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[SPARK-16813][SQL] Remove private[sql] and private[spark] from catalyst package #14418

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@rxin rxin commented Jul 30, 2016

What changes were proposed in this pull request?

The catalyst 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.catalyst.

How was this patch tested?

N/A - just visibility changes.

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SparkQA commented Jul 30, 2016

Test build #63037 has finished for PR 14418 at commit 5fa81a9.

  • This patch passes all tests.
  • This patch merges cleanly.
  • This patch adds the following public classes (experimental):
    • case class MonotonicallyIncreasingID() extends LeafExpression with Nondeterministic
    • case class SparkPartitionID() extends LeafExpression with Nondeterministic
    • case class AggregateExpression(
    • case class CurrentDatabase() extends LeafExpression with Unevaluable
    • class GenericInternalRow(val values: Array[Any]) extends BaseGenericInternalRow
    • class AbstractScalaRowIterator[T] extends Iterator[T]

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rxin commented Jul 31, 2016

cc @cloud-fan

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LGTM, merging to master!

@asfgit asfgit closed this in 064d91f Jul 31, 2016
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rxin commented Jul 31, 2016

I've also backported this into branch-2.0 to avoid future merge conflicts.

asfgit pushed a commit that referenced this pull request Jul 31, 2016
…st package

The catalyst 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.catalyst.

N/A - just visibility changes.

Author: Reynold Xin <rxin@databricks.com>

Closes #14418 from rxin/SPARK-16813.

(cherry picked from commit 064d91f)
Signed-off-by: Reynold Xin <rxin@databricks.com>
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