Sorry, sent before attaching screen shots.
On Tue, Jan 14, 2020 at 4:26 PM Sivabalan <[email protected]> wrote: > 3.x is not available under spark-avro_2.11. It is available only with 2.12 > and since 2.12 is not recommended, we are good. I verified that 2.4.4 works > for me if both spark shell and packages are using 2.4.4. > > > On Tue, Jan 14, 2020 at 12:19 PM Vinoth Chandar <[email protected]> wrote: > >> Siva, can you please confirm that if you match the spark version (version >> of spark-shell) with the version of spark-avro, things work for both 2.4.4 >> and 3.x? Else this is a release blocker. >> >> On Tue, Jan 14, 2020 at 6:45 AM Sivabalan <[email protected]> wrote: >> >> > cool, thanks for the assistance Sudha. We have to fix the quick start >> docs >> > then accordingly. >> > >> > >> > On Tue, Jan 14, 2020 at 2:28 AM Bhavani Sudha <[email protected]> >> > wrote: >> > >> > > Hi Siva, >> > > >> > > I was able to get past this issue by running from spark-shell( from >> > version >> > > 2.4.4) and spark-avro (org.apache.spark:spark-avro_2.11:2.4.4). This >> is >> > my >> > > command line for starting spark shell just for reference. >> > > >> > > spark-2.4.4-bin-hadoop2.7/bin/spark-shell --jars >> > > >> > > >> > >> /<path_to_hudi>/packaging/hudi-spark-bundle/target/hudi-spark-bundle-0.5.1-SNAPSHOT.jar >> > > --packages org.apache.spark:spark-avro_2.11:2.4.4 --conf >> > > 'spark.serializer=org.apache.spark.serializer.KryoSerializer' >> > > >> > > I think we have to match both spark-shell version and corresponding >> > > spark-avro version to 2.4.4. Please try this to see if this unblocks >> you. >> > > >> > > Thanks, >> > > Sudha >> > > >> > > On Mon, Jan 13, 2020 at 6:29 PM Vinoth Chandar <[email protected]> >> > wrote: >> > > >> > > > I will triage this tonight and get back! >> > > > >> > > > On Mon, Jan 13, 2020 at 2:28 PM Sivabalan <[email protected]> >> wrote: >> > > > >> > > > > Yes, that is what I tried. Is there any recommended version. I >> tried >> > > with >> > > > > 2.4.4. (My local spark from which I ran spark_shell >> > > > > is spark-3.0.0-preview2, guess that does not matter). >> > > > > >> > > > > ./bin/spark-shell --packages >> org.apache.spark:spark-avro_2.11:2.4.4 >> > > > --conf >> > > > > 'spark.serializer=org.apache.spark.serializer.KryoSerializer' >> --jars >> > > > > >> > > > > >> > > > >> > > >> > >> /Users/sivabala/Documents/personal/projects/siva_hudi/hudi/packaging/hudi-spark-bundle/target/hudi-spark-bundle-0.5.1-SNAPSHOT.jar >> > > > > >> > > > > >> > > > > On Mon, Jan 13, 2020 at 3:54 PM Vinoth Chandar <[email protected] >> > >> > > > wrote: >> > > > > >> > > > > > Hi Siva, >> > > > > > >> > > > > > In general, we need to match the >> > > > > > spark-avro_2.11:<spark_version_you_are_running> .. With this >> > change, >> > > > we >> > > > > > effectively dropped support for spark versions older than 2.4. >> > > > > > Are you running on a older spark version? >> > > > > > >> > > > > > >> > > > > > >> > > > > > On Mon, Jan 13, 2020 at 10:03 AM Sivabalan <[email protected]> >> > > wrote: >> > > > > > >> > > > > > > Hey folks, >> > > > > > > I am running into scala dependency issue w/ latest master >> > while >> > > > > trying >> > > > > > > to run the Quick Start. Can someone help me out on right >> > > dependency. >> > > > > > > >> > > > > > > I see that with Udit's latest PR, we have to specify explicit >> > > > packages >> > > > > > for >> > > > > > > spark-avro. Tried with spark-avro_2.11:2.4.4. >> > > > > > > >> > > > > > > scala> df.write.format("org.apache.hudi"). >> > > > > > > | options(getQuickstartWriteConfigs). >> > > > > > > | option(PRECOMBINE_FIELD_OPT_KEY, "ts"). >> > > > > > > | option(RECORDKEY_FIELD_OPT_KEY, "uuid"). >> > > > > > > | option(PARTITIONPATH_FIELD_OPT_KEY, >> "partitionpath"). >> > > > > > > | option(TABLE_NAME, tableName). >> > > > > > > | mode(Overwrite). >> > > > > > > | save(basePath); >> > > > > > > java.util.ServiceConfigurationError: >> > > > > > > org.apache.spark.sql.sources.DataSourceRegister: Provider >> > > > > > > org.apache.spark.sql.avro.AvroFileFormat could not be >> > instantiated >> > > > > > > at java.util.ServiceLoader.fail(ServiceLoader.java:232) >> > > > > > > at >> java.util.ServiceLoader.access$100(ServiceLoader.java:185) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:384) >> > > > > > > at >> > > > java.util.ServiceLoader$LazyIterator.next(ServiceLoader.java:404) >> > > > > > > at java.util.ServiceLoader$1.next(ServiceLoader.java:480) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.collection.convert.Wrappers$JIteratorWrapper.next(Wrappers.scala:44) >> > > > > > > at scala.collection.Iterator.foreach(Iterator.scala:941) >> > > > > > > at scala.collection.Iterator.foreach$(Iterator.scala:941) >> > > > > > > at >> > scala.collection.AbstractIterator.foreach(Iterator.scala:1429) >> > > > > > > at >> scala.collection.IterableLike.foreach(IterableLike.scala:74) >> > > > > > > at >> > scala.collection.IterableLike.foreach$(IterableLike.scala:73) >> > > > > > > at >> scala.collection.AbstractIterable.foreach(Iterable.scala:56) >> > > > > > > at >> > > > > > >> > > scala.collection.TraversableLike.filterImpl(TraversableLike.scala:255) >> > > > > > > at >> > > > > > > >> > > > >> scala.collection.TraversableLike.filterImpl$(TraversableLike.scala:249) >> > > > > > > at >> > > > > > >> > > scala.collection.AbstractTraversable.filterImpl(Traversable.scala:108) >> > > > > > > at >> > > > scala.collection.TraversableLike.filter(TraversableLike.scala:347) >> > > > > > > at >> > > > > >> scala.collection.TraversableLike.filter$(TraversableLike.scala:347) >> > > > > > > at >> > > > scala.collection.AbstractTraversable.filter(Traversable.scala:108) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:644) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSourceV2(DataSource.scala:728) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.lookupV2Provider(DataFrameWriter.scala:832) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:252) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:236) >> > > > > > > ... 66 elided >> > > > > > > Caused by: java.lang.NoClassDefFoundError: >> > > > > > > org/apache/spark/sql/execution/datasources/FileFormat$class >> > > > > > > at >> > > > > > > >> > > > > >> > > >> org.apache.spark.sql.avro.AvroFileFormat.<init>(AvroFileFormat.scala:44) >> > > > > > > at >> > sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native >> > > > > > Method) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) >> > > > > > > at >> > > java.lang.reflect.Constructor.newInstance(Constructor.java:423) >> > > > > > > at java.lang.Class.newInstance(Class.java:442) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> java.util.ServiceLoader$LazyIterator.nextService(ServiceLoader.java:380) >> > > > > > > ... 86 more >> > > > > > > Caused by: java.lang.ClassNotFoundException: >> > > > > > > org.apache.spark.sql.execution.datasources.FileFormat$class >> > > > > > > at >> java.net.URLClassLoader.findClass(URLClassLoader.java:382) >> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:424) >> > > > > > > at java.lang.ClassLoader.loadClass(ClassLoader.java:357) >> > > > > > > ... 93 more >> > > > > > > >> > > > > > > >> > > > > > > So, tried with 2.12. >> > > > > > > >> > > > > > > ./bin/spark-shell --packages >> > org.apache.spark:spark-avro_2.12:2.4.4 >> > > > > > --conf >> > > > > > > 'spark.serializer=org.apache.spark.serializer.KryoSerializer' >> > > --jars >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> /Users/sivabala/Documents/personal/projects/siva_hudi/hudi/packaging/hudi-spark-bundle/target/hudi-spark-bundle-0.5.1-SNAPSHOT.jar >> > > > > > > >> > > > > > > scala> df.write.format("org.apache.hudi"). >> > > > > > > | options(getQuickstartWriteConfigs). >> > > > > > > | option(PRECOMBINE_FIELD_OPT_KEY, "ts"). >> > > > > > > | option(RECORDKEY_FIELD_OPT_KEY, "uuid"). >> > > > > > > | option(PARTITIONPATH_FIELD_OPT_KEY, >> "partitionpath"). >> > > > > > > | option(TABLE_NAME, tableName). >> > > > > > > | mode(Overwrite). >> > > > > > > | save(basePath); >> > > > > > > 20/01/13 11:42:45 ERROR Executor: Exception in task 0.0 in >> stage >> > > 1.0 >> > > > > (TID >> > > > > > > 2) >> > > > > > > java.lang.NoSuchMethodError: >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.Predef$.refArrayOps([Ljava/lang/Object;)Lscala/collection/mutable/ArrayOps; >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionHelper$.createConverterToAvro(AvroConversionHelper.scala:341) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:46) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:42) >> > > > > > > at >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:127) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441) >> > > > > > > at >> > > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) >> > > > > > > at >> > > > > >> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >> > > > > > > at java.lang.Thread.run(Thread.java:748) >> > > > > > > 20/01/13 11:42:46 WARN TaskSetManager: Lost task 0.0 in stage >> 1.0 >> > > > (TID >> > > > > 2, >> > > > > > > 192.168.1.209, executor driver): java.lang.NoSuchMethodError: >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.Predef$.refArrayOps([Ljava/lang/Object;)Lscala/collection/mutable/ArrayOps; >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionHelper$.createConverterToAvro(AvroConversionHelper.scala:341) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:46) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:42) >> > > > > > > at >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:127) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441) >> > > > > > > at >> > > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) >> > > > > > > at >> > > > > >> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >> > > > > > > at java.lang.Thread.run(Thread.java:748) >> > > > > > > >> > > > > > > 20/01/13 11:42:46 ERROR TaskSetManager: Task 0 in stage 1.0 >> > failed >> > > 1 >> > > > > > times; >> > > > > > > aborting job >> > > > > > > org.apache.spark.SparkException: Job aborted due to stage >> > failure: >> > > > > Task 0 >> > > > > > > in stage 1.0 failed 1 times, most recent failure: Lost task >> 0.0 >> > in >> > > > > stage >> > > > > > > 1.0 (TID 2, 192.168.1.209, executor driver): >> > > > > java.lang.NoSuchMethodError: >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.Predef$.refArrayOps([Ljava/lang/Object;)Lscala/collection/mutable/ArrayOps; >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionHelper$.createConverterToAvro(AvroConversionHelper.scala:341) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:46) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:42) >> > > > > > > at >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > > > > >> > > > >> > org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:127) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441) >> > > > > > > at >> > > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) >> > > > > > > at >> > > > > >> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >> > > > > > > at java.lang.Thread.run(Thread.java:748) >> > > > > > > >> > > > > > > Driver stacktrace: >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:1989) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:1977) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:1976) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) >> > > > > > > at >> > > > scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1976) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:956) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:956) >> > > > > > > at scala.Option.foreach(Option.scala:407) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:956) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2206) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2155) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2144) >> > > > > > > at >> > > org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) >> > > > > > > at >> > > > > > >> > > org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:758) >> > > > > > > at >> > org.apache.spark.SparkContext.runJob(SparkContext.scala:2116) >> > > > > > > at >> > org.apache.spark.SparkContext.runJob(SparkContext.scala:2137) >> > > > > > > at >> > org.apache.spark.SparkContext.runJob(SparkContext.scala:2156) >> > > > > > > at org.apache.spark.rdd.RDD.$anonfun$take$1(RDD.scala:1423) >> > > > > > > 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:388) >> > > > > > > at org.apache.spark.rdd.RDD.take(RDD.scala:1396) >> > > > > > > at >> org.apache.spark.rdd.RDD.$anonfun$isEmpty$1(RDD.scala:1531) >> > > > > > > at >> > > > > > >> > > scala.runtime.java8.JFunction0$mcZ$sp.apply(JFunction0$mcZ$sp.java:23) >> > > > > > > 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:388) >> > > > > > > at org.apache.spark.rdd.RDD.isEmpty(RDD.scala:1531) >> > > > > > > at >> > > > > >> org.apache.spark.api.java.JavaRDDLike.isEmpty(JavaRDDLike.scala:544) >> > > > > > > at >> > > > > > >> > org.apache.spark.api.java.JavaRDDLike.isEmpty$(JavaRDDLike.scala:544) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.api.java.AbstractJavaRDDLike.isEmpty(JavaRDDLike.scala:45) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:141) >> > > > > > > at >> > > > > >> org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:91) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46) >> > > > > > > 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(SparkPlan.scala:173) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:211) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:208) >> > > > > > > at >> > > > > > >> > org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:169) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:110) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:109) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:828) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$4(SQLExecution.scala:100) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:87) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:828) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:309) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:293) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:236) >> > > > > > > ... 66 elided >> > > > > > > Caused by: java.lang.NoSuchMethodError: >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.Predef$.refArrayOps([Ljava/lang/Object;)Lscala/collection/mutable/ArrayOps; >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionHelper$.createConverterToAvro(AvroConversionHelper.scala:341) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:46) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$$anonfun$2.apply(AvroConversionUtils.scala:42) >> > > > > > > at >> > > org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2(RDD.scala:837) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> org.apache.spark.rdd.RDD.$anonfun$mapPartitions$2$adapted(RDD.scala:837) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > > > > > >> > > > > >> > > >> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >> > > > > > > at >> > > org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:349) >> > > > > > > at org.apache.spark.rdd.RDD.iterator(RDD.scala:313) >> > > > > > > at >> > > > org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >> > > > > > > at org.apache.spark.scheduler.Task.run(Task.scala:127) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:441) >> > > > > > > at >> > > > org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1377) >> > > > > > > at >> > > > > > >> > org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:444) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >> > > > > > > at java.lang.Thread.run(Thread.java:748) >> > > > > > > >> > > > > > > Just to unblock my work, I reverted my repo to a commit just >> > before >> > > > > > Udi'ts >> > > > > > > PR(git checkout d9675c4ec0be3f342c30e17a4779c8319b207681) and >> > tried >> > > > > > running >> > > > > > > the same. >> > > > > > > >> > > > > > > ./bin/spark-shell --packages >> com.databricks:spark-avro_2.11:3.2.0 >> > > > > --conf >> > > > > > > 'spark.serializer=org.apache.spark.serializer.KryoSerializer' >> > > --jars >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> /Users/sivabala/Documents/personal/projects/siva_hudi/hudi/packaging/hudi-spark-bundle/target/hudi-spark-bundle-0.5.1-SNAPSHOT.jar >> > > > > > > >> > > > > > > // initial imports. >> > > > > > > .. >> > > > > > > .. >> > > > > > > >> > > > > > > scala> df.write.format("org.apache.hudi"). >> > > > > > > | options(getQuickstartWriteConfigs). >> > > > > > > | option(PRECOMBINE_FIELD_OPT_KEY, "ts"). >> > > > > > > | option(RECORDKEY_FIELD_OPT_KEY, "uuid"). >> > > > > > > | option(PARTITIONPATH_FIELD_OPT_KEY, >> "partitionpath"). >> > > > > > > | option(TABLE_NAME, tableName). >> > > > > > > | mode(Overwrite). >> > > > > > > | save(basePath); >> > > > > > > java.lang.NoSuchMethodError: >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> scala.Predef$.refArrayOps([Ljava/lang/Object;)Lscala/collection/mutable/ArrayOps; >> > > > > > > at >> > > > > > > org.apache.hudi.com >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> .databricks.spark.avro.SchemaConverters$.convertStructToAvro(SchemaConverters.scala:118) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.AvroConversionUtils$.convertStructTypeToAvroSchema(AvroConversionUtils.scala:79) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.hudi.HoodieSparkSqlWriter$.write(HoodieSparkSqlWriter.scala:92) >> > > > > > > at >> > > > > >> org.apache.hudi.DefaultSource.createRelation(DefaultSource.scala:91) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.datasources.SaveIntoDataSourceCommand.run(SaveIntoDataSourceCommand.scala:46) >> > > > > > > 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$1(SparkPlan.scala:173) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SparkPlan.$anonfun$executeQuery$1(SparkPlan.scala:211) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SparkPlan.executeQuery(SparkPlan.scala:208) >> > > > > > > at >> > > > > > >> > org.apache.spark.sql.execution.SparkPlan.execute(SparkPlan.scala:169) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.QueryExecution.toRdd$lzycompute(QueryExecution.scala:110) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.QueryExecution.toRdd(QueryExecution.scala:109) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.$anonfun$runCommand$1(DataFrameWriter.scala:828) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$4(SQLExecution.scala:100) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:160) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:87) >> > > > > > > at >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.runCommand(DataFrameWriter.scala:828) >> > > > > > > at >> > > > > > > >> > > > > > > >> > > > > > >> > > > > >> > > > >> > > >> > >> org.apache.spark.sql.DataFrameWriter.saveToV1Source(DataFrameWriter.scala:309) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:293) >> > > > > > > at >> > > > > >> org.apache.spark.sql.DataFrameWriter.save(DataFrameWriter.scala:236) >> > > > > > > >> > > > > > > >> > > > > > > -- >> > > > > > > Regards, >> > > > > > > -Sivabalan >> > > > > > > >> > > > > > >> > > > > >> > > > > >> > > > > -- >> > > > > Regards, >> > > > > -Sivabalan >> > > > > >> > > > >> > > >> > >> > >> > -- >> > Regards, >> > -Sivabalan >> > >> > > > -- > Regards, > -Sivabalan > -- Regards, -Sivabalan
