imonteroq opened a new issue, #10533:
URL: https://github.com/apache/hudi/issues/10533
**Describe the problem you faced**
Streaming in Spark from a Hudi table fails with the error below when a
`writeStream` process has created / written to the table with the schema
evolution settings `hoodie.schema.on.read.enable` &
`hoodie.datasource.write.reconcile.schema` on. I have not been able to upsert a
source schema containing either more columns and/or fewer columns than the
target schema without this two settings enabled.
`org.apache.spark.sql.AnalysisException: [COLUMN_ALREADY_EXISTS] The column
_hoodie_commit_seqno already exists. Consider to choose another name or rename
the existing column.`
**To Reproduce**
Steps to reproduce the behavior:
```
val sparkConf: SparkConf = new SparkConf()
.setMaster("local[*]")
.setAppName("testAppName")
.set("spark.serializer", "org.apache.spark.serializer.KryoSerializer")
.set("spark.sql.extensions",
"org.apache.spark.sql.hudi.HoodieSparkSessionExtension")
.set("spark.kryo.registrator", "org.apache.spark.HoodieSparkKryoRegistrar")
.set("spark.sql.catalog.spark_catalog",
"org.apache.spark.sql.hudi.catalog.HoodieCatalog")
val spark = SparkSession.builder.config(sparkConf).getOrCreate()
import spark.implicits._
implicit val sqlContext: SQLContext = spark.sqlContext
val hudiOptions: Map[String, String] = Map(
"hoodie.table.name" -> "test_table",
"hoodie.datasource.write.storage.type" -> "COPY_ON_WRITE",
"hoodie.datasource.write.operation" -> "upsert",
"hoodie.datasource.write.hive_style_partitioning" -> "true",
"hoodie.datasource.write.recordkey.field" -> "identifier",
"hoodie.datasource.write.precombine.field" -> "date",
"hoodie.datasource.insert.dup.policy" -> "none",
"hoodie.avro.schema.externalTransformation" -> "true",
"hoodie.schema.on.read.enable" -> "true",
"hoodie.datasource.write.reconcile.schema" -> "true")
val inMemoryRecords: List[Contract] =
List(Contract("001", 1, "test1", 100), Contract("002", 2, "test2", 100),
Contract("003", 3, "test3", 100))
val contractsInMemory: MemoryStream[Contract] = MemoryStream[Contract]
contractsInMemory.addData(inMemoryRecords)
contractsInMemory
.toDF()
.writeStream
.format("hudi")
.trigger(Trigger.AvailableNow())
.queryName("streamingQueryName")
.option("checkpointLocation", "/tmp/checkpoint")
.options(hudiOptions)
.outputMode(OutputMode.Append())
.start("/tmp/data")
.processAllAvailable()
spark.readStream
.format("hudi")
.load("/tmp/data")
.writeStream
.format("memory")
.queryName("queryName")
.outputMode("append")
.start()
.processAllAvailable()
```
**Environment Description**
* OS: Mac OS X
* Hudi version: 0.14.0
* Spark version: 3.4.1
* Storage: S3 (LocalStack)
* Running on Docker?: No
**Additional context**
This works fine with either `hoodie.schema.on.read.enable` or
`hoodie.datasource.write.reconcile.schema` disabled.
**Stacktrace**
```
org.apache.spark.sql.AnalysisException: [COLUMN_ALREADY_EXISTS] The column
`_hoodie_commit_seqno` already exists. Consider to choose another name or
rename the existing column.
at
org.apache.spark.sql.errors.QueryCompilationErrors$.columnAlreadyExistsError(QueryCompilationErrors.scala:2300)
at
org.apache.spark.sql.util.SchemaUtils$.checkColumnNameDuplication(SchemaUtils.scala:113)
at
org.apache.spark.sql.util.SchemaUtils$.checkSchemaColumnNameDuplication(SchemaUtils.scala:55)
at
org.apache.spark.sql.util.SchemaUtils$.checkSchemaColumnNameDuplication(SchemaUtils.scala:71)
at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:427)
at
org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229)
at
org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:211)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
at
org.apache.hudi.IncrementalRelation.buildScan(IncrementalRelation.scala:275)
at
org.apache.spark.sql.hudi.streaming.HoodieStreamSource.getBatch(HoodieStreamSource.scala:171)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$3(MicroBatchExecution.scala:586)
at
scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:293)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at
org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:27)
at scala.collection.TraversableLike.flatMap(TraversableLike.scala:293)
at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:290)
at
org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:27)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$2(MicroBatchExecution.scala:582)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:411)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:409)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:582)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:284)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:411)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:409)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:247)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:237)
at
org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:306)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:284)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:207)
[stream execution thread for test_hudi [id =
443bb452-13e7-4d43-916d-bac5fd5d1f2c, runId =
dbf43a65-825f-45ca-bae0-d7109ee9d066]] INFO
org.apache.spark.sql.execution.streaming.MicroBatchExecution - Async log purge
executor pool for query test_hudi [id = 443bb452-13e7-4d43-916d-bac5fd5d1f2c,
runId = dbf43a65-825f-45ca-bae0-d7109ee9d066] has been shutdown
[ScalaTest-run-running-HudiSourceIT] INFO org.apache.spark.SparkContext -
SparkContext is stopping with exitCode 0.
[dispatcher-event-loop-4] INFO
org.apache.spark.MapOutputTrackerMasterEndpoint -
MapOutputTrackerMasterEndpoint stopped!
[ScalaTest-run-running-HudiSourceIT] INFO
org.apache.spark.storage.memory.MemoryStore - MemoryStore cleared
[ScalaTest-run-running-HudiSourceIT] INFO
org.apache.spark.storage.BlockManager - BlockManager stopped
[ScalaTest-run-running-HudiSourceIT] INFO
org.apache.spark.storage.BlockManagerMaster - BlockManagerMaster stopped
[dispatcher-event-loop-2] INFO
org.apache.spark.scheduler.OutputCommitCoordinator$OutputCommitCoordinatorEndpoint
- OutputCommitCoordinator stopped!
[ScalaTest-run-running-HudiSourceIT] INFO org.apache.spark.SparkContext -
Successfully stopped SparkContext
[STREAM_FAILED] Query [id = 443bb452-13e7-4d43-916d-bac5fd5d1f2c, runId =
dbf43a65-825f-45ca-bae0-d7109ee9d066] terminated with exception:
[COLUMN_ALREADY_EXISTS] The column `_hoodie_commit_seqno` already exists.
Consider to choose another name or rename the existing column.
org.apache.spark.sql.streaming.StreamingQueryException:
[COLUMN_ALREADY_EXISTS] The column `_hoodie_commit_seqno` already exists.
Consider to choose another name or rename the existing column.
=== Streaming Query ===
Identifier: test_hudi [id = 443bb452-13e7-4d43-916d-bac5fd5d1f2c, runId =
dbf43a65-825f-45ca-bae0-d7109ee9d066]
Current Committed Offsets: {}
Current Available Offsets:
{org.apache.spark.sql.hudi.streaming.HoodieStreamSource@1ac520b5:
{"commitTime":"20240118170827012"}}
Current State: ACTIVE
Thread State: RUNNABLE
Logical Plan:
WriteToMicroBatchDataSource MemorySink,
443bb452-13e7-4d43-916d-bac5fd5d1f2c, [queryName=test_hudi], Append
+- StreamingExecutionRelation
org.apache.spark.sql.hudi.streaming.HoodieStreamSource@1ac520b5,
[_hoodie_commit_time#142, _hoodie_commit_seqno#143, _hoodie_record_key#144,
_hoodie_partition_path#145, _hoodie_file_name#146, identifier#147, name#148,
quantity#149, status#150, agent#151, metadata#152, contacts#153, date#154]
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:333)
at
org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:207)
Caused by: org.apache.spark.sql.AnalysisException: [COLUMN_ALREADY_EXISTS]
The column `_hoodie_commit_seqno` already exists. Consider to choose another
name or rename the existing column.
at
org.apache.spark.sql.errors.QueryCompilationErrors$.columnAlreadyExistsError(QueryCompilationErrors.scala:2300)
at
org.apache.spark.sql.util.SchemaUtils$.checkColumnNameDuplication(SchemaUtils.scala:113)
at
org.apache.spark.sql.util.SchemaUtils$.checkSchemaColumnNameDuplication(SchemaUtils.scala:55)
at
org.apache.spark.sql.util.SchemaUtils$.checkSchemaColumnNameDuplication(SchemaUtils.scala:71)
at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:427)
at
org.apache.spark.sql.DataFrameReader.loadV1Source(DataFrameReader.scala:229)
at
org.apache.spark.sql.DataFrameReader.$anonfun$load$2(DataFrameReader.scala:211)
at scala.Option.getOrElse(Option.scala:189)
at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:211)
at
org.apache.hudi.IncrementalRelation.buildScan(IncrementalRelation.scala:275)
at
org.apache.spark.sql.hudi.streaming.HoodieStreamSource.getBatch(HoodieStreamSource.scala:171)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$3(MicroBatchExecution.scala:586)
at
scala.collection.TraversableLike.$anonfun$flatMap$1(TraversableLike.scala:293)
at scala.collection.Iterator.foreach(Iterator.scala:943)
at scala.collection.Iterator.foreach$(Iterator.scala:943)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1431)
at scala.collection.IterableLike.foreach(IterableLike.scala:74)
at scala.collection.IterableLike.foreach$(IterableLike.scala:73)
at
org.apache.spark.sql.execution.streaming.StreamProgress.foreach(StreamProgress.scala:27)
at scala.collection.TraversableLike.flatMap(TraversableLike.scala:293)
at scala.collection.TraversableLike.flatMap$(TraversableLike.scala:290)
at
org.apache.spark.sql.execution.streaming.StreamProgress.flatMap(StreamProgress.scala:27)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runBatch$2(MicroBatchExecution.scala:582)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:411)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:409)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runBatch(MicroBatchExecution.scala:582)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$2(MicroBatchExecution.scala:284)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken(ProgressReporter.scala:411)
at
org.apache.spark.sql.execution.streaming.ProgressReporter.reportTimeTaken$(ProgressReporter.scala:409)
at
org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.$anonfun$runActivatedStream$1(MicroBatchExecution.scala:247)
at
org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:67)
at
org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:237)
at
org.apache.spark.sql.execution.streaming.StreamExecution.$anonfun$runStream$1(StreamExecution.scala:306)
at
scala.runtime.java8.JFunction0$mcV$sp.apply(JFunction0$mcV$sp.java:23)
at org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:827)
at
org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:284)
... 1 more
```
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