrong with this table specifically
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1909008476
Gotcha, that makes sense. I can go ahead and open a ticket with Spark and close this out. Thanks for taking a look!
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "singhpk234 (via GitHub)" <gi...@apache.org>.
singhpk234 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1907096291
> Apologies, I edited out a quick test I had done that I actually ran on a cluster that is on EMR 6.14 so it's expected that my test would succeed instead of hit the reported error
Sorry I didn't fully get this, you mean to say it can pass as well ? or is it consistently re-producable ?
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "singhpk234 (via GitHub)" <gi...@apache.org>.
singhpk234 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1909005110
ok so looks like a bug in spark 3.5 introduced via : https://github.com/apache/spark/commit/53df45650af1e48e01e392caed6c1f83c2e9e9f1#diff-b2edb35eb7c49f1f3c1fd074927328ac103e9a2cd058e6183e4cb7604ada6dd4
essentially :
```
object PushablePredicate {
def unapply(e: Expression): Option[Predicate] =
new V2ExpressionBuilder(e, true).build().map { v =>
assert(v.isInstanceOf[Predicate])
v.asInstanceOf[Predicate]
}
}
```
which is not true as the expression we get from `V2ExpressionBuilder` is not of Predicate type but of GeneralScalarExpression at this time we could have easily returned None so that this is not pushed down or handled the extractor in such a way that this works with `GeneralScalarExpression` but an assert was added which doesn't seems correct to me.
I think the fix needs to be done in spark rather than iceberg.
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1907148175
The issue is reproducible on Iceberg 1.4.2 and Spark 3.5
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1900989318
Apologies, I edited out a quick test I had done that I actually ran on a cluster that is on EMR 6.14 so it's expected that my test would succeed instead of hit the reported error
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Re: [I] Query optimization fails after upgrading to 1.4.0+ with nullif in predicate [iceberg]
Posted by "jakelong95 (via GitHub)" <gi...@apache.org>.
jakelong95 commented on issue #9518:
URL: https://github.com/apache/iceberg/issues/9518#issuecomment-1909044218
https://issues.apache.org/jira/browse/SPARK-46847
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