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authorWeichenXu <WeichenXu123@outlook.com>2016-06-30 23:00:39 +0800
committerCheng Lian <lian@databricks.com>2016-06-30 23:00:39 +0800
commit5344bade8efb6f12aa43fbfbbbc2e3c0c7d16d98 (patch)
tree28713a0ffef28c2f97c523c9f956911bfc3ee2d5
parent5320adc863ca85b489cef79f156392b9da36e53f (diff)
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[SPARK-15820][PYSPARK][SQL] Add Catalog.refreshTable into python API
## What changes were proposed in this pull request? Add Catalog.refreshTable API into python interface for Spark-SQL. ## How was this patch tested? Existing test. Author: WeichenXu <WeichenXu123@outlook.com> Closes #13558 from WeichenXu123/update_python_sql_interface_refreshTable.
-rw-r--r--python/pyspark/sql/catalog.py5
-rw-r--r--sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala2
2 files changed, 6 insertions, 1 deletions
diff --git a/python/pyspark/sql/catalog.py b/python/pyspark/sql/catalog.py
index 3033f147bc..4af930a3cd 100644
--- a/python/pyspark/sql/catalog.py
+++ b/python/pyspark/sql/catalog.py
@@ -232,6 +232,11 @@ class Catalog(object):
"""Removes all cached tables from the in-memory cache."""
self._jcatalog.clearCache()
+ @since(2.0)
+ def refreshTable(self, tableName):
+ """Invalidate and refresh all the cached metadata of the given table."""
+ self._jcatalog.refreshTable(tableName)
+
def _reset(self):
"""(Internal use only) Drop all existing databases (except "default"), tables,
partitions and functions, and set the current database to "default".
diff --git a/sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala b/sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala
index 083a63c98c..91ed9b3258 100644
--- a/sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala
+++ b/sql/core/src/main/scala/org/apache/spark/sql/catalog/Catalog.scala
@@ -214,7 +214,7 @@ abstract class Catalog {
def clearCache(): Unit
/**
- * Invalidate and refresh all the cached the metadata of the given table. For performance reasons,
+ * Invalidate and refresh all the cached metadata of the given table. For performance reasons,
* Spark SQL or the external data source library it uses might cache certain metadata about a
* table, such as the location of blocks. When those change outside of Spark SQL, users should
* call this function to invalidate the cache.