Hi Spark users and developers,
Anyone experiences issues in setting hadoop configurations after
SparkContext is initialized? I'm using Spark 1.5.1.
I'm trying to use s3a which requires access and secret key set into hadoop
configuration. I tried to set the properties in the hadoop configuration
from sparktcontext.
sc.hadoopConfiguration.set("fs.s3a.access.key", AWSAccessKeyId)
sc.hadoopConfiguration.set("fs.s3a.secret.key", AWSSecretKey)
val sqlContext = new SQLContext(sc)
val df = sqlContext.read.parquet("s3a://parquetfiles")
So far so good, I saw a job has been submitted to get the parquet schema
and it returns successfully.
and then I tried to do:
df.count
This failed with AmazonClientException:
com.amazonaws.AmazonClientException: Unable to load AWS credentials from
any provider in the chain
at
com.amazonaws.auth.AWSCredentialsProviderChain.getCredentials(AWSCredentialsProviderChain.java:117)
at com.amazonaws.services.s3.AmazonS3Client.invoke(AmazonS3Client.java:3521)
at
com.amazonaws.services.s3.AmazonS3Client.headBucket(AmazonS3Client.java:1031)
at
com.amazonaws.services.s3.AmazonS3Client.doesBucketExist(AmazonS3Client.java:994)
at org.apache.hadoop.fs.s3a.S3AFileSystem.initialize(S3AFileSystem.java:297)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2596)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:91)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2630)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2612)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:370)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:296)
at
org.apache.parquet.hadoop.ParquetFileReader.readFooter(ParquetFileReader.java:384)
at
org.apache.parquet.hadoop.ParquetRecordReader.initializeInternalReader(ParquetRecordReader.java:157)
at
org.apache.parquet.hadoop.ParquetRecordReader.initialize(ParquetRecordReader.java:140)
at
org.apache.spark.rdd.SqlNewHadoopRDD$$anon$1.<init>(SqlNewHadoopRDD.scala:155)
at org.apache.spark.rdd.SqlNewHadoopRDD.compute(SqlNewHadoopRDD.scala:120)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:38)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:297)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:264)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:73)
at
org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:41)
at org.apache.spark.scheduler.Task.run(Task.scala:88)
at org.apache.spark.executor.Executor$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)
Any idea why it can read the schema from the parquet file but not
processing the file? It feels like the hadoop configuration is not sent to
the executor for some reasons...
Thanks,
Jerry
