You are viewing a plain text version of this content. The canonical link for it is here.
Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/08/12 08:56:21 UTC

[GitHub] [spark] dcoliversun commented on a diff in pull request #37490: [SPARK-40051][PYTHON][SQL][DOCS] Make pyspark.sql.catalog examples self-contained

dcoliversun commented on code in PR #37490:
URL: https://github.com/apache/spark/pull/37490#discussion_r944256156


##########
python/pyspark/sql/catalog.py:
##########
@@ -674,59 +875,267 @@ def registerFunction(
         warnings.warn("Deprecated in 2.3.0. Use spark.udf.register instead.", FutureWarning)
         return self._sparkSession.udf.register(name, f, returnType)
 
-    @since(2.0)
     def isCached(self, tableName: str) -> bool:
-        """Returns true if the table is currently cached in-memory.
+        """
+        Returns true if the table is currently cached in-memory.
+
+        .. versionadded:: 2.0.0
+
+        Parameters
+        ----------
+        tableName : str
+            name of the table to get.
+
+            .. versionchanged:: 3.4.0
+                Allow ``tableName`` to be qualified with catalog name.
+
+        Returns
+        -------
+        bool
+
+        Examples
+        --------
+        >>> _ = spark.sql("DROP TABLE IF EXISTS tbl1")
+        >>> _ = spark.sql("CREATE TABLE tbl1 (name STRING, age INT) USING parquet")
+        >>> spark.catalog.cacheTable("tbl1")
+        >>> spark.catalog.isCached("tbl1")
+        True
+
+        Throw an analysis exception when the table does not exists.
 
-        .. versionchanged:: 3.4
-           Allowed ``tableName`` to be qualified with catalog name.
+        >>> spark.catalog.isCached("not_existing_table")
+        Traceback (most recent call last):
+            ...
+        pyspark.sql.utils.AnalysisException: ...

Review Comment:
   doctest will check result match or not. If only write `AnalysisException`, doctest will fail.



-- 
This is an automated message from the Apache Git Service.
To respond to the message, please log on to GitHub and use the
URL above to go to the specific comment.

To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org

For queries about this service, please contact Infrastructure at:
users@infra.apache.org


---------------------------------------------------------------------
To unsubscribe, e-mail: reviews-unsubscribe@spark.apache.org
For additional commands, e-mail: reviews-help@spark.apache.org