mgmarino opened a new issue, #10626:
URL: https://github.com/apache/iceberg/issues/10626
### Apache Iceberg version
1.5.2 (latest release)
### Query engine
Spark
### Please describe the bug 🐞
We have an iceberg table where we have changed the partitioning, going from
an identity partition to hidden partitioning.
The partition specs are defined in the metadata json file:
```json
"partition-specs" : [ {
"spec-id" : 0,
"fields" : [ {
"name" : "day",
"transform" : "identity",
"source-id" : 6,
"field-id" : 1000
} ]
}, {
"spec-id" : 1,
"fields" : [ {
"name" : "arrival_ts_day",
"transform" : "day",
"source-id" : 5,
"field-id" : 1001
} ]
} ],
```
We did this evolution quite some time ago (I can't unfortunately remember
which version of Iceberg we were using at that point), and are now trying to
clean up the table by removing the old `day` column. Running a `DROP COLUMN` in
spark (3.5.1, using Iceberg 1.5.2) succeeds, but then a subsequent read on the
table, or e.g. the partitions metadata table results in:
```java
Caused by: java.lang.NullPointerException: Type cannot be null
at
org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkNotNull(Preconditions.java:921)
at org.apache.iceberg.types.Types$NestedField.<init>(Types.java:447)
at org.apache.iceberg.types.Types$NestedField.optional(Types.java:416)
at
org.apache.iceberg.PartitionSpec.partitionType(PartitionSpec.java:132)
at
org.apache.iceberg.Partitioning.buildPartitionProjectionType(Partitioning.java:274)
at org.apache.iceberg.Partitioning.partitionType(Partitioning.java:242)
at
org.apache.iceberg.PartitionsTable.partitions(PartitionsTable.java:167)
at org.apache.iceberg.PartitionsTable.task(PartitionsTable.java:122)
at
org.apache.iceberg.PartitionsTable.access$1100(PartitionsTable.java:35)
at
org.apache.iceberg.PartitionsTable$PartitionsScan.lambda$new$0(PartitionsTable.java:248)
at
org.apache.iceberg.StaticTableScan.doPlanFiles(StaticTableScan.java:53)
at org.apache.iceberg.SnapshotScan.planFiles(SnapshotScan.java:139)
at
org.apache.iceberg.BatchScanAdapter.planFiles(BatchScanAdapter.java:119)
at
org.apache.iceberg.spark.source.SparkPartitioningAwareScan.tasks(SparkPartitioningAwareScan.java:174)
at
org.apache.iceberg.spark.source.SparkPartitioningAwareScan.taskGroups(SparkPartitioningAwareScan.java:202)
at
org.apache.iceberg.spark.source.SparkPartitioningAwareScan.outputPartitioning(SparkPartitioningAwareScan.java:104)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$$anonfun$partitioning$1.applyOrElse(V2ScanPartitioningAndOrdering.scala:44)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$$anonfun$partitioning$1.applyOrElse(V2ScanPartitioningAndOrdering.scala:42)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$1(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.trees.CurrentOrigin$.withOrigin(TreeNode.scala:104)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:512)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1249)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1248)
at
org.apache.spark.sql.catalyst.plans.logical.Project.mapChildren(basicLogicalOperators.scala:69)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1249)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1248)
at
org.apache.spark.sql.catalyst.plans.logical.LocalLimit.mapChildren(basicLogicalOperators.scala:1563)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.$anonfun$transformDownWithPruning$3(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren(TreeNode.scala:1249)
at
org.apache.spark.sql.catalyst.trees.UnaryLike.mapChildren$(TreeNode.scala:1248)
at
org.apache.spark.sql.catalyst.plans.logical.GlobalLimit.mapChildren(basicLogicalOperators.scala:1542)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDownWithPruning(TreeNode.scala:517)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.org$apache$spark$sql$catalyst$plans$logical$AnalysisHelper$$super$transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning(AnalysisHelper.scala:267)
at
org.apache.spark.sql.catalyst.plans.logical.AnalysisHelper.transformDownWithPruning$(AnalysisHelper.scala:263)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.plans.logical.LogicalPlan.transformDownWithPruning(LogicalPlan.scala:31)
at
org.apache.spark.sql.catalyst.trees.TreeNode.transformDown(TreeNode.scala:488)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$.partitioning(V2ScanPartitioningAndOrdering.scala:42)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$.$anonfun$apply$1(V2ScanPartitioningAndOrdering.scala:35)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$.$anonfun$apply$3(V2ScanPartitioningAndOrdering.scala:38)
at
scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
at
scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
at scala.collection.immutable.List.foldLeft(List.scala:91)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$.apply(V2ScanPartitioningAndOrdering.scala:37)
at
org.apache.spark.sql.execution.datasources.v2.V2ScanPartitioningAndOrdering$.apply(V2ScanPartitioningAndOrdering.scala:33)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$2(RuleExecutor.scala:222)
at
scala.collection.LinearSeqOptimized.foldLeft(LinearSeqOptimized.scala:126)
at
scala.collection.LinearSeqOptimized.foldLeft$(LinearSeqOptimized.scala:122)
at scala.collection.immutable.List.foldLeft(List.scala:91)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1(RuleExecutor.scala:219)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$execute$1$adapted(RuleExecutor.scala:211)
at scala.collection.immutable.List.foreach(List.scala:431)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.execute(RuleExecutor.scala:211)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.$anonfun$executeAndTrack$1(RuleExecutor.scala:182)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker$.withTracker(QueryPlanningTracker.scala:88)
at
org.apache.spark.sql.catalyst.rules.RuleExecutor.executeAndTrack(RuleExecutor.scala:182)
at
org.apache.spark.sql.execution.QueryExecution.$anonfun$optimizedPlan$1(QueryExecution.scala:143)
at
org.apache.spark.sql.catalyst.QueryPlanningTracker.measurePhase(QueryPlanningTracker.scala:111)
at
org.apache.spark.sql.execution.QueryExecution.$anonfun$executePhase$2(QueryExecution.scala:202)
at
org.apache.spark.sql.execution.QueryExecution$.withInternalError(QueryExecution.scala:526)
... 32 more
```
This fails in Spark, but writes/commits from Flink (1.18.1, also using
Iceberg 1.5.2) also fail following this change. There the stack trace looks
like:
```java
java.lang.NullPointerException: Type cannot be null
at
org.apache.iceberg.relocated.com.google.common.base.Preconditions.checkNotNull(Preconditions.java:921)
at org.apache.iceberg.types.Types$NestedField.<init>(Types.java:448)
at org.apache.iceberg.types.Types$NestedField.optional(Types.java:417)
at
org.apache.iceberg.PartitionSpec.partitionType(PartitionSpec.java:132)
at
org.apache.iceberg.util.PartitionSet.lambda$new$0(PartitionSet.java:46)
at
org.apache.iceberg.relocated.com.google.common.collect.RegularImmutableMap.forEach(RegularImmutableMap.java:297)
at org.apache.iceberg.util.PartitionSet.<init>(PartitionSet.java:46)
at org.apache.iceberg.util.PartitionSet.create(PartitionSet.java:38)
at
org.apache.iceberg.ManifestFilterManager.<init>(ManifestFilterManager.java:94)
at
org.apache.iceberg.MergingSnapshotProducer$DataFileFilterManager.<init>(MergingSnapshotProducer.java:1028)
at
org.apache.iceberg.MergingSnapshotProducer$DataFileFilterManager.<init>(MergingSnapshotProducer.java:1026)
at
org.apache.iceberg.MergingSnapshotProducer.<init>(MergingSnapshotProducer.java:118)
at org.apache.iceberg.MergeAppend.<init>(MergeAppend.java:32)
at org.apache.iceberg.BaseTable.newAppend(BaseTable.java:180)
at
org.apache.iceberg.flink.sink.IcebergFilesCommitter.commitDeltaTxn(IcebergFilesCommitter.java:360)
at
org.apache.iceberg.flink.sink.IcebergFilesCommitter.commitPendingResult(IcebergFilesCommitter.java:298)
at
org.apache.iceberg.flink.sink.IcebergFilesCommitter.commitUpToCheckpoint(IcebergFilesCommitter.java:280)
at
org.apache.iceberg.flink.sink.IcebergFilesCommitter.initializeState(IcebergFilesCommitter.java:198)
at
org.apache.flink.streaming.api.operators.StreamOperatorStateHandler.initializeOperatorState(StreamOperatorStateHandler.java:122)
at
org.apache.flink.streaming.api.operators.AbstractStreamOperator.initializeState(AbstractStreamOperator.java:274)
at
org.apache.flink.streaming.runtime.tasks.RegularOperatorChain.initializeStateAndOpenOperators(RegularOperatorChain.java:106)
at
org.apache.flink.streaming.runtime.tasks.StreamTask.restoreGates(StreamTask.java:753)
at
org.apache.flink.streaming.runtime.tasks.StreamTaskActionExecutor$1.call(StreamTaskActionExecutor.java:55)
at
org.apache.flink.streaming.runtime.tasks.StreamTask.restoreInternal(StreamTask.java:728)
at
org.apache.flink.streaming.runtime.tasks.StreamTask.restore(StreamTask.java:693)
at
org.apache.flink.runtime.taskmanager.Task.runWithSystemExitMonitoring(Task.java:955)
at
org.apache.flink.runtime.taskmanager.Task.restoreAndInvoke(Task.java:924)
at org.apache.flink.runtime.taskmanager.Task.doRun(Task.java:748)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:564)
at java.base/java.lang.Thread.run(Thread.java:829)
```
We are using the AWS Glue Catalog to store information about the table. Here
are the current table properties set:
```
+------------------------------------------+-------------------+
|key |value |
+------------------------------------------+-------------------+
|connector |none |
|current-snapshot-id |2617120118159963811|
|format |iceberg/parquet |
|format-version |2 |
|history.expire.max-snapshot-age-ms |6000000 |
|write.metadata.delete-after-commit.enabled|true |
|write.metadata.previous-versions-max |2880 |
+------------------------------------------+-------------------+
```
The only way for us to recover was to force the table to point to the
metadata file right before the change.
I can provide the two metadata files if that's helpful, but I would rather
do that privately if possible.
This seems quite similar to #7386, the table was initially written using
Iceberg 1.2.1.
Please let me know if I can provide any other information!
--
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.
To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org.apache.org
For queries about this service, please contact Infrastructure at:
us...@infra.apache.org
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@iceberg.apache.org
For additional commands, e-mail: issues-h...@iceberg.apache.org
