Thanks, Michael and Akhil. Yes, it worked with Spark 1.3.1 along with AWS EMR AMI 3.7. Sorry I didn't update the status.
On Mon, Jun 1, 2015 at 5:17 AM, Michael Armbrust <mich...@databricks.com> wrote: > This sounds like a problem that was fixed in Spark 1.3.1. > > https://issues.apache.org/jira/browse/SPARK-6351 > > On Mon, Jun 1, 2015 at 5:44 PM, Akhil Das <ak...@sigmoidanalytics.com> > wrote: >> >> This thread has various methods on accessing S3 from spark, it might help >> you. >> >> Thanks >> Best Regards >> >> On Sun, May 24, 2015 at 8:03 AM, ogoh <oke...@gmail.com> wrote: >>> >>> >>> Hello, >>> I am using Spark1.3 in AWS. >>> SparkSQL can't recognize Hive external table on S3. >>> The following is the error message. >>> I appreciate any help. >>> Thanks, >>> Okehee >>> ------ >>> 15/05/24 01:02:18 ERROR thriftserver.SparkSQLDriver: Failed in [select >>> count(*) from api_search where pdate='2015-05-08'] >>> java.lang.IllegalArgumentException: Wrong FS: >>> >>> s3://test-emr/datawarehouse/api_s3_perf/api_search/pdate=2015-05-08/phour=00, >>> expected: hdfs://10.128.193.211:9000 >>> at org.apache.hadoop.fs.FileSystem.checkPath(FileSystem.java:647) >>> at >>> org.apache.hadoop.fs.FileSystem.makeQualified(FileSystem.java:467) >>> at >>> >>> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:252) >>> at >>> >>> org.apache.spark.sql.parquet.ParquetRelation2$MetadataCache$$anonfun$6.apply(newParquet.scala:251) >>> at >>> >>> scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244) >>> >>> >>> >>> >>> >>> -- >>> View this message in context: >>> http://apache-spark-user-list.1001560.n3.nabble.com/SparkSQL-can-t-read-S3-path-for-hive-external-table-tp23002.html >>> Sent from the Apache Spark User List mailing list archive at Nabble.com. >>> >>> --------------------------------------------------------------------- >>> To unsubscribe, e-mail: user-unsubscr...@spark.apache.org >>> For additional commands, e-mail: user-h...@spark.apache.org >>> >> > --------------------------------------------------------------------- To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
