I'm trying to get a pretty large table from mysql so I can manipulate using spark/databricks. I can't get it to load into spark - I have tried taking smaller subsets, but even at the smallest reasonable unit, it still fails to load.
I have tried playing with the wait_timeout and interactive_timeout in mysql, but it doesn't seem to make any difference
I am also loading a smaller (different) table, and that loads just fine.
df_dataset = get_jdbc('raw_data_load', predicates=predicates).select('field1','field2', 'field3','date')
df_dataset = df_dataset.repartition('date')
df_dataset.registerTempTable('raw_data')
I then am trying to cache the data for sql purposes using
%sql
cache table raw_data;
And it goes and chugs for a while and his the database, but always times out after 30-40 minutes and I get the error below
Up until the point it times out, I see
Error in SQL statement: SparkException: Job aborted due to stage failure: Task 0 in stage 30.0 failed 4 times, most recent failure: Lost task 0.3 in stage 30.0 (TID 17075, 10.200.240.63, executor 1): com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link failure
The last packet successfully received from the server was 1,715,280 milliseconds ago. The last packet sent successfully to the server was 1,715,290 milliseconds ago.
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 com.mysql.jdbc.Util.handleNewInstance(Util.java:411)
at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:1121)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2290)
at com.mysql.jdbc.MysqlIO.nextRow(MysqlIO.java:2046)
at com.mysql.jdbc.MysqlIO.readSingleRowSet(MysqlIO.java:3554)
at com.mysql.jdbc.MysqlIO.getResultSet(MysqlIO.java:491)
at com.mysql.jdbc.MysqlIO.readResultsForQueryOrUpdate(MysqlIO.java:3245)
at com.mysql.jdbc.MysqlIO.readAllResults(MysqlIO.java:2413)
at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2836)
at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2825)
at com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:2156)
at com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:2323)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:301)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:336)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:334)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1005)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:936)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:700)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException: Can not read response from server. Expected to read 10 bytes, read 4 bytes before connection was unexpectedly lost.
at com.mysql.jdbc.MysqlIO.readFully(MysqlIO.java:3166)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2271)
... 42 more
Driver stacktrace:
com.databricks.backend.common.rpc.DatabricksExceptions$SQLExecutionException: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 30.0 failed 4 times, most recent failure: Lost task 0.3 in stage 30.0 (TID 17075, 10.200.240.63, executor 1): com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link failure
The last packet successfully received from the server was 1,715,280 milliseconds ago. The last packet sent successfully to the server was 1,715,290 milliseconds ago.
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 com.mysql.jdbc.Util.handleNewInstance(Util.java:411)
at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:1121)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2290)
at com.mysql.jdbc.MysqlIO.nextRow(MysqlIO.java:2046)
at com.mysql.jdbc.MysqlIO.readSingleRowSet(MysqlIO.java:3554)
at com.mysql.jdbc.MysqlIO.getResultSet(MysqlIO.java:491)
at com.mysql.jdbc.MysqlIO.readResultsForQueryOrUpdate(MysqlIO.java:3245)
at com.mysql.jdbc.MysqlIO.readAllResults(MysqlIO.java:2413)
at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2836)
at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2825)
at com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:2156)
at com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:2323)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:301)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:336)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:334)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1005)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:936)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:700)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Caused by: java.io.EOFException: Can not read response from server. Expected to read 10 bytes, read 4 bytes before connection was unexpectedly lost.
at com.mysql.jdbc.MysqlIO.readFully(MysqlIO.java:3166)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2271)
... 42 more
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1442)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1430)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1429)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1429)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:803)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:803)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:803)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1657)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1612)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1601)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1937)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1950)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1963)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1977)
at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:936)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:362)
at org.apache.spark.rdd.RDD.collect(RDD.scala:935)
at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:275)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2409)
at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2408)
at org.apache.spark.sql.Dataset$$anonfun$60.apply(Dataset.scala:2791)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:87)
at org.apache.spark.sql.execution.SQLExecution$.withFileAccessAudit(SQLExecution.scala:53)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:70)
at org.apache.spark.sql.Dataset.withAction(Dataset.scala:2790)
at org.apache.spark.sql.Dataset.count(Dataset.scala:2408)
at org.apache.spark.sql.execution.command.CacheTableCommand.run(cache.scala:45)
at com.databricks.sql.acl.TrustedRunnableCommand$$anonfun$run$1.apply(TrustedRunnableCommand.scala:29)
at com.databricks.sql.acl.TrustedRunnableCommand$$anonfun$run$1.apply(TrustedRunnableCommand.scala:29)
at com.databricks.sql.acl.CheckPermissions$.trusted(CheckPermissions.scala:460)
at com.databricks.sql.acl.TrustedRunnableCommand.run(TrustedRunnableCommand.scala:29)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult$lzycompute(commands.scala:58)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.sideEffectResult(commands.scala:56)
at org.apache.spark.sql.execution.command.ExecutedCommandExec.executeCollect(commands.scala:67)
at org.apache.spark.sql.Dataset.<init>(Dataset.scala:185)
at org.apache.spark.sql.Dataset$.ofRows(Dataset.scala:64)
at org.apache.spark.sql.SparkSession.sql(SparkSession.scala:599)
at org.apache.spark.sql.SQLContext.sql(SQLContext.scala:698)
at com.databricks.backend.daemon.driver.SQLDriverLocal$$anonfun$1.apply(SQLDriverLocal.scala:82)
at com.databricks.backend.daemon.driver.SQLDriverLocal$$anonfun$1.apply(SQLDriverLocal.scala:28)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
at scala.collection.immutable.List.map(List.scala:285)
at com.databricks.backend.daemon.driver.SQLDriverLocal.executeSql(SQLDriverLocal.scala:28)
at com.databricks.backend.daemon.driver.SQLDriverLocal.repl(SQLDriverLocal.scala:128)
at com.databricks.backend.daemon.driver.DriverLocal$$anonfun$execute$2.apply(DriverLocal.scala:230)
at com.databricks.backend.daemon.driver.DriverLocal$$anonfun$execute$2.apply(DriverLocal.scala:211)
at com.databricks.logging.UsageLogging$$anonfun$withAttributionContext$1.apply(UsageLogging.scala:173)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.logging.UsageLogging$class.withAttributionContext(UsageLogging.scala:168)
at com.databricks.backend.daemon.driver.DriverLocal.withAttributionContext(DriverLocal.scala:39)
at com.databricks.logging.UsageLogging$class.withAttributionTags(UsageLogging.scala:206)
at com.databricks.backend.daemon.driver.DriverLocal.withAttributionTags(DriverLocal.scala:39)
at com.databricks.backend.daemon.driver.DriverLocal.execute(DriverLocal.scala:211)
at com.databricks.backend.daemon.driver.DriverWrapper$$anonfun$tryExecutingCommand$2.apply(DriverWrapper.scala:589)
at com.databricks.backend.daemon.driver.DriverWrapper$$anonfun$tryExecutingCommand$2.apply(DriverWrapper.scala:589)
at scala.util.Try$.apply(Try.scala:192)
at com.databricks.backend.daemon.driver.DriverWrapper.tryExecutingCommand(DriverWrapper.scala:584)
at com.databricks.backend.daemon.driver.DriverWrapper.executeCommand(DriverWrapper.scala:488)
at com.databricks.backend.daemon.driver.DriverWrapper.runInnerLoop(DriverWrapper.scala:391)
at com.databricks.backend.daemon.driver.DriverWrapper.runInner(DriverWrapper.scala:348)
at com.databricks.backend.daemon.driver.DriverWrapper.run(DriverWrapper.scala:215)
at java.lang.Thread.run(Thread.java:745)
Caused by: com.mysql.jdbc.exceptions.jdbc4.CommunicationsException: Communications link failure
The last packet successfully received from the server was 1,715,280 milliseconds ago. The last packet sent successfully to the server was 1,715,290 milliseconds ago.
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 com.mysql.jdbc.Util.handleNewInstance(Util.java:411)
at com.mysql.jdbc.SQLError.createCommunicationsException(SQLError.java:1121)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2290)
at com.mysql.jdbc.MysqlIO.nextRow(MysqlIO.java:2046)
at com.mysql.jdbc.MysqlIO.readSingleRowSet(MysqlIO.java:3554)
at com.mysql.jdbc.MysqlIO.getResultSet(MysqlIO.java:491)
at com.mysql.jdbc.MysqlIO.readResultsForQueryOrUpdate(MysqlIO.java:3245)
at com.mysql.jdbc.MysqlIO.readAllResults(MysqlIO.java:2413)
at com.mysql.jdbc.MysqlIO.sqlQueryDirect(MysqlIO.java:2836)
at com.mysql.jdbc.ConnectionImpl.execSQL(ConnectionImpl.java:2825)
at com.mysql.jdbc.PreparedStatement.executeInternal(PreparedStatement.java:2156)
at com.mysql.jdbc.PreparedStatement.executeQuery(PreparedStatement.java:2323)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:301)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:336)
at org.apache.spark.rdd.RDD$$anonfun$8.apply(RDD.scala:334)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:1005)
at org.apache.spark.storage.BlockManager$$anonfun$doPutIterator$1.apply(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.doPut(BlockManager.scala:936)
at org.apache.spark.storage.BlockManager.doPutIterator(BlockManager.scala:996)
at org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:700)
at org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:285)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:322)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
Caused by: java.io.EOFException: Can not read response from server. Expected to read 10 bytes, read 4 bytes before connection was unexpectedly lost.
at com.mysql.jdbc.MysqlIO.readFully(MysqlIO.java:3166)
at com.mysql.jdbc.MysqlIO.nextRowFast(MysqlIO.java:2271)
... 42 more
at com.databricks.backend.daemon.driver.SQLDriverLocal.executeSql(SQLDriverLocal.scala:116)
at com.databricks.backend.daemon.driver.SQLDriverLocal.repl(SQLDriverLocal.scala:128)
at com.databricks.backend.daemon.driver.DriverLocal$$anonfun$execute$2.apply(DriverLocal.scala:230)
at com.databricks.backend.daemon.driver.DriverLocal$$anonfun$execute$2.apply(DriverLocal.scala:211)
at com.databricks.logging.UsageLogging$$anonfun$withAttributionContext$1.apply(UsageLogging.scala:173)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:58)
at com.databricks.logging.UsageLogging$class.withAttributionContext(UsageLogging.scala:168)
at com.databricks.backend.daemon.driver.DriverLocal.withAttributionContext(DriverLocal.scala:39)
at com.databricks.logging.UsageLogging$class.withAttributionTags(UsageLogging.scala:206)
at com.databricks.backend.daemon.driver.DriverLocal.withAttributionTags(DriverLocal.scala:39)
at com.databricks.backend.daemon.driver.DriverLocal.execute(DriverLocal.scala:211)
at com.databricks.backend.daemon.driver.DriverWrapper$$anonfun$tryExecutingCommand$2.apply(DriverWrapper.scala:589)
at com.databricks.backend.daemon.driver.DriverWrapper$$anonfun$tryExecutingCommand$2.apply(DriverWrapper.scala:589)
at scala.util.Try$.apply(Try.scala:192)
at com.databricks.backend.daemon.driver.DriverWrapper.tryExecutingCommand(DriverWrapper.scala:584)
at com.databricks.backend.daemon.driver.DriverWrapper.executeCommand(DriverWrapper.scala:488)
at com.databricks.backend.daemon.driver.DriverWrapper.runInnerLoop(DriverWrapper.scala:391)
at com.databricks.backend.daemon.driver.DriverWrapper.runInner(DriverWrapper.scala:348)
at com.databricks.backend.daemon.driver.DriverWrapper.run(DriverWrapper.scala:215)
at java.lang.Thread.run(Thread.java:745)
With extremely large tables you're going to want to partition the query across your executors. By default the JDBC reader will read the query the parallelize it from the driver. If you have an incrementing, sequential key in the table you can parallelize using the lowerBound, upperBound, and numPartitions parameters. Here's an example taken from https://docs.databricks.com/spark/latest/data-sources/sql-databases.html#python-example
df = spark.read.\
jdbc(url=jdbcUrl, \
table='employees',\
column='emp_no',\
lowerBound=1,\
upperBound=100000, \
numPartitions=100)
df.show()
Having said that, you may want to read and write the data out to Parquet as that will perform better than re-reading from JDBC again.
Related
i want to write a dataframe partitionned :
df.repartition(50).write.mode('overwrite').format("com.databricks.spark.avro").save(data_path)
I chose 50 partitions because the data are light, when everything works well there are 1.7MB per .avro file, so i don't understand why sometimes it fails with this error 'Pyspark Size exceeds Integer.MAX_VALUE'
The files have never reached more than 3mb.
The Exception :
more Caused by: java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE at
sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:869) at
org.apache.spark.storage.DiskStore$$anonfun$getBytes$4.apply(DiskStore.scala:125) at
org.apache.spark.storage.DiskStore$$anonfun$getBytes$4.apply(DiskStore.scala:124) at
org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1337) at
org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:126) at
org.apache.spark.storage.BlockManager.getLocalValues(BlockManager.scala:520) at
org.apache.spark.storage.BlockManager.getOrElseUpdate(BlockManager.scala:764) at
org.apache.spark.rdd.RDD.getOrCompute(RDD.scala:334) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:285) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at
org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at
org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at
org.apache.spark.scheduler.Task.run(Task.scala:108) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142) at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:6
17) ... 1 more End of LogType:stdout action.xml aws-java-sdk-core-1.10.6.jar
aws-java-sdk-kms-1.10.6.jar aws-java-sdk-s3-1.10.6.jar azure-data-lake-
store-sdk-2.1.4.jar azure-keyvault-core-0.8.0.jar azure-storage-5.4.0.jar
commons-lang3-3.4.jar commons-lang3-3.4.jar.backup container_tokens distcp
guava-11.0.2.jar hadoop-aws-2.7.3.2.6.4.194-2.jar hadoop-azure-
2.7.3.2.6.4.194-2.jar hadoop-azure-datalake-2.7.3.2.6.4.194-2.jar hcatalog
hive hive2 job.xml joda-time-2.9.6.jar json-simple-1.1.jar
launch_container.sh lib_20220227155043 logger.sh mapreduce-streaming mr-
framework okhttp-2.4.0.jar okio-1.4.0.jar oozie oozie-hadoop-utils-hadoop-2-
4.2.0.2.6.4.194-2.jar oozie-sharelib-oozie-4.2.0.2.6.4.194-2.jar pig
propagation-conf.xml sharelib.properties spark sqoop tmp ```
When accessing to a Postgresql using the JDBC Datasource of Spark, the property partitionColumn is used as case-insensitive and a exception is thrown
CREATE TABLE data USING org.apache.spark.sql.jdbc OPTIONS (url 'jdbc:postgresql://localhost:5432/postgres', dbtable 'public.datios', lowerBound '0', upperBound '10', partitionColumn 'COD_PERSON', numPartitions '4')
Therefore, executing the query:
SELECT * FROM data
throws the next exception:
Job aborted due to stage failure: Task 1 in stage 9.0 failed 1 times, most recent failure: Lost task 1.0 in stage 9.0 (TID 19, localhost, executor driver): org.postgresql.util.PSQLException: ERROR: column "cod_person" does not exist
Position: 386
at org.postgresql.core.v3.QueryExecutorImpl.receiveErrorResponse(QueryExecutorImpl.java:2433)
at org.postgresql.core.v3.QueryExecutorImpl.processResults(QueryExecutorImpl.java:2178)
at org.postgresql.core.v3.QueryExecutorImpl.execute(QueryExecutorImpl.java:306)
at org.postgresql.jdbc.PgStatement.executeInternal(PgStatement.java:441)
at org.postgresql.jdbc.PgStatement.execute(PgStatement.java:365)
at org.postgresql.jdbc.PgPreparedStatement.executeWithFlags(PgPreparedStatement.java:155)
at org.postgresql.jdbc.PgPreparedStatement.executeQuery(PgPreparedStatement.java:118)
at org.apache.spark.sql.execution.datasources.jdbc.JDBCRDD.compute(JDBCRDD.scala:301)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:88)
at org.apache.spark.scheduler.Task$$anonfun$run$2.apply(Task.scala:109)
at org.apache.spark.scheduler.Task$$anonfun$run$2.apply(Task.scala:109)
at org.apache.spark.scheduler.KerberosFunction$.executeSecure(KerberosFunction.scala:28)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)```
Is there any workaround to use a column name in uppercase to use it as the partitionColumn?
Try enclosing your column name in back-ticks to make it case sensitive.
..partitionColumn `COD_PERSON`
Experts, i am facing a weird problem where my PySpark join of 2 dataframes is failing if i don't use broadcast. I am using Spark 1.6 with Python 2.17
My Join condition is very simple and the volumes are also minimal (in KB). This is generic code and all these names in below expressions are defined as variables containing exact values and working for many other files.
DF = src.withColumnRenamed(srcCol, lkpCol)\
.join(broadcast(lkpDF), lkpCol, 'left')\
.filter(isnull(lkpDF[uniqueID])).coalesce(1)
This piece of code is running fine as long as i am broadcasting my lookup Dataframe. The moment i remove it, i am facing below error-
19/06/21 13:58:59 WARN scheduler.TaskSetManager: Lost task 0.0 in stage 43.0 (TID 1532, svr-m03wn05.c24.hadoop.com, executor 3): java.lang.OutOfMemoryError: Unable to acquire 228 bytes of memory, got 0
at org.apache.spark.memory.MemoryConsumer.allocatePage(MemoryConsumer.java:120)
at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.acquireNewPageIfNecessary(UnsafeExternalSorter.java:332)
at org.apache.spark.util.collection.unsafe.sort.UnsafeExternalSorter.insertRecord(UnsafeExternalSorter.java:347)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.insertRow(UnsafeExternalRowSorter.java:91)
at org.apache.spark.sql.execution.UnsafeExternalRowSorter.sort(UnsafeExternalRowSorter.java:168)
at org.apache.spark.sql.execution.Sort$$anonfun$1.apply(Sort.scala:90)
at org.apache.spark.sql.execution.Sort$$anonfun$1.apply(Sort.scala:64)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$21.apply(RDD.scala:728)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:88)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.CoalescedRDD$$anonfun$compute$1.apply(CoalescedRDD.scala:96)
at org.apache.spark.rdd.CoalescedRDD$$anonfun$compute$1.apply(CoalescedRDD.scala:95)
at scala.collection.Iterator$$anon$13.hasNext(Iterator.scala:371)
at org.apache.spark.sql.execution.columnar.InMemoryRelation$$anonfun$2$$anon$1.hasNext(InMemoryColumnarTableScan.scala:140)
at org.apache.spark.storage.MemoryStore.unrollSafely(MemoryStore.scala:292)
at org.apache.spark.CacheManager.putInBlockManager(CacheManager.scala:171)
at org.apache.spark.CacheManager.getOrCompute(CacheManager.scala:78)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:268)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:66)
at org.apache.spark.scheduler.Task.run(Task.scala:89)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:242)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
19/06/21 13:59:00 WARN server.TransportChannelHandler: Exception in connection from svr-m03wn05.c24.hadoop.com/15.546.349.115:45076
java.io.IOException: Connection reset by peer
at sun.nio.ch.FileDispatcherImpl.read0(Native Method)
at sun.nio.ch.SocketDispatcher.read(SocketDispatcher.java:39)
at sun.nio.ch.IOUtil.readIntoNativeBuffer(IOUtil.java:223)
at sun.nio.ch.IOUtil.read(IOUtil.java:192)
at sun.nio.ch.SocketChannelImpl.read(SocketChannelImpl.java:379)
at io.netty.buffer.PooledUnsafeDirectByteBuf.setBytes(PooledUnsafeDirectByteBuf.java:313)
at io.netty.buffer.AbstractByteBuf.writeBytes(AbstractByteBuf.java:881)
at io.netty.channel.socket.nio.NioSocketChannel.doReadBytes(NioSocketChannel.java:242)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:119)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
at java.lang.Thread.run(Thread.java:745)
19/06/21 13:59:00 WARN cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Container marked as failed: container_e68_1561070366427_23261_01_000004 on host: svr-m03wn05.c24.hadoop.com. Exit status: 52. Diagnostics: Exception from container-launch.
Container id: container_e68_1561070366427_23261_01_000004
Exit code: 52
Stack trace: ExitCodeException exitCode=52:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:604)
at org.apache.hadoop.util.Shell.run(Shell.java:507)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:789)
at org.apache.hadoop.yarn.server.nodemanager.LinuxContainerExecutor.launchContainer(LinuxContainerExecutor.java:399)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Shell output: main : command provided 1
main : run as user is userabc
main : requested yarn user is userabc
Writing to tmp file /data/1/yarn/nm/nmPrivate/application_1561070366427_23261/container_e68_1561070366427_23261_01_000004/container_e68_1561070366427_23261_01_000004.pid.tmp
Container exited with a non-zero exit code 52
19/06/21 13:59:00 ERROR cluster.YarnScheduler: Lost executor 3 on svr-m03wn05.c24.hadoop.com: Container marked as failed: container_e68_1561070366427_23261_01_000004 on host: svr-m03wn05.c24.hadoop.com. Exit status: 52. Diagnostics: Exception from container-launch.
Container id: container_e68_1561070366427_23261_01_000004
Exit code: 52
Stack trace: ExitCodeException exitCode=52:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:604)
at org.apache.hadoop.util.Shell.run(Shell.java:507)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:789)
at org.apache.hadoop.yarn.server.nodemanager.LinuxContainerExecutor.launchContainer(LinuxContainerExecutor.java:399)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:302)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:266)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
Shell output: main : command provided 1
main : run as user is userabc
main : requested yarn user is userabc
Writing to tmp file /data/1/yarn/nm/nmPrivate/application_1561070366427_23261/container_e68_1561070366427_23261_01_000004/container_e68_1561070366427_23261_01_000004.pid.tmp
Getting below error while saving a dataframe as table with parquet mode, before saving table was repartitioned to 400, here is the spark submit arguments being parsed:
--num-executors 12 --executor-cores 8 --executor-memory 12g --driver-
memory 32g --driver-cores 2 --conf spark.sql.shuffle.partitions=400
18/11/05 22:02:04 ERROR FileFormatWriter: Aborting job null.
org.apache.spark.SparkException: Job aborted due to stage failure:
ShuffleMapStage 16 (saveAsTable at testSite.scala:192) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.FetchFailedException:
Too large frame: 3405090943 at org.apache.spark.storage.ShuffleBlockFetcherIterator.throwFetchFailedException(ShuffleBlockFetcherIterator.scala:513)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:444)
at org.apache.spark.storage.ShuffleBlockFetcherIterator.next(ShuffleBlockFetcherIterator.scala:61)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.util.CompletionIterator.hasNext(CompletionIterator.scala:32)
at org.apache.spark.InterruptibleIterator.hasNext(InterruptibleIterator.scala:37)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.sort_addToSorter$(Unknown Source)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source) at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:395) at org.apache.spark.sql.execution.RowIteratorFromScala.advanceNext(RowIterator.scala:83) at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.advancedBufferedToRowWithNullFreeJoinKey(SortMergeJoinExec.scala:793) at org.apache.spark.sql.execution.joins.SortMergeJoinScanner.<init>(SortMergeJoinExec.scala:668) at org.apache.spark.sql.execution.joins.SortMergeJoinExec$$anonfun$doExecute$1.apply(SortMergeJoinExec.scala:204) at org.apache.spark.sql.execution.joins.SortMergeJoinExec$$anonfun$doExecute$1.apply(SortMergeJoinExec.scala:141) at org.apache.spark.rdd.ZippedPartitionsRDD2.compute(ZippedPartitionsRDD.scala:89) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38) at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323) at org.apache.spark.rdd.RDD.iterator(RDD.scala:287) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96) at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53) at org.apache.spark.scheduler.Task.run(Task.scala:108) at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:338) at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745) Caused by: java.lang.IllegalArgumentException: Too large frame: 3405090943
at org.spark_project.guava.base.Preconditions.checkArgument(Preconditions.java:119)
at org.apache.spark.network.util.TransportFrameDecoder.decodeNext(TransportFrameDecoder.java:133)
at org.apache.spark.network.util.TransportFrameDecoder.channelRead(TransportFrameDecoder.java:81)
This question already has answers here:
Spark Error:expected zero arguments for construction of ClassDict (for numpy.core.multiarray._reconstruct)
(6 answers)
Closed 5 years ago.
I have a DataFrame column with an array of strings. I've tried creating a udf and using numpy to permute (unit is the column name):
def permute(row):
return np.random.permutation(row)
udfPermute = udf(permute, ArrayType(StringType()))
print(units.withColumn("shuffled", udfPermute("unit")).head(5))
Py4JJavaError: An error occurred while calling o4246.collectToPython.
: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 871.0 failed 1 times, most recent failure: Lost task 0.0 in stage 871.0 (TID 1224, localhost, executor driver): net.razorvine.pickle.PickleException: expected zero arguments for construction of ClassDict (for numpy.core.multiarray._reconstruct)
at net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707)
at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175)
at net.razorvine.pickle.Unpickler.load(Unpickler.java:99)
at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1$$anonfun$apply$6.apply(BatchEvalPythonExec.scala:156)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1$$anonfun$apply$6.apply(BatchEvalPythonExec.scala:155)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:745)
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1435)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1423)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1422)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1422)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:802)
at scala.Option.foreach(Option.scala:257)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:802)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1650)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1605)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1594)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:628)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1918)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1931)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1944)
at org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:333)
at org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:38)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply$mcI$sp(Dataset.scala:2745)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2742)
at org.apache.spark.sql.Dataset$$anonfun$collectToPython$1.apply(Dataset.scala:2742)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:57)
at org.apache.spark.sql.Dataset.withNewExecutionId(Dataset.scala:2765)
at org.apache.spark.sql.Dataset.collectToPython(Dataset.scala:2742)
at sun.reflect.GeneratedMethodAccessor77.invoke(Unknown Source)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
at py4j.Gateway.invoke(Gateway.java:280)
at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
at py4j.commands.CallCommand.execute(CallCommand.java:79)
at py4j.GatewayConnection.run(GatewayConnection.java:214)
at java.lang.Thread.run(Thread.java:745)
Caused by: net.razorvine.pickle.PickleException: expected zero arguments for construction of ClassDict (for numpy.core.multiarray._reconstruct)
at net.razorvine.pickle.objects.ClassDictConstructor.construct(ClassDictConstructor.java:23)
at net.razorvine.pickle.Unpickler.load_reduce(Unpickler.java:707)
at net.razorvine.pickle.Unpickler.dispatch(Unpickler.java:175)
at net.razorvine.pickle.Unpickler.load(Unpickler.java:99)
at net.razorvine.pickle.Unpickler.loads(Unpickler.java:112)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1$$anonfun$apply$6.apply(BatchEvalPythonExec.scala:156)
at org.apache.spark.sql.execution.python.BatchEvalPythonExec$$anonfun$doExecute$1$$anonfun$apply$6.apply(BatchEvalPythonExec.scala:155)
at scala.collection.Iterator$$anon$12.nextCur(Iterator.scala:434)
at scala.collection.Iterator$$anon$12.hasNext(Iterator.scala:440)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIterator.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anonfun$8$$anon$1.hasNext(WholeStageCodegenExec.scala:377)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:231)
at org.apache.spark.sql.execution.SparkPlan$$anonfun$2.apply(SparkPlan.scala:225)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
at org.apache.spark.rdd.RDD$$anonfun$mapPartitionsInternal$1$$anonfun$apply$25.apply(RDD.scala:826)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:323)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:287)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
at org.apache.spark.scheduler.Task.run(Task.scala:99)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:282)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
... 1 more
In [161]:
How can I accomplish this?
You are returning a numpy array, you need to return a list instead.
Change your UDF as below and it should work.
def permute(row):
return np.random.permutation(row).tolist()