viirya commented on a change in pull request #27466:
[SPARK-30722][PYTHON][DOCS] Update documentation for Pandas UDF with Python
type hints
URL: https://github.com/apache/spark/pull/27466#discussion_r375663877
##########
File path: docs/sql-pyspark-pandas-with-arrow.md
##########
@@ -201,16 +273,15 @@ Note that all data for a cogroup will be loaded into
memory before the function
memory exceptions, especially if the group sizes are skewed. The configuration
for [maxRecordsPerBatch](#setting-arrow-batch-size)
is not applied and it is up to the user to ensure that the cogrouped data will
fit into the available memory.
-The following example shows how to use `groupby().cogroup().apply()` to
perform an asof join between two datasets.
+The following example shows how to use `groupby().cogroup().applyInPandas()`
to perform an asof join between two datasets.
<div class="codetabs">
<div data-lang="python" markdown="1">
-{% include_example cogrouped_map_pandas_udf python/sql/arrow.py %}
+{% include_example cogrouped_apply_in_pandas python/sql/arrow.py %}
</div>
</div>
-For detailed usage, please see
[`pyspark.sql.functions.pandas_udf`](api/python/pyspark.sql.html#pyspark.sql.functions.pandas_udf)
and
-[`pyspark.sql.CoGroupedData.apply`](api/python/pyspark.sql.html#pyspark.sql.CoGroupedData.apply).
+For detailed usage, please see
[`pyspark.sql.CoGroupedData.applyInPandas()`](api/python/pyspark.sql.html#pyspark.sql.CoGroupedData.applyInPandas).
Review comment:
Does this mean `PandasCogroupedOps` or `GroupedData` actually? I don't find
any `CoGroupedData`.
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