Github user watermen commented on a diff in the pull request:
https://github.com/apache/spark/pull/8125#discussion_r37258258
--- Diff:
sql/hive/src/main/scala/org/apache/spark/sql/hive/TableReader.scala ---
@@ -283,7 +284,7 @@ class HadoopTableReader(
_minSplitsPerRDD)
// Only take the value (skip the key) because Hive works only with
values.
- rdd.map(_._2)
+ CombineSmallFile.combineWithPath(rdd, sc, path).map(_._2)
--- End diff --
@liancheng We can do this except `s3`, because if `your application needs
to access large datasets, the fastest way to do that is to load them from
Amazon S3 or an Amazon EBS device into an instance of the Hadoop Distributed
File System (HDFS) on your nodes.` which write in `ec2-scripts.md`
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