[SPARK-29126][PYSPARK][DOC] Pandas Cogroup udf usage guide#26110
[SPARK-29126][PYSPARK][DOC] Pandas Cogroup udf usage guide#26110d80tb7 wants to merge 6 commits into
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…9126-cogroup-udf-usage-guide # Conflicts: # python/pyspark/sql/cogroup.py
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Test build #112022 has finished for PR 26110 at commit
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retest this please |
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From a cursory look, seems fine. cc @icexelloss, @BryanCutler, @viirya |
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| ### Cogrouped Map | ||
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| CoGrouped map Pandas UDFs allow two DataFrames to be cogrouped a by a common key and then a python function applied to |
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Is it CoGrouped or Cogrouped :-)?
| on how to label columns when constructing a `pandas.DataFrame`. | ||
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| Note that all data for a cogroup will be loaded into memory before the function is applied. This can lead to out of | ||
| memory exceptions, especially if the group sizes are skewed. The configuration for[maxRecordsPerBatch](#setting-arrow-batch-size) |
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typoe -> for[maxRecordsPerBatch] -> for [maxRecordsPerBatch]
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Test build #112538 has finished for PR 26110 at commit
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BryanCutler
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BryanCutler
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Thanks for doing this @d80tb7 , I just had some minor comments but looks good overall.
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| ### Cogrouped Map | ||
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| CoGrouped map Pandas UDFs allow two DataFrames to be cogrouped a by a common key and then a python function applied to |
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cogrouped a by -> cogrouped by
| each cogroup. They are used with `groupBy().cogroup().apply()` which consists of the following steps: | ||
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| * Shuffle the data such that the groups of each dataframe which share a key are cogrouped together. | ||
| * Apply a function to each cogroup. The input of of the function is two `pandas.DataFrame` (with an optional Tuple |
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duplicate of in input of of
| * Shuffle the data such that the groups of each dataframe which share a key are cogrouped together. | ||
| * Apply a function to each cogroup. The input of of the function is two `pandas.DataFrame` (with an optional Tuple | ||
| representing the key). The output of the function is a `pandas.DataFrame`. | ||
| * Combine the results into a new `DataFrame`. |
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Maybe elaborate to explain results are pandas.DataFrames from all groups that are combined in a new pyspark.DataFrame
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| 6. COGROUPED_MAP | ||
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| A cogrouped map UDF defines transformation: two `pandas.DataFrame` -> `pandas.DataFrame` |
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I think instead of "two pandas.DataFrame", better to show "(pandas.DataFrame, pandas.DataFrame) -> pandas.DataFrame"
| 6. COGROUPED_MAP | ||
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| A cogrouped map UDF defines transformation: two `pandas.DataFrame` -> `pandas.DataFrame` | ||
| The returnType should be a :class:`StructType` describing the schema of the returned |
…9126-cogroup-udf-usage-guide
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Test build #112939 has finished for PR 26110 at commit
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Test build #112944 has finished for PR 26110 at commit
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Merged to master. |
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This PR adds some extra documentation for the new Cogrouped map Pandas udfs. Specifically:
COGROUPED_MAPPandas udfs added in [SPARK-27463][PYTHON] Support Dataframe Cogroup via Pandas UDFs #24981