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[GitHub] [spark] liangz1 opened a new pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
liangz1 opened a new pull request #34021:
URL: https://github.com/apache/spark/pull/34021
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This PR adds the pyspark API `df.withMetadata(columnName, metadata)`. The scala API is added in this PR https://github.com/apache/spark/pull/33853.
### What changes were proposed in this pull request?
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To make it easy to use/modify the semantic annotation, we want to have a shorter API to update the metadata in a dataframe. Currently we have `df.withColumn("col1", col("col1").alias("col1", metadata=metadata))` to update the metadata without changing the column name, and this is too verbose. We want to have a syntax suger API `df.withMetadata("col1", metadata=metadata)` to achieve the same functionality.
### Why are the changes needed?
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A bit of background for the frequency of the update: We are working on inferring the semantic data types and use them in AutoML and store the semantic annotation in the metadata. So in many cases, we will suggest the user update the metadata to correct the wrong inference or add the annotation for weak inference.
### Does this PR introduce _any_ user-facing change?
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Yes.
A syntax suger API `df.withMetadata("col1", metadata=metadata)` to achieve the same functionality as`df.withColumn("col1", col("col1").alias("col1", metadata=metadata))`.
### How was this patch tested?
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doctest.
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[GitHub] [spark] liangz1 commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
liangz1 commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r710150489
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
Review comment:
https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L712 The existing API that takes the metadata also specified that the metadata should be a dict in the docstring. However, I'm also fine with not checking the dict type.
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921716656
**[Test build #143409 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143409/testReport)** for PR 34021 at commit [`e09cc2f`](https://github.com/apache/spark/commit/e09cc2fdfff6b423d797b66a40b582663b9b6456).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] WeichenXu123 commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
WeichenXu123 commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-920924138
CC @HyukjinKwon
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r711837003
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
Review comment:
I think this is fine to check if it's an explicitly a dictionary. Following docstring sounds fine.
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[GitHub] [spark] WeichenXu123 commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
WeichenXu123 commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r710137451
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
Review comment:
why restrict the type to be dict ? we should allow any types which can be converted to JSON.
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[GitHub] [spark] WeichenXu123 commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
WeichenXu123 commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r710134006
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
+ raise TypeError("metadata should be a dict")
+ return DataFrame(self._jdf.withMetadata(columnName, metadata), self.sql_ctx)
Review comment:
The metadata argument type is a dict , how does it pass to the java method `def withMetadata(columnName: String, metadata: Metadata)` and the metadata become a `Metadata` class type ?
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[GitHub] [spark] WeichenXu123 commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
WeichenXu123 commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r711587577
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
Review comment:
@HyukjinKwon
> https://github.com/apache/spark/blob/master/python/pyspark/sql/column.py#L712 The existing API that takes the metadata also specified that the metadata should be a dict in the docstring. However, I'm also fine with not checking the dict type.
But in code here https://github.com/apache/spark/blob/cabc36b54d7f6633d8b128e511e7049c475b919d/python/pyspark/sql/column.py#L747 it doesn't require metadata to be dict , so is it a doc error or code error there ?
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[GitHub] [spark] codecov-commenter commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
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URL: https://github.com/apache/spark/pull/34021#issuecomment-922454551
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[GitHub] [spark] WeichenXu123 closed pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
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URL: https://github.com/apache/spark/pull/34021#issuecomment-921813729
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* This patch passes all tests.
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[GitHub] [spark] HyukjinKwon commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921344172
looks like we should fix the test:
```
**********************************************************************
File "/__w/spark/spark/python/pyspark/sql/dataframe.py", line 2553, in pyspark.sql.dataframe.DataFrame.withMetadata
Failed example:
df_meta = df.withMetadata('age', {'foo': 'bar'})
Exception raised:
Traceback (most recent call last):
File "/usr/lib/pypy3/lib-python/3/doctest.py", line 1339, in __run
compileflags, 1), test.globs)
File "<doctest pyspark.sql.dataframe.DataFrame.withMetadata[0]>", line 1, in <module>
df_meta = df.withMetadata('age', {'foo': 'bar'})
File "/__w/spark/spark/python/pyspark/sql/dataframe.py", line 2559, in withMetadata
sc = SparkContext._active_spark_context
NameError: name 'SparkContext' is not defined
**********************************************************************
File "/__w/spark/spark/python/pyspark/sql/dataframe.py", line 2554, in pyspark.sql.dataframe.DataFrame.withMetadata
Failed example:
df_meta.schema['age'].metadata
Exception raised:
Traceback (most recent call last):
File "/usr/lib/pypy3/lib-python/3/doctest.py", line 1339, in __run
compileflags, 1), test.globs)
File "<doctest pyspark.sql.dataframe.DataFrame.withMetadata[1]>", line 1, in <module>
df_meta.schema['age'].metadata
NameError: name 'df_meta' is not defined
```
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WeichenXu123 commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-926258660
merge to master
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[GitHub] [spark] liangz1 commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
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liangz1 commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921854773
@HyukjinKwon The Kubernetes test failure looks irrelevant, is this a know issue?
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[GitHub] [spark] HyukjinKwon commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
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HyukjinKwon commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-922166335
Yeah doesn't look related
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[GitHub] [spark] liangz1 commented on a change in pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
liangz1 commented on a change in pull request #34021:
URL: https://github.com/apache/spark/pull/34021#discussion_r710147710
##########
File path: python/pyspark/sql/dataframe.py
##########
@@ -2536,6 +2536,28 @@ def withColumnRenamed(self, existing, new):
"""
return DataFrame(self._jdf.withColumnRenamed(existing, new), self.sql_ctx)
+ def withMetadata(self, columnName, metadata):
+ """Returns a new :class:`DataFrame` by updating an existing column with metadata.
+
+ .. versionadded:: 3.3.0
+
+ Parameters
+ ----------
+ columnName : str
+ string, name of the existing column to update the metadata.
+ metadata : dict
+ dict, new metadata to be assigned to df.schema[columnName].metadata
+
+ Examples
+ --------
+ >>> df_meta = df.withMetadata('age', {'foo': 'bar'})
+ >>> df_meta.schema['age'].metadata
+ {'foo': 'bar'}
+ """
+ if not isinstance(metadata, dict):
+ raise TypeError("metadata should be a dict")
+ return DataFrame(self._jdf.withMetadata(columnName, metadata), self.sql_ctx)
Review comment:
Nice catch! I updated the conversion.
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@@ Coverage Diff @@
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=======================================
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Lines 60437 60527 +90
Branches 8879 8889 +10
=======================================
+ Hits 54514 54596 +82
- Misses 4595 4599 +4
- Partials 1328 1332 +4
```
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------
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> Powered by [Codecov](https://codecov.io/gh/apache/spark/pull/34021?src=pr&el=footer&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation). Last update [adbea25...28faa2e](https://codecov.io/gh/apache/spark/pull/34021?src=pr&el=lastupdated&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation). Read the [comment docs](https://docs.codecov.io/docs/pull-request-comments?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation).
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SparkQA commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921704171
**[Test build #143409 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143409/testReport)** for PR 34021 at commit [`e09cc2f`](https://github.com/apache/spark/commit/e09cc2fdfff6b423d797b66a40b582663b9b6456).
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[GitHub] [spark] SparkQA commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921039610
**[Test build #143355 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143355/testReport)** for PR 34021 at commit [`2192b5f`](https://github.com/apache/spark/commit/2192b5fd5bff067366ba7e255bde1a3135a660a3).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] codecov-commenter edited a comment on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
codecov-commenter edited a comment on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-922454551
# [Codecov](https://codecov.io/gh/apache/spark/pull/34021?src=pr&el=h1&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation) Report
> Merging [#34021](https://codecov.io/gh/apache/spark/pull/34021?src=pr&el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation) (cabc36b) into [master](https://codecov.io/gh/apache/spark/commit/2d7dc7c7ce6d524a232f37927ca179f162ad9971?el=desc&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation) (2d7dc7c) will **increase** coverage by `0.00%`.
> The diff coverage is `93.24%`.
> :exclamation: Current head cabc36b differs from pull request most recent head 28faa2e. Consider uploading reports for the commit 28faa2e to get more accurate results
[](https://codecov.io/gh/apache/spark/pull/34021?src=pr&el=tree&utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation)
```diff
@@ Coverage Diff @@
## master #34021 +/- ##
=======================================
Coverage 90.19% 90.20%
=======================================
Files 288 288
Lines 60437 60527 +90
Branches 8879 8889 +10
=======================================
+ Hits 54514 54596 +82
- Misses 4595 4599 +4
- Partials 1328 1332 +4
```
| Flag | Coverage Δ | |
|---|---|---|
| unittests | `90.17% <93.24%> (+<0.01%)` | :arrow_up: |
Flags with carried forward coverage won't be shown. [Click here](https://docs.codecov.io/docs/carryforward-flags?utm_medium=referral&utm_source=github&utm_content=comment&utm_campaign=pr+comments&utm_term=The+Apache+Software+Foundation#carryforward-flags-in-the-pull-request-comment) to find out more.
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|---|---|---|
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[GitHub] [spark] liangz1 edited a comment on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
liangz1 edited a comment on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921854773
@HyukjinKwon The Kubernetes test failure looks irrelevant, is this a known issue?
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[GitHub] [spark] SparkQA removed a comment on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
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SparkQA removed a comment on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921786316
**[Test build #143414 has started](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143414/testReport)** for PR 34021 at commit [`28faa2e`](https://github.com/apache/spark/commit/28faa2e5070eb53abd24cb64af78d67222960e0a).
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[GitHub] [spark] SparkQA commented on pull request #34021: [SPARK-36642][SQL] Add df.withMetadata pyspark API
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #34021:
URL: https://github.com/apache/spark/pull/34021#issuecomment-921846207
Kubernetes integration test status failure
URL: https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder-K8s/47921/
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