I am facing java.io.IOException: s3n://bucket-name : 400 : Bad Request error while loading Redshift data through spark-redshift library:
The Redshift cluster and the s3 bucket both are in mumbai region.
Here is the full error stack:
2017-01-13 13:14:22 WARN TaskSetManager:66 - Lost task 0.0 in stage 0.0 (TID 0, master): java.io.IOException: s3n://bucket-name : 400 : Bad Request
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.processException(Jets3tNativeFileSystemStore.java:453)
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.processException(Jets3tNativeFileSystemStore.java:427)
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.handleException(Jets3tNativeFileSystemStore.java:411)
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.retrieveMetadata(Jets3tNativeFileSystemStore.java:181)
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 org.apache.hadoop.io.retry.RetryInvocationHandler.invokeMethod(RetryInvocationHandler.java:191)
at org.apache.hadoop.io.retry.RetryInvocationHandler.invoke(RetryInvocationHandler.java:102)
at org.apache.hadoop.fs.s3native.$Proxy10.retrieveMetadata(Unknown Source)
at org.apache.hadoop.fs.s3native.NativeS3FileSystem.getFileStatus(NativeS3FileSystem.java:476)
at com.databricks.spark.redshift.RedshiftRecordReader.initialize(RedshiftInputFormat.scala:115)
at com.databricks.spark.redshift.RedshiftFileFormat$$anonfun$buildReader$1.apply(RedshiftFileFormat.scala:92)
at com.databricks.spark.redshift.RedshiftFileFormat$$anonfun$buildReader$1.apply(RedshiftFileFormat.scala:80)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(fileSourceInterfaces.scala:279)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(fileSourceInterfaces.scala:263)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:116)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:91)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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$1.hasNext(WholeStageCodegenExec.scala:370)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$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:370)
at scala.collection.Iterator$$anon$11.hasNext(Iterator.scala:408)
at org.apache.spark.shuffle.sort.BypassMergeSortShuffleWriter.write(BypassMergeSortShuffleWriter.java:125)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:79)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:47)
at org.apache.spark.scheduler.Task.run(Task.scala:86)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
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: org.jets3t.service.impl.rest.HttpException: 400 Bad Request
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRequest(RestStorageService.java:425)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRequest(RestStorageService.java:279)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.performRestHead(RestStorageService.java:1052)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.getObjectImpl(RestStorageService.java:2264)
at org.jets3t.service.impl.rest.httpclient.RestStorageService.getObjectDetailsImpl(RestStorageService.java:2193)
at org.jets3t.service.StorageService.getObjectDetails(StorageService.java:1120)
at org.jets3t.service.StorageService.getObjectDetails(StorageService.java:575)
at org.apache.hadoop.fs.s3native.Jets3tNativeFileSystemStore.retrieveMetadata(Jets3tNativeFileSystemStore.java:174)
... 30 more
And here is my java code for the same:
SparkContext sparkContext = SparkSession.builder().appName("CreditModeling").getOrCreate().sparkContext();
sparkContext.hadoopConfiguration().set("fs.s3a.impl", "org.apache.hadoop.fs.s3native.NativeS3FileSystem");
sparkContext.hadoopConfiguration().set("fs.s3a.awsAccessKeyId", fs_s3a_awsAccessKeyId);
sparkContext.hadoopConfiguration().set("fs.s3a.awsSecretAccessKey", fs_s3a_awsSecretAccessKey);
sparkContext.hadoopConfiguration().set("fs.s3a.endpoint", "s3.ap-south-1.amazonaws.com");
SQLContext sqlContext=new SQLContext(sparkContext);
Dataset dataset= sqlContext
.read()
.format("com.databricks.spark.redshift")
.option("url", redshiftUrl)
.option("query", query)
.option("aws_iam_role", aws_iam_role)
.option("tempdir", "s3a://bucket-name/temp-dir")
.load();
I was able to solve the problem on spark local mode by doing following changes (referred this):
1) I have replaced the jets3t jar to 0.9.4
2) Changed jets3t configuration properties to support the aws4 version bucket as follows:
Jets3tProperties myProperties = Jets3tProperties.getInstance(Constants.JETS3T_PROPERTIES_FILENAME);
myProperties.setProperty("s3service.s3-endpoint", "s3.ap-south-1.amazonaws.com");
myProperties.setProperty("storage-service.request-signature-version", "AWS4-HMAC-SHA256");
myProperties.setProperty("uploads.stream-retry-buffer-size", "2147483646");
But now i am trying to run the job in a clustered mode (spark standalone mode or with a resource manager MESOS) and the error appears again :(
Any help would be appreciated!
Actual Problem:
Updating Jets3tProperties, to support AWS s3 signature version 4, at runtime worked on local mode but not on cluster mode because the properties were only getting updated on the driver JVM but not on any of the executor JVM's.
Solution:
I found a workaround to update the Jets3tProperties on all executors by referring to this link.
By referring to the above link I have put an additional code snippet, to update the Jets3tProperties, inside .foreachPartition() function which will run it for the first partition created on any of the executors.
Here is the code:
Dataset dataset= sqlContext
.read()
.format("com.databricks.spark.redshift")
.option("url", redshiftUrl)
.option("query", query)
.option("aws_iam_role", aws_iam_role)
.option("tempdir", "s3a://bucket-name/temp-dir")
.load();
dataset.foreachPartition(rdd -> {
boolean first=true;
if(first){
Jets3tProperties myProperties =
Jets3tProperties.getInstance(Constants.JETS3T_PROPERTIES_FILENAME);
myProperties.setProperty("s3service.s3-endpoint", "s3.ap-south-1.amazonaws.com");
myProperties
.setProperty("storage-service.request-signature-version", "AWS4-HMAC-SHA256");
myProperties.setProperty("uploads.stream-retry-buffer-size", "2147483646");
first = false;
}
});