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From Uthayan Suthakar <uthayan.sutha...@gmail.com>
Subject native snappy library not available: this version of libhadoop was built without snappy support.
Date Tue, 04 Oct 2016 19:59:20 GMT
Hello guys,

I have a job that reads compressed (Snappy) data but when I run the job, it
is throwing an error "native snappy library not available: this version
of libhadoop was built without snappy support".
.
I followed this instruction but it did not resolve the issue:
https://community.hortonworks.com/questions/18903/this-
version-of-libhadoop-was-built-without-snappy.html

The check native command show that snappy is installed.
hadoop checknative
16/10/04 21:01:30 INFO bzip2.Bzip2Factory: Successfully loaded &
initialized native-bzip2 library system-native
16/10/04 21:01:30 INFO zlib.ZlibFactory: Successfully loaded & initialized
native-zlib library
Native library checking:
hadoop:  true /usr/lib/hadoop/lib/native/libhadoop.so.1.0.0
zlib:    true /lib64/libz.so.1
snappy:  true /usr/lib/hadoop/lib/native/libsnappy.so.1
lz4:     true revision:99
bzip2:   true /lib64/libbz2.so.1
openssl: true /usr/lib64/libcrypto.so

I also have a code in the job to check whether native snappy is loaded,
which is returning true.

Now, I have no idea why I'm getting this error. Also, I had no issue
reading Snappy data using MapReduce job on the same cluster, Could anyone
tell me what is wrong?



Thank you.

Stack:


java.lang.RuntimeException: native snappy library not available: this
version of libhadoop was built without snappy support.
        at org.apache.hadoop.io.compress.SnappyCodec.checkNativeCodeLoaded(
SnappyCodec.java:65)
        at org.apache.hadoop.io.compress.SnappyCodec.getDecompressorType(
SnappyCodec.java:193)
        at org.apache.hadoop.io.compress.CodecPool.getDecompressor(
CodecPool.java:178)
        at org.apache.hadoop.mapred.LineRecordReader.<init>(
LineRecordReader.java:111)
        at org.apache.hadoop.mapred.TextInputFormat.getRecordReader(
TextInputFormat.java:67)
        at org.apache.spark.rdd.HadoopRDD$$anon$1.<init>(
HadoopRDD.scala:237)
        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:208)
        at org.apache.spark.rdd.HadoopRDD.compute(HadoopRDD.scala:101)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
        at org.apache.spark.rdd.MapPartitionsRDD.compute(
MapPartitionsRDD.scala:38)
        at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:306)
        at org.apache.spark.rdd.RDD.iterator(RDD.scala:270)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(
ShuffleMapTask.scala:73)
        at org.apache.spark.scheduler.ShuffleMapTask.runTask(
ShuffleMapTask.scala:41)
        at org.apache.spark.scheduler.Task.run(Task.scala:89)
        at org.apache.spark.executor.Executor$TaskRunner.run(
Executor.scala:214)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(
ThreadPoolExecutor.java:1145)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(
ThreadPoolExecutor.java:615)
        at java.lang.Thread.run(Thread.java:745)

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