Jean-Francis Roy created SPARK-24018:
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Summary: Spark-without-hadoop package fails to create or read
parquet files with snappy compression
Key: SPARK-24018
URL: https://issues.apache.org/jira/browse/SPARK-24018
Project: Spark
Issue Type: Bug
Components: Deploy
Affects Versions: 2.3.0
Reporter: Jean-Francis Roy
On a brand-new installation of Spark 2.3.0 with a user-provided hadoop-2.8.3,
Spark fails to read or write dataframes in parquet format with snappy
compression.
This is due to an incompatibility between the snappy-java version that is
required by parquet (parquet is provided in Spark jars but snappy isn't) and
the version that is available from hadoop-2.8.3.
Steps to reproduce:
* Download and extract hadoop-2.8.3
* Download and extract spark-2.3.0-without-hadoop
* export JAVA_HOME, HADOOP_HOME, SPARK_HOME, PATH
* Following instructions from
https://spark.apache.org/docs/latest/hadoop-provided.html, set
SPARK_DIST_CLASSPATH=$(hadoop classpath) in spark-env.sh
* Start a spark-shell, enter the following:
{code:java}
import spark.implicits._
val df = List(1, 2, 3, 4).toDF
df.write
.format("parquet")
.option("compression", "snappy")
.mode("overwrite")
.save("test.parquet")
{code}
This fails with the following:
{noformat}
java.lang.UnsatisfiedLinkError:
org.xerial.snappy.SnappyNative.maxCompressedLength(I)I at
org.xerial.snappy.SnappyNative.maxCompressedLength(Native Method) at
org.xerial.snappy.Snappy.maxCompressedLength(Snappy.java:316) at
org.apache.parquet.hadoop.codec.SnappyCompressor.compress(SnappyCompressor.java:67)
at
org.apache.hadoop.io.compress.CompressorStream.compress(CompressorStream.java:81)
at
org.apache.hadoop.io.compress.CompressorStream.finish(CompressorStream.java:92)
at
org.apache.parquet.hadoop.CodecFactory$BytesCompressor.compress(CodecFactory.java:112)
at
org.apache.parquet.hadoop.ColumnChunkPageWriteStore$ColumnChunkPageWriter.writePage(ColumnChunkPageWriteStore.java:93)
at
org.apache.parquet.column.impl.ColumnWriterV1.writePage(ColumnWriterV1.java:150)
at
org.apache.parquet.column.impl.ColumnWriterV1.flush(ColumnWriterV1.java:238) at
org.apache.parquet.column.impl.ColumnWriteStoreV1.flush(ColumnWriteStoreV1.java:121)
at
org.apache.parquet.hadoop.InternalParquetRecordWriter.flushRowGroupToStore(InternalParquetRecordWriter.java:167)
at
org.apache.parquet.hadoop.InternalParquetRecordWriter.close(InternalParquetRecordWriter.java:109)
at
org.apache.parquet.hadoop.ParquetRecordWriter.close(ParquetRecordWriter.java:163)
at
org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.close(ParquetOutputWriter.scala:42)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.releaseResources(FileFormatWriter.scala:405)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:396)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:269)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:267)
at
org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1411)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:272)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:197)
at
org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:196)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87) at
org.apache.spark.scheduler.Task.run(Task.scala:109) at
org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345) at
java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at
java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
{noformat}
Downloading snappy-java-1.1.2.6.jar and placing it in Sparks's jar folder
solves the issue.
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