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Posted to commits@hudi.apache.org by GitBox <gi...@apache.org> on 2020/05/27 03:58:46 UTC
[GitHub] [hudi] a-uddhav opened a new issue #1669: [SUPPORT] IOException when PAYLOAD_CLASS_OPT_KEY is used to write to MOR tbls
a-uddhav opened a new issue #1669:
URL: https://github.com/apache/hudi/issues/1669
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**Describe the problem you faced**
I am writing records to a MOR type table using Spark Datasource while overriding the logic for `preCombine()` and `combineAndGetUpdateValue` instead of using the default behavior. However, the spark application run into an unexpected error during compaction
```
org.apache.hudi.exception.HoodieIOException: IOException when reading log file
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordScanner.scan(AbstractHoodieLogRecordScanner.java:244)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner.<init>(HoodieMergedLogRecordScanner.java:81)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.compact(HoodieMergeOnReadTableCompactor.java:126)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.lambda$compact$644ebad7$1(HoodieMergeOnReadTableCompactor.java:98)
```
**To Reproduce**
Steps to reproduce the behavior:
I am running the spark application on Intellij.
1. Write the first set of records to the MOR tbl in the OVERWRITE mode.
I used the following
```
// record class
case class RecordClass (id:Int,
name:String,
age:Int,
event_type:Int,
created_at:Timestamp)
RecordClass(1, "Uddhav-1", 30, 0,Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav0", 40, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 31, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(3, "Uddhav2", 32, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(4, "Uddhav3", 33, 0, Timestamp.valueOf("2023-09-07 00:00:00"))
```
with
```
//hudi options
HoodieWriteConfig.TABLE_NAME -> "<tblName>",
DataSourceWriteOptions.TABLE_TYPE_OPT_KEY -> DataSourceWriteOptions.MOR_TABLE_TYPE_OPT_VAL,
DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "id",
DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY -> "<date part of the created_at_column>",
DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "created_at",
DataSourceWriteOptions.PAYLOAD_CLASS_OPT_KEY -> "<payload class>"
```
and
```
//payload class
class RecordPayloadClass (val genericRecord: GenericRecord, val comparable: Comparable[Int])
extends BaseAvroPayload(genericRecord, comparable)
with HoodieRecordPayload[RecordPayloadClass]{
override def preCombine(another: RecordPayloadClass): RecordPayloadClass = {
val latestRecord: GenericRecord = pickLatestRecord(this.genericRecord, another.genericRecord)
if (latestRecord.equals(this.genericRecord)) this else another
}
// get the current record
override def combineAndGetUpdateValue(currentValue: IndexedRecord, schema: Schema): util.Option[IndexedRecord] = {
val diskRecord: GenericRecord = currentValue.asInstanceOf[GenericRecord]
val inFlighRecord: GenericRecord = this.genericRecord
Option.of(pickLatestRecord(diskRecord, inFlighRecord))
}
override def getInsertValue(schema: Schema): util.Option[IndexedRecord] = Option.of(HoodieAvroUtils.bytesToAvro(recordBytes, schema))
private def pickLatestRecord(diskRecord: GenericRecord, inFlighRecord: GenericRecord): GenericRecord = {
val diskRecordTs:Int = diskRecord.get("event_type").asInstanceOf[Int]
val inFlighRecordTs:Int = inFlighRecord.get("event_type").asInstanceOf[Int]
if(inFlighRecordTs > diskRecordTs) inFlighRecord
else if (diskRecordTs == inFlighRecordTs) {
val diskRecordEventType:Int = diskRecord.get("age").asInstanceOf[Int]
val inFlighRecordEventType:Int = inFlighRecord.get("age").asInstanceOf[Int]
// always pick the latest record
if(inFlighRecordEventType >= diskRecordEventType) inFlighRecord else diskRecord
}
else diskRecord
}
}
```
This write should be successful
2. Then write another set of records in the APPEND mode. I used the following
```
RecordClass(1, "Uddhav4", 41, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 42, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(3, "Uddhav2", 32, 0, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(4, "Uddhav3", 33, 2, Timestamp.valueOf("2023-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 42, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 43, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 44, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 45, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(1, "Uddhav5", 46, 1, Timestamp.valueOf("2020-09-07 00:00:00")),
RecordClass(3, "Uddhav2", 32, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav21", 33, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav22", 34, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav23", 35, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav24", 36, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav25", 38, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(3, "Uddhav26", 39, 1, Timestamp.valueOf("2022-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 31, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 32, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 33, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 34, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 35, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 36, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 37, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 38, 0, Timestamp.valueOf("2021-09-07 00:00:00")),
RecordClass(2, "Uddhav1", 39, 0, Timestamp.valueOf("2021-09-07 00:00:00"))
```
This write should fail with the aforementioned `HoodieIOException`
**Expected behavior**
The expectation was that records with higher `event type` and/or `age` should be written out to the hudi table. However, instead, I ran into the exception. The above logic works well when the tbl type is COW.
**Environment Description**
* Hudi version : 0.5.2
* Spark version : 2.4.4
* Hive version : No
* Hadoop version : No
* Storage (HDFS/S3/GCS..) : Local FS
* Running on Docker? (yes/no) : No
**Additional context**
Add any other context about the problem here.
**Stacktrace**
```
Exception in thread "main" org.apache.spark.SparkException: Job aborted due to stage failure: Task 1 in stage 28.0 failed 1 times, most recent failure: Lost task 1.0 in stage 28.0 (TID 13534, localhost, executor driver): org.apache.hudi.exception.HoodieIOException: IOException when reading log file
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordScanner.scan(AbstractHoodieLogRecordScanner.java:244)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner.<init>(HoodieMergedLogRecordScanner.java:81)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.compact(HoodieMergeOnReadTableCompactor.java:126)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.lambda$compact$644ebad7$1(HoodieMergeOnReadTableCompactor.java:98)
at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsBytes(MemoryStore.scala:378)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1111)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1020)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:811)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1651)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1639)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1638)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1638)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:831)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:831)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1872)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1821)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1810)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:642)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2034)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2055)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2074)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:2099)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:945)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
at org.apache.spark.rdd.RDD.collect(RDD.scala:944)
at org.apache.spark.api.java.JavaRDDLike$class.collect(JavaRDDLike.scala:361)
at org.apache.spark.api.java.AbstractJavaRDDLike.collect(JavaRDDLike.scala:45)
at org.apache.hudi.client.HoodieWriteClient.doCompactionCommit(HoodieWriteClient.java:1123)
at org.apache.hudi.client.HoodieWriteClient.commitCompaction(HoodieWriteClient.java:1091)
at org.apache.hudi.client.HoodieWriteClient.runCompaction(HoodieWriteClient.java:1074)
at org.apache.hudi.client.HoodieWriteClient.compact(HoodieWriteClient.java:1045)
at org.apache.hudi.client.HoodieWriteClient.lambda$forceCompact$12(HoodieWriteClient.java:1160)
at org.apache.hudi.common.util.Option.ifPresent(Option.java:96)
at org.apache.hudi.client.HoodieWriteClient.forceCompact(HoodieWriteClient.java:1157)
at org.apache.hudi.client.HoodieWriteClient.postCommit(HoodieWriteClient.java:502)
at org.apache.hudi.client.AbstractHoodieWriteClient.commit(AbstractHoodieWriteClient.java:157)
at org.apache.hudi.client.AbstractHoodieWriteClient.commit(AbstractHoodieWriteClient.java:101)
at org.apache.hudi.client.AbstractHoodieWriteClient.commit(AbstractHoodieWriteClient.java:92)
at org.apache.hudi.HoodieSparkSqlWriter$.checkWriteStatus(HoodieSparkSqlWriter.scala:262)
at org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:184)
at org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:91)
at org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:45)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:70)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:68)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.doExecute(commands.scala:86)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:131)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$execute$1.apply(SparkPlan.scala:127)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$executeQuery$1.apply(SparkPlan.scala:155)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:152)
at org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:127)
at org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:80)
at org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:80)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter$$anonfun$runCommand$1.apply(DataFrameWriter.scala:656)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
at org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:656)
at org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:273)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:267)
at org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:225)
at com.paypay.daas.uddhav.CustomPreCombine2$.delayedEndpoint$com$paypay$daas$uddhav$CustomPreCombine2$1(CustomPreCombine2.scala:77)
at com.paypay.daas.uddhav.CustomPreCombine2$delayedInit$body.apply(CustomPreCombine2.scala:10)
at scala.Function0$class.apply$mcV$sp(Function0.scala:34)
at scala.runtime.AbstractFunction0.apply$mcV$sp(AbstractFunction0.scala:12)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.App$$anonfun$main$1.apply(App.scala:76)
at scala.collection.immutable.List.foreach(List.scala:392)
at scala.collection.generic.TraversableForwarder$class.foreach(TraversableForwarder.scala:35)
at scala.App$class.main(App.scala:76)
at com.paypay.daas.uddhav.CustomPreCombine2$.main(CustomPreCombine2.scala:10)
at com.paypay.daas.uddhav.CustomPreCombine2.main(CustomPreCombine2.scala)
Caused by: org.apache.hudi.exception.HoodieIOException: IOException when reading log file
at org.apache.hudi.common.table.log.AbstractHoodieLogRecordScanner.scan(AbstractHoodieLogRecordScanner.java:244)
at org.apache.hudi.common.table.log.HoodieMergedLogRecordScanner.<init>(HoodieMergedLogRecordScanner.java:81)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.compact(HoodieMergeOnReadTableCompactor.java:126)
at org.apache.hudi.table.compact.HoodieMergeOnReadTableCompactor.lambda$compact$644ebad7$1(HoodieMergeOnReadTableCompactor.java:98)
at org.apache.spark.api.java.JavaPairRDD$$anonfun$toScalaFunction$1.apply(JavaPairRDD.scala:1040)
at scala.collection.Iterator$$anon$11.next(Iterator.scala:410)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:435)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:441)
at org.apache.spark.storage.memory.MemoryStore.putIteratorAsBytes(MemoryStore.scala:378)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1111)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:1020)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:1085)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:811)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:335)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:286)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
```
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[GitHub] [hudi] a-uddhav commented on issue #1669: [SUPPORT] IOException when PAYLOAD_CLASS_OPT_KEY is used to write to MOR tbls
Posted by GitBox <gi...@apache.org>.
a-uddhav commented on issue #1669:
URL: https://github.com/apache/hudi/issues/1669#issuecomment-634449462
I figured what was I doing wrong. I had missed a constructor to the payload class.
```
class RecordPayloadClass (val genericRecord: GenericRecord, val comparable: Comparable[Int])
extends BaseAvroPayload(genericRecord, comparable)
with HoodieRecordPayload[RecordPayloadClass]{
===== added constructor ======
// required by SpillableMapUtils.convertToHoodieRecordPayload
def this(optionalRecord: Option[GenericRecord]) {
this(optionalRecord.get(), 1)
}
override def preCombine(another: RecordPayloadClass): RecordPayloadClass = {
....
```
I will close this issue.
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[GitHub] [hudi] a-uddhav closed issue #1669: [SUPPORT] IOException when PAYLOAD_CLASS_OPT_KEY is used to write to MOR tbls
Posted by GitBox <gi...@apache.org>.
a-uddhav closed issue #1669:
URL: https://github.com/apache/hudi/issues/1669
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