[HUDI-6219] Ensure consistency between Spark catalog schema and Hudi schema #8725
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leesf
reviewed
May 16, 2023
| assertTrue(exception.getMessage.contains(s"""$tableName is not a Hudi table""")) | ||
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| test("Test hoodie table schema consistency for non-Avro data types") { |
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do you also tested it with hive sync enabled?
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Yes, I have test the write operation with hive-sync. It works well because the table schema has been converted to avro types.
leesf
approved these changes
May 18, 2023
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@leesf The failed test seems a bit strange, the report failed test is: 2023-05-19T01:35:52.6353614Z [ERROR] Tests run: 12, Failures: 0, Errors: 1, Skipped: 0, Time elapsed: 155.564 s <<< FAILURE! - in org.apache.hudi.functional.TestDataSourceForBootstrap
2023-05-19T01:35:52.6358391Z [ERROR] testMetadataBootstrapMORPartitionedInlineClustering{boolean}[2] Time elapsed: 8.665 s <<< ERROR!
2023-05-19T01:35:52.6359417Z org.apache.spark.SparkException:
2023-05-19T01:35:52.6360746Z Job aborted due to stage failure: Task 2 in stage 66.0 failed 1 times, most recent failure: Lost task 2.0 in stage 66.0 (TID 150) (fv-az1114-420.v3gn4mkxnddubagvm3aoiftxed.cx.internal.cloudapp.net executor driver): org.apache.hudi.exception.HoodieException: Unable to instantiate payload class
2023-05-19T01:35:52.6361900Z at org.apache.hudi.common.util.HoodieRecordUtils.loadPayload(HoodieRecordUtils.java:103)
2023-05-19T01:35:52.6362657Z at org.apache.hudi.common.util.SpillableMapUtils.convertToHoodieRecordPayload(SpillableMapUtils.java:153)
2023-05-19T01:35:52.6363382Z at org.apache.hudi.common.util.SpillableMapUtils.convertToHoodieRecordPayload(SpillableMapUtils.java:121)
2023-05-19T01:35:52.6364119Z at org.apache.hudi.avro.HoodieAvroUtils.createHoodieRecordFromAvro(HoodieAvroUtils.java:1100)
2023-05-19T01:35:52.6438493Z at org.apache.hudi.common.model.HoodieAvroIndexedRecord.wrapIntoHoodieRecordPayloadWithParams(HoodieAvroIndexedRecord.java:159)
2023-05-19T01:35:52.6439602Z at org.apache.hudi.common.table.log.HoodieFileSliceReader.getFileSliceReader(HoodieFileSliceReader.java:45)
2023-05-19T01:35:52.6440832Z at org.apache.hudi.client.clustering.run.strategy.MultipleSparkJobExecutionStrategy.lambda$null$8(MultipleSparkJobExecutionStrategy.java:313)
2023-05-19T01:35:52.6441605Z at java.util.Iterator.forEachRemaining(Iterator.java:116)
2023-05-19T01:35:52.6442126Z at scala.collection.convert.Wrappers$IteratorWrapper.forEachRemaining(Wrappers.scala:30)
2023-05-19T01:35:52.6443174Z at org.apache.hudi.client.clustering.run.strategy.MultipleSparkJobExecutionStrategy.lambda$readRecordsForGroupWithLogs$7e6d03ba$1(MultipleSparkJobExecutionStrategy.java:287)
2023-05-19T01:35:52.6444022Z at org.apache.spark.api.java.JavaRDDLike.$anonfun$mapPartitions$1(JavaRDDLike.scala:153)
2023-05-19T01:35:52.6444558Z at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:863)
2023-05-19T01:35:52.6445056Z at org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:863)
2023-05-19T01:35:52.6445573Z at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
2023-05-19T01:35:52.6446142Z at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
2023-05-19T01:35:52.6446639Z at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
2023-05-19T01:35:52.6447151Z at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
2023-05-19T01:35:52.6447693Z at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373)
2023-05-19T01:35:52.6448192Z at org.apache.spark.rdd.RDD.iterator(RDD.scala:337)
2023-05-19T01:35:52.6448735Z at org.apache.spark.shuffle.ShuffleWriteProcessor.write(ShuffleWriteProcessor.scala:59)
2023-05-19T01:35:52.6449356Z at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:99)
2023-05-19T01:35:52.6449922Z at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:52)
2023-05-19T01:35:52.6450449Z at org.apache.spark.scheduler.Task.run(Task.scala:131)
2023-05-19T01:35:52.6450951Z at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506)
2023-05-19T01:35:52.6451467Z at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491)
2023-05-19T01:35:52.6451952Z at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509)
2023-05-19T01:35:52.6452568Z at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
2023-05-19T01:35:52.6453166Z at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
2023-05-19T01:35:52.6453639Z at java.lang.Thread.run(Thread.java:750)
2023-05-19T01:35:52.6454160Z Caused by: java.lang.reflect.InvocationTargetException
2023-05-19T01:35:52.6454678Z at sun.reflect.GeneratedConstructorAccessor117.newInstance(Unknown Source)
2023-05-19T01:35:52.6455358Z at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
2023-05-19T01:35:52.6456124Z at java.lang.reflect.Constructor.newInstance(Constructor.java:423)
2023-05-19T01:35:52.6456712Z at org.apache.hudi.common.util.HoodieRecordUtils.loadPayload(HoodieRecordUtils.java:101)
2023-05-19T01:35:52.6457162Z ... 28 more
2023-05-19T01:35:52.6459273Z Caused by: org.apache.hudi.exception.HoodieException: Ordering value is null for record: {"_hoodie_commit_time": "00000000000001", "_hoodie_commit_seqno": "00000000000001_0_0", "_hoodie_record_key": "trip_77", "_hoodie_partition_path": "datestr=2020-04-03", "_hoodie_file_name": "8b831469-fe34-45fe-a711-9d1a2523ddd9_0-7-17_00000000000001.parquet", "timestamp": null, "_row_key": null, "partition_path": null, "rider": null, "driver": null, "begin_lat": null, "begin_lon": null, "end_lat": null, "end_lon": null, "fare": null, "tip_history": null, "_hoodie_is_deleted": null, "datestr": null}I can not reproduce it in local with command for both Spark3.1 and Spark3.2: mvn test -Dtest=org.apache.hudi.functional.TestDataSourceForBootstrap -Punit-tests -Dscala-2.12 -Dspark3.2 -pl "hudi-spark-datasource/hudi-spark" -e -ntp -B -V -Pwarn-log -Dorg.slf4j.simpleLogger.log.org.apache.maven.plugins.shade=warn -Dorg.slf4j.simpleLogger.log.org.apache.maven.plugins.dependency=warn -DfailIfNoTests=false
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The tests have been fixed. Kindly request to retrigger the pipeline. @leesf |
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Change Logs
HUDI-4149 fix the drop table error if table directory moved, but it will make the Spark catalog table schema not consistent with Hudi schema if some column types are not Avro data types.
This PR want to ensure the schema consistency when create a hoodie table. Otherwise it will throw exception in hive-sync:
Caused by: org.apache.hudi.hive.HoodieHiveSyncException: Could not convert field Type from TINYINT to int for field has_lowest_price_guarantee at org.apache.hudi.hive.util.HiveSchemaUtil.getSchemaDifference(HiveSchemaUtil.java:118) at org.apache.hudi.hive.HiveSyncTool.syncSchema(HiveSyncTool.java:369) at org.apache.hudi.hive.HiveSyncTool.syncHoodieTable(HiveSyncTool.java:280) at org.apache.hudi.hive.HiveSyncTool.doSync(HiveSyncTool.java:198) at org.apache.hudi.hive.HiveSyncTool.syncHoodieTable(HiveSyncTool.java:164) ... 65 moreImpact
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Risk level (write none, low medium or high below)
None.
Documentation Update
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