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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2022/06/16 21:39:09 UTC
[GitHub] [spark] xinrong-databricks opened a new pull request, #36893: Support `createDataFrame` from a list of scalars
xinrong-databricks opened a new pull request, #36893:
URL: https://github.com/apache/spark/pull/36893
### What changes were proposed in this pull request?
Support `createDataFrame` from a list of scalars.
### Why are the changes needed?
### Does this PR introduce _any_ user-facing change?
Yes.
1. `createDataFrame` from a list of scalars is supported.
```py
>>> spark.createDataFrame([1, 2]).collect()
[Row(_1=1), Row(_1=2)]
```
2. Consolidated error messages
```py
>>> spark.createDataFrame([1, 'x'])
Traceback (most recent call last):
...
TypeError: field _1: Can not merge type <class 'pyspark.sql.types.LongType'> and <class 'pyspark.sql.types.StringType'>
>>> spark.createDataFrame([1, (2,)])
Traceback (most recent call last):
...
TypeError: field _1: Can not merge type <class 'pyspark.sql.types.LongType'> and <class 'pyspark.sql.types.StructType'>
```
### How was this patch tested?
Unit tests.
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r918171922
##########
python/pyspark/sql/session.py:
##########
@@ -1023,6 +1023,20 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
+ elif isinstance(data, list) and schema is None:
+ # Wrap each element with a tuple if there is any scalar in the list
+
+ has_scalar = any(
+ isinstance(x, str)
+ or (
+ not isinstance(x, Sized)
+ and (type(x).__module__ == object.__module__) # built-in
Review Comment:
Accepts native Python scalars only.
Supporting numpy/pandas scalars should be a follow-up.
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[GitHub] [spark] zhengruifeng commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
zhengruifeng commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r900708474
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,14 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
Review Comment:
```suggestion
else if isinstance(data, list):
# Wrap each element with a tuple if there is any scalar in the list
has_scalar = any(isinstance(x, str) or not hasattr(x, "__len__") for x in data)
converted_data = [(x,) for x in data] if has_scalar else data
rdd, struct = self._createFromLocal(map(prepare, converted_data), schema)
else:
rdd, struct = self._createFromLocal(map(prepare, data), schema)
```
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[GitHub] [spark] github-actions[bot] commented on pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
github-actions[bot] commented on PR #36893:
URL: https://github.com/apache/spark/pull/36893#issuecomment-1286306448
We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
If you'd like to revive this PR, please reopen it and ask a committer to remove the Stale tag!
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r918165714
##########
python/pyspark/sql/tests/test_types.py:
##########
@@ -374,12 +373,6 @@ def test_negative_decimal(self):
finally:
self.spark.sql("set spark.sql.legacy.allowNegativeScaleOfDecimal=false")
- def test_create_dataframe_from_objects(self):
Review Comment:
Moved the test to python/pyspark/sql/tests/test_session.py.
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r918171922
##########
python/pyspark/sql/session.py:
##########
@@ -1023,6 +1023,20 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
+ elif isinstance(data, list) and schema is None:
+ # Wrap each element with a tuple if there is any scalar in the list
+
+ has_scalar = any(
+ isinstance(x, str)
+ or (
+ not isinstance(x, Sized)
+ and (type(x).__module__ == object.__module__) # built-in
Review Comment:
Accepts native Python scalars only.
Supporting numpy/pandas scalars will be implemented https://issues.apache.org/jira/browse/SPARK-39745.
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[GitHub] [spark] ueshin commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
ueshin commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r899648682
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,18 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
- rdd, struct = self._createFromLocal(map(prepare, data), schema)
+ if isinstance(data, list):
+ # Wrap each element with a tuple if there is any scalar in the list
+ has_scalar = False
+ for x in data:
+ if isinstance(x, str) or not hasattr(x, "__len__"): # Scalar
+ has_scalar = True
+ break
Review Comment:
How about:
```py
has_scalar = any(isinstance(x, str) or not hasattr(x, "__len__") for x in data)
```
?
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r903018256
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,14 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
Review Comment:
Thanks!
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[GitHub] [spark] github-actions[bot] closed pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
github-actions[bot] closed pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
URL: https://github.com/apache/spark/pull/36893
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r903033580
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,14 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
- rdd, struct = self._createFromLocal(map(prepare, data), schema)
+ if isinstance(data, list):
+ # Wrap each element with a tuple if there is any scalar in the list
+ has_scalar = any(isinstance(x, str) or not hasattr(x, "__len__") for x in data)
Review Comment:
Replaced, thanks!
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r901221465
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,14 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
- rdd, struct = self._createFromLocal(map(prepare, data), schema)
+ if isinstance(data, list):
+ # Wrap each element with a tuple if there is any scalar in the list
+ has_scalar = any(isinstance(x, str) or not hasattr(x, "__len__") for x in data)
Review Comment:
`hasattr(x, "__len__")` could be replaced to `isinstance(x, collections.abc.Sized)`
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[GitHub] [spark] zhengruifeng commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
zhengruifeng commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r900708474
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,14 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
Review Comment:
```suggestion
elif isinstance(data, list):
# Wrap each element with a tuple if there is any scalar in the list
has_scalar = any(isinstance(x, str) or not hasattr(x, "__len__") for x in data)
converted_data = [(x,) for x in data] if has_scalar else data
rdd, struct = self._createFromLocal(map(prepare, converted_data), schema)
else:
rdd, struct = self._createFromLocal(map(prepare, data), schema)
```
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r899675695
##########
python/pyspark/sql/session.py:
##########
@@ -1024,7 +1024,18 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
else:
- rdd, struct = self._createFromLocal(map(prepare, data), schema)
+ if isinstance(data, list):
+ # Wrap each element with a tuple if there is any scalar in the list
+ has_scalar = False
+ for x in data:
+ if isinstance(x, str) or not hasattr(x, "__len__"): # Scalar
+ has_scalar = True
+ break
Review Comment:
Looks much cleaner! I guess Python `any` should return immediately when it detects the **first** `True`.
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[GitHub] [spark] xinrong-databricks commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r917160564
##########
python/pyspark/sql/session.py:
##########
@@ -1023,6 +1023,12 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
+ elif isinstance(data, list) and schema is None:
Review Comment:
Respect the existing behavior when `schema` is given.
Specifically,
```py
>>> spark.createDataFrame([1, 2], schema='int')
DataFrame[value: int]
>>> spark.createDataFrame([(1,), (2,)], schema='int')
...
TypeError: field value: IntegerType() can not accept object (1,) in type <class 'tuple'>
```
Adjusting the inconsistency above is out of the scope of this PR and ought to be a follow-up.
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[GitHub] [spark] HyukjinKwon commented on a diff in pull request #36893: [SPARK-39494][PYTHON] Support `createDataFrame` from a list of scalars when schema is not provided
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on code in PR #36893:
URL: https://github.com/apache/spark/pull/36893#discussion_r919529370
##########
python/pyspark/sql/session.py:
##########
@@ -1023,6 +1023,20 @@ def prepare(obj: Any) -> Any:
if isinstance(data, RDD):
rdd, struct = self._createFromRDD(data.map(prepare), schema, samplingRatio)
+ elif isinstance(data, list) and schema is None:
+ # Wrap each element with a tuple if there is any scalar in the list
+
+ has_scalar = any(
+ isinstance(x, str)
+ or (
+ not isinstance(x, Sized)
Review Comment:
How does this work in case of nested types? e.g., `spark.createDataFrame([(1,), (2,)], schema='struct<a: int>')`. We should probably check how the Scala side works, and match the behaviour.
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