Finally I was able to solve this issue by setting this conf. "spark.driver.extraJavaOptions=-Dorg.xerial.snappy.tempdir=/my_user/temp_ folder"
Thanks all! On Sat, 8 Jul 2023 at 3:45 AM, Brian Huynh <brianhuy...@gmail.com> wrote: > Hi Khalid, > > Elango mentioned the file is working fine in our another environment with > the same driver and executor memory > > Brian > > On Jul 7, 2023, at 10:18 AM, Khalid Mammadov <khalidmammad...@gmail.com> > wrote: > > > > Perhaps that parquet file is corrupted or got that is in that folder? > To check, try to read that file with pandas or other tools to see if you > can read without Spark. > > On Wed, 5 Jul 2023, 07:25 elango vaidyanathan, <elango...@gmail.com> > wrote: > >> >> Hi team, >> >> Any updates on this below issue >> >> On Mon, 3 Jul 2023 at 6:18 PM, elango vaidyanathan <elango...@gmail.com> >> wrote: >> >>> >>> >>> Hi all, >>> >>> I am reading a parquet file like this and it gives >>> java.lang.IllegalArgumentException. >>> However i can work with other parquet files (such as nyc taxi parquet >>> files) without any issue. I have copied the full error log as well. Can you >>> please check once and let me know how to fix this? >>> >>> import pyspark >>> >>> from pyspark.sql import SparkSession >>> >>> spark=SparkSession.builder.appName("testPyspark").config("spark.executor.memory", >>> "20g").config("spark.driver.memory", "50g").getOrCreate() >>> >>> df=spark.read.parquet("/data/202301/account_cycle") >>> >>> df.printSchema() # worksfine >>> >>> df.count() #worksfine >>> >>> df.show()# getting below error >>> >>> >>> df.show() >>> >>> 23/07/03 18:07:20 INFO FileSourceStrategy: Pushed Filters: >>> >>> 23/07/03 18:07:20 INFO FileSourceStrategy: Post-Scan Filters: >>> >>> 23/07/03 18:07:20 INFO FileSourceStrategy: Output Data Schema: >>> struct<account_cycle_serial: bigint, account_serial: bigint, >>> account_status: string, currency_code: string, opened_dt: date ... 30 more >>> fields> >>> >>> 23/07/03 18:07:20 INFO MemoryStore: Block broadcast_19 stored as values >>> in memory (estimated size 540.6 KiB, free 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO MemoryStore: Block broadcast_19_piece0 stored as >>> bytes in memory (estimated size 46.0 KiB, free 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO BlockManagerInfo: Added broadcast_19_piece0 in >>> memory on mynode:41055 (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO SparkContext: Created broadcast 19 from >>> showString at NativeMethodAccessorImpl.java:0 >>> >>> 23/07/03 18:07:20 INFO FileSourceScanExec: Planning scan with bin >>> packing, max size: 134217728 bytes, open cost is considered as scanning >>> 4194304 bytes. >>> >>> 23/07/03 18:07:20 INFO SparkContext: Starting job: showString at >>> NativeMethodAccessorImpl.java:0 >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Got job 13 (showString at >>> NativeMethodAccessorImpl.java:0) with 1 output partitions >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Final stage: ResultStage 14 >>> (showString at NativeMethodAccessorImpl.java:0) >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Parents of final stage: List() >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Missing parents: List() >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Submitting ResultStage 14 >>> (MapPartitionsRDD[42] at showString at NativeMethodAccessorImpl.java:0), >>> which has no missing parents >>> >>> 23/07/03 18:07:20 INFO MemoryStore: Block broadcast_20 stored as values >>> in memory (estimated size 38.1 KiB, free 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO MemoryStore: Block broadcast_20_piece0 stored as >>> bytes in memory (estimated size 10.5 KiB, free 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO BlockManagerInfo: Added broadcast_20_piece0 in >>> memory on mynode:41055 (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:20 INFO SparkContext: Created broadcast 20 from broadcast >>> at DAGScheduler.scala:1478 >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Submitting 1 missing tasks from >>> ResultStage 14 (MapPartitionsRDD[42] at showString at >>> NativeMethodAccessorImpl.java:0) (first 15 tasks are for partitions >>> Vector(0)) >>> >>> 23/07/03 18:07:20 INFO TaskSchedulerImpl: Adding task set 14.0 with 1 >>> tasks resource profile 0 >>> >>> 23/07/03 18:07:20 INFO TaskSetManager: Starting task 0.0 in stage 14.0 >>> (TID 48) (mynode, executor driver, partition 0, PROCESS_LOCAL, 4890 bytes) >>> taskResourceAssignments Map() >>> >>> 23/07/03 18:07:20 INFO Executor: Running task 0.0 in stage 14.0 (TID 48) >>> >>> 23/07/03 18:07:20 INFO FileScanRDD: Reading File path: >>> file:///data/202301/account_cycle/account_cycle-202301-53.parquet, range: >>> 0-134217728, partition values: [empty row] >>> >>> 23/07/03 18:07:20 ERROR Executor: Exception in task 0.0 in stage 14.0 >>> (TID 48) >>> >>> java.lang.IllegalArgumentException >>> >>> at java.nio.Buffer.limit(Buffer.java:275) >>> >>> at org.xerial.snappy.Snappy.uncompress(Snappy.java:553) >>> >>> at >>> org.apache.parquet.hadoop.codec.SnappyDecompressor.decompress(SnappyDecompressor.java:71) >>> >>> at >>> org.apache.parquet.hadoop.codec.NonBlockedDecompressorStream.read(NonBlockedDecompressorStream.java:51) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:195) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:169) >>> >>> at >>> org.apache.parquet.bytes.BytesInput$StreamBytesInput.toByteArray(BytesInput.java:286) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toByteBuffer(BytesInput.java:237) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toInputStream(BytesInput.java:246) >>> >>> at >>> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary.<init>(PlainValuesDictionary.java:154) >>> >>> at >>> org.apache.parquet.column.Encoding$1.initDictionary(Encoding.java:96) >>> >>> at >>> org.apache.parquet.column.Encoding$5.initDictionary(Encoding.java:163) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.<init>(VectorizedColumnReader.java:114) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:352) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:293) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) >>> >>> at >>> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >>> >>> at >>> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >>> >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) >>> >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:131) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) >>> >>> at >>> org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) >>> >>> 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:750) >>> >>> 23/07/03 18:07:20 WARN TaskSetManager: Lost task 0.0 in stage 14.0 (TID >>> 48) (mynode executor driver): java.lang.IllegalArgumentException >>> >>> at java.nio.Buffer.limit(Buffer.java:275) >>> >>> at org.xerial.snappy.Snappy.uncompress(Snappy.java:553) >>> >>> at >>> org.apache.parquet.hadoop.codec.SnappyDecompressor.decompress(SnappyDecompressor.java:71) >>> >>> at >>> org.apache.parquet.hadoop.codec.NonBlockedDecompressorStream.read(NonBlockedDecompressorStream.java:51) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:195) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:169) >>> >>> at >>> org.apache.parquet.bytes.BytesInput$StreamBytesInput.toByteArray(BytesInput.java:286) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toByteBuffer(BytesInput.java:237) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toInputStream(BytesInput.java:246) >>> >>> at >>> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary.<init>(PlainValuesDictionary.java:154) >>> >>> at >>> org.apache.parquet.column.Encoding$1.initDictionary(Encoding.java:96) >>> >>> at >>> org.apache.parquet.column.Encoding$5.initDictionary(Encoding.java:163) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.<init>(VectorizedColumnReader.java:114) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:352) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:293) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) >>> >>> at >>> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >>> >>> at >>> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >>> >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) >>> >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:131) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) >>> >>> at >>> org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >>> >>> at java.lang.Thread.run(Thread.java:750) >>> >>> 23/07/03 18:07:20 ERROR TaskSetManager: Task 0 in stage 14.0 failed 1 >>> times; aborting job >>> >>> 23/07/03 18:07:20 INFO TaskSchedulerImpl: Removed TaskSet 14.0, whose >>> tasks have all completed, from pool >>> >>> 23/07/03 18:07:20 INFO TaskSchedulerImpl: Cancelling stage 14 >>> >>> 23/07/03 18:07:20 INFO TaskSchedulerImpl: Killing all running tasks in >>> stage 14: Stage cancelled >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: ResultStage 14 (showString at >>> NativeMethodAccessorImpl.java:0) failed in 0.278 s due to Job aborted due >>> to stage failure: Task 0 in stage 14.0 failed 1 times, most recent failure: >>> Lost task 0.0 in stage 14.0 (TID 48) (mynode executor driver): >>> java.lang.IllegalArgumentException >>> >>> at java.nio.Buffer.limit(Buffer.java:275) >>> >>> at org.xerial.snappy.Snappy.uncompress(Snappy.java:553) >>> >>> at >>> org.apache.parquet.hadoop.codec.SnappyDecompressor.decompress(SnappyDecompressor.java:71) >>> >>> at >>> org.apache.parquet.hadoop.codec.NonBlockedDecompressorStream.read(NonBlockedDecompressorStream.java:51) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:195) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:169) >>> >>> at >>> org.apache.parquet.bytes.BytesInput$StreamBytesInput.toByteArray(BytesInput.java:286) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toByteBuffer(BytesInput.java:237) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toInputStream(BytesInput.java:246) >>> >>> at >>> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary.<init>(PlainValuesDictionary.java:154) >>> >>> at >>> org.apache.parquet.column.Encoding$1.initDictionary(Encoding.java:96) >>> >>> at >>> org.apache.parquet.column.Encoding$5.initDictionary(Encoding.java:163) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.<init>(VectorizedColumnReader.java:114) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:352) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:293) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) >>> >>> at >>> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >>> >>> at >>> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >>> >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) >>> >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:131) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) >>> >>> at >>> org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) >>> >>> 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:750) >>> >>> Driver stacktrace: >>> >>> 23/07/03 18:07:20 INFO DAGScheduler: Job 13 failed: showString at >>> NativeMethodAccessorImpl.java:0, took 0.280998 s >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_5_piece0 on >>> mynode:41055 in memory (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_16_piece0 on >>> mynode:41055 in memory (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_10_piece0 on >>> mynode:41055 in memory (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_15_piece0 on >>> mynode:41055 in memory (size: 46.9 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_18_piece0 on >>> mynode:41055 in memory (size: 46.9 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_8_piece0 on >>> mynode:41055 in memory (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_6_piece0 on >>> mynode:41055 in memory (size: 46.9 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_11_piece0 on >>> mynode:41055 in memory (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_14_piece0 on >>> mynode:41055 in memory (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_12_piece0 on >>> mynode:41055 in memory (size: 46.9 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_7_piece0 on >>> mynode:41055 in memory (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_13_piece0 on >>> mynode:41055 in memory (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_3_piece0 on >>> mynode:41055 in memory (size: 5.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_17_piece0 on >>> mynode:41055 in memory (size: 10.5 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_4_piece0 on >>> mynode:41055 in memory (size: 46.0 KiB, free: 26.5 GiB) >>> >>> 23/07/03 18:07:21 INFO BlockManagerInfo: Removed broadcast_9_piece0 on >>> mynode:41055 in memory (size: 46.9 KiB, free: 26.5 GiB) >>> >>> Traceback (most recent call last): >>> >>> File "<stdin>", line 1, in <module> >>> >>> File >>> "/nix/store/jkyamgd3bd97bjy8vd4nawlnyz23lk2w-spark-3.2.2/lib/spark-3.2.2/python/pyspark/sql/dataframe.py", >>> line 494, in show >>> >>> print(self._jdf.showString(n, 20, vertical)) >>> >>> File >>> "/nix/store/jkyamgd3bd97bjy8vd4nawlnyz23lk2w-spark-3.2.2/lib/spark-3.2.2/python/lib/py4j-0.10.9.5-src.zip/py4j/java_gateway.py", >>> line 1321, in __call__ >>> >>> File >>> "/nix/store/jkyamgd3bd97bjy8vd4nawlnyz23lk2w-spark-3.2.2/lib/spark-3.2.2/python/pyspark/sql/utils.py", >>> line 111, in deco >>> >>> return f(*a, **kw) >>> >>> File >>> "/nix/store/jkyamgd3bd97bjy8vd4nawlnyz23lk2w-spark-3.2.2/lib/spark-3.2.2/python/lib/py4j-0.10.9.5-src.zip/py4j/protocol.py", >>> line 326, in get_return_value >>> >>> py4j.protocol.Py4JJavaError: An error occurred while calling >>> o64.showString. >>> >>> : org.apache.spark.SparkException: Job aborted due to stage failure: >>> Task 0 in stage 14.0 failed 1 times, most recent failure: Lost task 0.0 in >>> stage 14.0 (TID 48) (mynode executor driver): >>> java.lang.IllegalArgumentException >>> >>> at java.nio.Buffer.limit(Buffer.java:275) >>> >>> at org.xerial.snappy.Snappy.uncompress(Snappy.java:553) >>> >>> at >>> org.apache.parquet.hadoop.codec.SnappyDecompressor.decompress(SnappyDecompressor.java:71) >>> >>> at >>> org.apache.parquet.hadoop.codec.NonBlockedDecompressorStream.read(NonBlockedDecompressorStream.java:51) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:195) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:169) >>> >>> at >>> org.apache.parquet.bytes.BytesInput$StreamBytesInput.toByteArray(BytesInput.java:286) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toByteBuffer(BytesInput.java:237) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toInputStream(BytesInput.java:246) >>> >>> at >>> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary.<init>(PlainValuesDictionary.java:154) >>> >>> at >>> org.apache.parquet.column.Encoding$1.initDictionary(Encoding.java:96) >>> >>> at >>> org.apache.parquet.column.Encoding$5.initDictionary(Encoding.java:163) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.<init>(VectorizedColumnReader.java:114) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:352) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:293) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) >>> >>> at >>> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >>> >>> at >>> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >>> >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) >>> >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:131) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) >>> >>> at >>> org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >>> >>> at java.lang.Thread.run(Thread.java:750) >>> >>> Driver stacktrace: >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.failJobAndIndependentStages(DAGScheduler.scala:2454) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2(DAGScheduler.scala:2403) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.$anonfun$abortStage$2$adapted(DAGScheduler.scala:2402) >>> >>> at >>> scala.collection.mutable.ResizableArray.foreach(ResizableArray.scala:62) >>> >>> at >>> scala.collection.mutable.ResizableArray.foreach$(ResizableArray.scala:55) >>> >>> at >>> scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:49) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:2402) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1(DAGScheduler.scala:1160) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.$anonfun$handleTaskSetFailed$1$adapted(DAGScheduler.scala:1160) >>> >>> at scala.Option.foreach(Option.scala:407) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:1160) >>> >>> at >>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:2642) >>> >>> at >>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2584) >>> >>> at >>> org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:2573) >>> >>> at >>> org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:49) >>> >>> at >>> org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:938) >>> >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2214) >>> >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2235) >>> >>> at org.apache.spark.SparkContext.runJob(SparkContext.scala:2254) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:492) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.executeTake(SparkPlan.scala:445) >>> >>> at >>> org.apache.spark.sql.execution.CollectLimitExec.executeCollect(limit.scala:48) >>> >>> at >>> org.apache.spark.sql.Dataset.collectFromPlan(Dataset.scala:3715) >>> >>> at >>> org.apache.spark.sql.Dataset.$anonfun$head$1(Dataset.scala:2728) >>> >>> at >>> org.apache.spark.sql.Dataset.$anonfun$withAction$1(Dataset.scala:3706) >>> >>> at >>> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$5(SQLExecution.scala:103) >>> >>> at >>> org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:163) >>> >>> at >>> org.apache.spark.sql.execution.SQLExecution$.$anonfun$withNewExecutionId$1(SQLExecution.scala:90) >>> >>> at >>> org.apache.spark.sql.SparkSession.withActive(SparkSession.scala:775) >>> >>> at >>> org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:64) >>> >>> at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3704) >>> >>> at org.apache.spark.sql.Dataset.head(Dataset.scala:2728) >>> >>> at org.apache.spark.sql.Dataset.take(Dataset.scala:2935) >>> >>> at org.apache.spark.sql.Dataset.getRows(Dataset.scala:287) >>> >>> at org.apache.spark.sql.Dataset.showString(Dataset.scala:326) >>> >>> at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) >>> >>> at >>> sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) >>> >>> 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:282) >>> >>> at >>> py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) >>> >>> at py4j.commands.CallCommand.execute(CallCommand.java:79) >>> >>> at >>> py4j.ClientServerConnection.waitForCommands(ClientServerConnection.java:182) >>> >>> at >>> py4j.ClientServerConnection.run(ClientServerConnection.java:106) >>> >>> at java.lang.Thread.run(Thread.java:750) >>> >>> Caused by: java.lang.IllegalArgumentException >>> >>> at java.nio.Buffer.limit(Buffer.java:275) >>> >>> at org.xerial.snappy.Snappy.uncompress(Snappy.java:553) >>> >>> at >>> org.apache.parquet.hadoop.codec.SnappyDecompressor.decompress(SnappyDecompressor.java:71) >>> >>> at >>> org.apache.parquet.hadoop.codec.NonBlockedDecompressorStream.read(NonBlockedDecompressorStream.java:51) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:195) >>> >>> at java.io.DataInputStream.readFully(DataInputStream.java:169) >>> >>> at >>> org.apache.parquet.bytes.BytesInput$StreamBytesInput.toByteArray(BytesInput.java:286) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toByteBuffer(BytesInput.java:237) >>> >>> at >>> org.apache.parquet.bytes.BytesInput.toInputStream(BytesInput.java:246) >>> >>> at >>> org.apache.parquet.column.values.dictionary.PlainValuesDictionary$PlainLongDictionary.<init>(PlainValuesDictionary.java:154) >>> >>> at >>> org.apache.parquet.column.Encoding$1.initDictionary(Encoding.java:96) >>> >>> at >>> org.apache.parquet.column.Encoding$5.initDictionary(Encoding.java:163) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedColumnReader.<init>(VectorizedColumnReader.java:114) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.checkEndOfRowGroup(VectorizedParquetRecordReader.java:352) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextBatch(VectorizedParquetRecordReader.java:293) >>> >>> at >>> org.apache.spark.sql.execution.datasources.parquet.VectorizedParquetRecordReader.nextKeyValue(VectorizedParquetRecordReader.java:196) >>> >>> at >>> org.apache.spark.sql.execution.datasources.RecordReaderIterator.hasNext(RecordReaderIterator.scala:39) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:191) >>> >>> at >>> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:104) >>> >>> at >>> org.apache.spark.sql.execution.FileSourceScanExec$$anon$1.hasNext(DataSourceScanExec.scala:522) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.columnartorow_nextBatch_0$(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown >>> Source) >>> >>> at >>> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43) >>> >>> at >>> org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:759) >>> >>> at >>> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:350) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:898) >>> >>> at >>> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52) >>> >>> at >>> org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:373) >>> >>> at org.apache.spark.rdd.RDD.iterator(RDD.scala:337) >>> >>> at >>> org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90) >>> >>> at org.apache.spark.scheduler.Task.run(Task.scala:131) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:506) >>> >>> at >>> org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1491) >>> >>> at >>> org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:509) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149) >>> >>> at >>> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624) >>> >>> ... 1 more >>> >>> >>> >>> >>> >>> Thanks, >>> >>> Elango >>> >>> >>> -- >>> >>> Thanks, >>> Elango >>> >> -- >> >> Thanks, >> Elango >> > -- Thanks, Elango