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| author | Reynold Xin <rxin@databricks.com> | 2016-08-09 18:22:14 +0800 |
|---|---|---|
| committer | Wenchen Fan <wenchen@databricks.com> | 2016-08-09 18:22:14 +0800 |
| commit | 511f52f8423e151b0d0133baf040d34a0af3d422 (patch) | |
| tree | 390a5f9f3bee846625994a447238d9579e17051f /sql/hive/src | |
| parent | 62e62124419f3fa07b324f5e42feb2c5b4fde715 (diff) | |
| download | spark-511f52f8423e151b0d0133baf040d34a0af3d422.tar.gz spark-511f52f8423e151b0d0133baf040d34a0af3d422.tar.bz2 spark-511f52f8423e151b0d0133baf040d34a0af3d422.zip | |
[SPARK-16964][SQL] Remove private[sql] and private[spark] from sql.execution package
## What changes were proposed in this pull request?
This package is meant to be internal, and as a result it does not make sense to mark things as private[sql] or private[spark]. It simply makes debugging harder when Spark developers need to inspect the plans at runtime.
This patch removes all private[sql] and private[spark] visibility modifiers in org.apache.spark.sql.execution.
## How was this patch tested?
N/A - just visibility changes.
Author: Reynold Xin <rxin@databricks.com>
Closes #14554 from rxin/remote-private.
Diffstat (limited to 'sql/hive/src')
| -rw-r--r-- | sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala | 2 |
1 files changed, 1 insertions, 1 deletions
diff --git a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala index cc3e74b4e8..a716a3eab6 100644 --- a/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala +++ b/sql/hive/src/main/scala/org/apache/spark/sql/hive/execution/HiveTableScanExec.scala @@ -54,7 +54,7 @@ case class HiveTableScanExec( require(partitionPruningPred.isEmpty || relation.hiveQlTable.isPartitioned, "Partition pruning predicates only supported for partitioned tables.") - private[sql] override lazy val metrics = Map( + override lazy val metrics = Map( "numOutputRows" -> SQLMetrics.createMetric(sparkContext, "number of output rows")) override def producedAttributes: AttributeSet = outputSet ++ |