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[GitHub] [spark] HyukjinKwon opened a new pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
HyukjinKwon opened a new pull request #33877:
URL: https://github.com/apache/spark/pull/33877
### What changes were proposed in this pull request?
This PR adds the support of `TimestampNTZType` in pandas API on Spark. They are handled identically with `TimestampType` for now. In fact, we don't support `datetime` with timezone yet.
This PR is dependent on #33876 and #33875.
### Why are the changes needed?
To complete `TimestampNTZ` support.
### Does this PR introduce _any_ user-facing change?
Yes, now pandas API on Spark can handle `TimestampNTZType`.
```python
import datetime
spark.createDataFrame([(datetime.datetime.now(),)], schema="dt timestamp_ntz").to_pandas_on_spark()
```
```
dt
0 2021-08-31 19:58:55.024410
```
### How was this patch tested?
Unittests were added.
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-912847527
**[Test build #142985 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142985/testReport)** for PR 33877 at commit [`83afb0b`](https://github.com/apache/spark/commit/83afb0b01a2059473801a99db8b41fe2354ccca7).
* This patch **fails from timeout after a configured wait of `500m`**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913599261
This PR is ready for a review.
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[GitHub] [spark] SparkQA commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-914095069
**[Test build #143037 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143037/testReport)** for PR 33877 at commit [`6620ade`](https://github.com/apache/spark/commit/6620adeb54fe95870c6de1604dfc2cd32028bed2).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZOps(DatetimeOps):`
* `class DatetimeNTZConverter(object):`
* `case class CastTimestampNTZToLong(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] cloud-fan commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703672741
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
> pd.Timestamp - pd.Timestamp
So this means the same timestamp type right? either TIMESTAMP_LZT - TIMESTAMP_LZT, or TIMESTAMP_NZT - TIMESTAMP_NZT
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-912767698
**[Test build #142982 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142982/testReport)** for PR 33877 at commit [`6bdfad2`](https://github.com/apache/spark/commit/6bdfad2e703a16676894ef4ab2e17eff60db539d).
* This patch **fails from timeout after a configured wait of `500m`**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZConverter(object):`
* `case class UnixSecondsUTC(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701909457
##########
File path: python/pyspark/pandas/tests/test_dataframe.py
##########
@@ -5172,6 +5172,7 @@ def test_explode(self):
self.assertRaises(TypeError, lambda: psdf.explode(["A", "B"]))
self.assertRaises(ValueError, lambda: psdf.explode("A"))
+ @unittest.skip("Skip for testing")
Review comment:
should revert this back before merging.
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[GitHub] [spark] HyukjinKwon edited a comment on pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon edited a comment on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-909131812
cc @ueshin, @xinrong-databricks and @itholic FYI
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-909131812
cc @ueshin FYI
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703373865
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
##########
@@ -708,6 +708,19 @@ case class UnixSeconds(child: Expression) extends TimestampToLongBase {
copy(child = newChild)
}
+// Internal expression used to get the raw UTC timestamp in pandas API on Spark.
Review comment:
The timstamp will be considered as a local timesone and will be normalized to UTC internally:
https://github.com/apache/spark/blob/f2492772baf1d00d802e704f84c22a9c410929e9/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala#L510
e.g.)
```scala
scala> sql("SELECT CAST(CAST(TIMESTAMP_NTZ '1970-01-01 00:00:00' AS TIMESTAMP) AS LONG)").show()
```
```
+----------------------------------------------------------------------+
|CAST(CAST(TIMESTAMP_NTZ '1970-01-01 00:00:00' AS TIMESTAMP) AS BIGINT)|
+----------------------------------------------------------------------+
| -32400|
+----------------------------------------------------------------------+
```
This has to be in UTC to mimic pandas' behaviour.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701796691
##########
File path: python/pyspark/testing/sqlutils.py
##########
@@ -249,6 +249,7 @@ class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils):
def setUpClass(cls):
super(ReusedSQLTestCase, cls).setUpClass()
cls.spark = SparkSession(cls.sc)
+ cls.spark.conf.set("spark.sql.timestampType", "TIMESTAMP_NTZ")
Review comment:
should revert back when the tests pass
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Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-909131812
cc @ueshin FYI
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[GitHub] [spark] xinrong-databricks commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r699640407
##########
File path: python/pyspark/pandas/groupby.py
##########
@@ -1439,8 +1439,15 @@ def _make_pandas_df_builder_func(
the same pandas DataFrame as if the pandas-on-Spark DataFrame is collected to driver side.
The index, column labels, etc. are re-constructed within the function.
"""
+ from pyspark.pandas.utils import default_session
+
arguments_for_restore_index = psdf._internal.arguments_for_restore_index
+ prefer_timestamp_ntz = (
Review comment:
I am wondering if we may save it as a global variable, then we may reuse it https://github.com/apache/spark/pull/33877/files#diff-fac4c35e2182657dfceedcaa20fd78963573ad34f08fd597067652e66dad53eeR1455-R1457 as well.
The current approach looks good enough though.
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33877#issuecomment-912232111
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701796298
##########
File path: python/pyspark/pandas/utils.py
##########
@@ -470,6 +470,7 @@ def default_session(conf: Optional[Dict[str, Any]] = None) -> SparkSession:
# Currently, pandas-on-Spark is dependent on such join due to 'compute.ops_on_diff_frames'
# configuration. This is needed with Spark 3.0+.
builder.config("spark.sql.analyzer.failAmbiguousSelfJoin", False)
+ builder.config("spark.sql.timestampType", "TIMESTAMP_NTZ")
Review comment:
should revert this back once tests pass.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703562782
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
This is not related to the change. It will hit the code path when:
pd.Timestamp - pd.Timestamp which will result in interval types.
Once we implement ones in PySpark, we should switch it to return interval types. Currently, we return long values instead of interval types due to missing interval in PySpark.
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Posted by GitBox <gi...@apache.org>.
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URL: https://github.com/apache/spark/pull/33877#issuecomment-913321114
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-912500264
cc @MaxGekk @gengliangwang @cloud-fan too FYI
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[GitHub] [spark] MaxGekk commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
MaxGekk commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703059104
##########
File path: python/pyspark/sql/types.py
##########
@@ -1665,7 +1665,35 @@ def convert(self, obj, gateway_client):
t.setNanos(obj.microsecond * 1000)
return t
+
+class DatetimeNTZConverter(object):
+ def can_convert(self, obj):
+ def prefer_timestamp_ntz():
+ from pyspark.sql import SparkSession
+
+ session = SparkSession._activeSession
+
+ with SparkContext._lock:
+ context = SparkContext._active_spark_context
+ if context is not None and session is not None:
+ return session._is_timestamp_ntz_preferred()
+ else:
+ return False
+
+ return isinstance(obj, datetime.datetime) and obj.tzinfo is None and prefer_timestamp_ntz()
+
+ def convert(self, obj, gateway_client):
+ from pyspark import SparkContext
+
+ seconds = calendar.timegm(obj.utctimetuple())
+ jvm = SparkContext._jvm
+ return jvm.org.apache.spark.sql.catalyst.util.DateTimeUtils.microsToLocalDateTime(
+ int(seconds) * 1000000 + obj.microsecond
Review comment:
Don't you afraid to overflow int?
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703373865
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
##########
@@ -708,6 +708,19 @@ case class UnixSeconds(child: Expression) extends TimestampToLongBase {
copy(child = newChild)
}
+// Internal expression used to get the raw UTC timestamp in pandas API on Spark.
Review comment:
The timstamp will be considered as a local timesone and will be normalized to UTC internally:
https://github.com/apache/spark/blob/f2492772baf1d00d802e704f84c22a9c410929e9/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/Cast.scala#L510
e.g.)
```scala
scala> sql("SELECT CAST(CAST(TIMESTAMP_NTZ '1970-01-01 00:00:00' AS TIMESTAMP) AS LONG)").show()
+----------------------------------------------------------------------+
|CAST(CAST(TIMESTAMP_NTZ '1970-01-01 00:00:00' AS TIMESTAMP) AS BIGINT)|
+----------------------------------------------------------------------+
| -32400|
+----------------------------------------------------------------------+
```
This has to be in UTC to mimic pandas' behaviour.
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[GitHub] [spark] ueshin commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
ueshin commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r702168125
##########
File path: python/pyspark/pandas/data_type_ops/base.py
##########
@@ -184,10 +186,21 @@ def _as_other_type(
)
assert not need_pre_process, "Pre-processing is needed before the type casting."
- scol = index_ops.spark.column.cast(spark_type)
+ if isinstance(index_ops.spark.data_type, TimestampNTZType) and isinstance(
+ spark_type, NumericType
+ ):
+ scol = _cast_spark_column_timestamp_ntz_to_long(index_ops.spark.column).cast(spark_type)
+ else:
+ scol = index_ops.spark.column.cast(spark_type)
Review comment:
We shouldn't put `index_ops`'s data type dependent code here but in `DatetimeOps.astype` instead?
##########
File path: python/pyspark/pandas/data_type_ops/base.py
##########
@@ -184,10 +186,21 @@ def _as_other_type(
)
assert not need_pre_process, "Pre-processing is needed before the type casting."
- scol = index_ops.spark.column.cast(spark_type)
+ if isinstance(index_ops.spark.data_type, TimestampNTZType) and isinstance(
+ spark_type, NumericType
+ ):
+ scol = _cast_spark_column_timestamp_ntz_to_long(index_ops.spark.column).cast(spark_type)
+ else:
+ scol = index_ops.spark.column.cast(spark_type)
+
return index_ops._with_new_scol(scol, field=InternalField(dtype=dtype))
+def _cast_spark_column_timestamp_ntz_to_long(scol: Column) -> Column:
+ jvm = SparkContext._active_spark_context._jvm # type: ignore
+ return Column(jvm.PythonSQLUtils.unixSecondsUTC(scol._jc))
Review comment:
This should be placed in `.../data_type_ops/datetime_ops.py`?
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[GitHub] [spark] xinrong-databricks commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r699575464
##########
File path: python/pyspark/pandas/typedef/typehints.py
##########
@@ -313,7 +315,9 @@ def pandas_on_spark_type(tpe: Union[str, type, Dtype]) -> Tuple[Dtype, types.Dat
return dtype, spark_type
-def infer_pd_series_spark_type(pser: pd.Series, dtype: Dtype) -> types.DataType:
+def infer_pd_series_spark_type(
+ pser: pd.Series, dtype: Dtype, prefer_timestamp_ntz: bool = False
+) -> types.DataType:
"""Infer Spark DataType from pandas Series dtype.
:param pser: :class:`pandas.Series` to be inferred
Review comment:
nit: Shall we add docstring for the `prefer_timestamp_ntz` parameter?
##########
File path: python/pyspark/pandas/groupby.py
##########
@@ -1439,8 +1439,15 @@ def _make_pandas_df_builder_func(
the same pandas DataFrame as if the pandas-on-Spark DataFrame is collected to driver side.
The index, column labels, etc. are re-constructed within the function.
"""
+ from pyspark.pandas.utils import default_session
+
arguments_for_restore_index = psdf._internal.arguments_for_restore_index
+ prefer_timestamp_ntz = (
Review comment:
I am wondering if we may save it as a global variable, then we may reuse it https://github.com/apache/spark/pull/33877/files#diff-fac4c35e2182657dfceedcaa20fd78963573ad34f08fd597067652e66dad53eeR1455-R1457 as well.
The current approach looks good enough though.
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[GitHub] [spark] SparkQA commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913592649
**[Test build #143016 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143016/testReport)** for PR 33877 at commit [`128f796`](https://github.com/apache/spark/commit/128f796bb02f41a1a551bd0cd6b0571f3318d35d).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZOps(DatetimeOps):`
* `class DatetimeNTZConverter(object):`
* `case class CastTimestampNTZToLong(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703916826
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Yeah. So this one has to be removed once intervals are implemented in PySpark. At this moment, we cannot remove this or let Spark SQL to decide it by implicit cast. Not because Spark SQL does not have the implicit cast on NTZ and LTZ, but because PySpark doesn't have interval implementation.
Or do you suggest to implement the type coercion between NTZ and LTZ in this PR, and use something like `(right - left).astype("int")` in this PR?
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gengliangwang commented on pull request #33877:
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Overall LGTM. Thanks for the work!
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**[Test build #143013 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143013/testReport)** for PR 33877 at commit [`7a920ad`](https://github.com/apache/spark/commit/7a920adc906bac33ede8a8d81a11d5c8f01a88ad).
* This patch **fails from timeout after a configured wait of `500m`**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZOps(DatetimeOps):`
* `class DatetimeNTZConverter(object):`
* `case class CastTimestampNTZToLong(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701796298
##########
File path: python/pyspark/pandas/utils.py
##########
@@ -470,6 +470,7 @@ def default_session(conf: Optional[Dict[str, Any]] = None) -> SparkSession:
# Currently, pandas-on-Spark is dependent on such join due to 'compute.ops_on_diff_frames'
# configuration. This is needed with Spark 3.0+.
builder.config("spark.sql.analyzer.failAmbiguousSelfJoin", False)
+ builder.config("spark.sql.timestampType", "TIMESTAMP_NTZ")
Review comment:
should revert this back once tests pass.
##########
File path: python/pyspark/testing/sqlutils.py
##########
@@ -249,6 +249,7 @@ class ReusedSQLTestCase(ReusedPySparkTestCase, SQLTestUtils):
def setUpClass(cls):
super(ReusedSQLTestCase, cls).setUpClass()
cls.spark = SparkSession(cls.sc)
+ cls.spark.conf.set("spark.sql.timestampType", "TIMESTAMP_NTZ")
Review comment:
should revert back when the tests pass
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* This patch passes all tests.
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* `class DatetimeNTZOps(DatetimeOps):`
* `class DatetimeNTZConverter(object):`
* `case class CastTimestampNTZToLong(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703368553
##########
File path: python/pyspark/sql/utils.py
##########
@@ -210,3 +210,14 @@ def to_str(value):
return value
else:
return str(value)
+
+
+def is_timestamp_ntz_preferred():
Review comment:
We can. I took this out of `SparkSession` because
1. there are some places like `types.py` where some methods can be accessed without initiating `SparkSession`
2. it doesn't require any properties in `SparkSession` instance
3. some tests fail for `SQLContext` (e.g., https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143016/console)
4. When `SparkContext` or `SparkSession` is stopped, JVM is still supposed to be alive in PySpark. It's safer to don't assume on `SparkSession`.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701796596
##########
File path: python/pyspark/sql/types.py
##########
@@ -202,7 +202,7 @@ def typeName(cls):
def toInternal(self, dt):
if dt is not None:
- seconds = calendar.timegm(dt.timetuple())
+ seconds = calendar.timegm(dt.utctimetuple())
Review comment:
doesn't make any difference in spark. just semantical correction.
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SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913500934
**[Test build #143011 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143011/testReport)** for PR 33877 at commit [`178c70b`](https://github.com/apache/spark/commit/178c70bfb9937ab6e94baabccad5af619ce1680a).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] cloud-fan commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703294771
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
If left side is LTZ and right side is NTZ, we need to let Spark add implicit cast.
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[GitHub] [spark] SparkQA commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-914150506
**[Test build #143038 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/143038/testReport)** for PR 33877 at commit [`f83511b`](https://github.com/apache/spark/commit/f83511b4729f5d4906205f400cba57f5ab0dcd3b).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZOps(DatetimeOps):`
* `class DatetimeNTZConverter(object):`
* `case class CastTimestampNTZToLong(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703936859
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Do you suggest something like `(right - left).astype("int")`? This won't work because:
1. interval can't be converted to longs. To natively support this, it requires internal implementation on PySpark
2. `TimestampNTZ` is considered as unix timestamp in UTC but `TIMESTAMP_LZT - TIMESTAMP_NZT` or `TIMESTAMP_LZT - TIMESTAMP_NZT` will assume `TIMESTAMP_NZT` is in local session timezone. e.g.):
```scala
scala> sql("SELECT TIMESTAMP '1970-01-01 00:00:00' - TIMESTAMP_NTZ '1970-01-01 00:00:00'").show(false)
```
should result in something like `INTERVAL '0 09:00:00' DAY TO SECOND` (I am in KST) but it result in `INTERVAL '0 00:00:00' DAY TO SECOND`
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Yeah. So this one has to be removed once intervals are implemented in PySpark. At this moment, we cannot remove this or let Spark SQL to decide it by implicit cast. Not because Spark SQL does not have the implicit cast on NTZ and LTZ, but because PySpark doesn't have interval implementation.
Or do you suggest to implement the type coercion between NTZ and LTZ in this PR, and use something like `(right - left).astype("int")` in this PR?
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I cleaned up a bit more.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r702536157
##########
File path: python/pyspark/pandas/spark/accessors.py
##########
@@ -352,33 +338,6 @@ def print_schema(self, index_col: Optional[Union[str, List[str]]] = None) -> Non
Returns
-------
None
-
Review comment:
should revert
##########
File path: python/pyspark/pandas/spark/accessors.py
##########
@@ -322,20 +322,6 @@ def schema(self, index_col: Optional[Union[str, List[str]]] = None) -> StructTyp
index_col: str or list of str, optional, default: None
Column names to be used in Spark to represent pandas-on-Spark's index. The index name
in pandas-on-Spark is ignored. By default, the index is always lost.
-
Review comment:
should revert
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Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913582274
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-911488421
I set `spark.sql.timestampType` to `TIMESTAMP_NTZ` to see if tests pass at https://github.com/apache/spark/pull/33877/commits/59efcacf74272634bcde0b24007a8a87161da25f. Should revert before merging.
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[GitHub] [spark] gengliangwang commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
gengliangwang commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703207364
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
##########
@@ -708,6 +708,19 @@ case class UnixSeconds(child: Expression) extends TimestampToLongBase {
copy(child = newChild)
}
+// Internal expression used to get the raw UTC timestamp in pandas API on Spark.
+// This is to work around casting timestamp_ntz to long disallowed by ANSI.
Review comment:
Thanks for the comment here!
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r702536157
##########
File path: python/pyspark/pandas/spark/accessors.py
##########
@@ -352,33 +338,6 @@ def print_schema(self, index_col: Optional[Union[str, List[str]]] = None) -> Non
Returns
-------
None
-
Review comment:
should revert
##########
File path: python/pyspark/pandas/spark/accessors.py
##########
@@ -322,20 +322,6 @@ def schema(self, index_col: Optional[Union[str, List[str]]] = None) -> StructTyp
index_col: str or list of str, optional, default: None
Column names to be used in Spark to represent pandas-on-Spark's index. The index name
in pandas-on-Spark is ignored. By default, the index is always lost.
-
Review comment:
should revert
##########
File path: python/pyspark/pandas/tests/test_dataframe.py
##########
@@ -5172,6 +5172,7 @@ def test_explode(self):
self.assertRaises(TypeError, lambda: psdf.explode(["A", "B"]))
self.assertRaises(ValueError, lambda: psdf.explode("A"))
+ @unittest.skip("Skip for testing")
Review comment:
should revert this back before merging.
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-909131812
cc @ueshin FYI
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Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913964232
I cleaned up a bit more.
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cc @ueshin, @xinrong-databricks and @itholic FYI
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703075783
##########
File path: python/pyspark/sql/types.py
##########
@@ -1665,7 +1665,35 @@ def convert(self, obj, gateway_client):
t.setNanos(obj.microsecond * 1000)
return t
+
+class DatetimeNTZConverter(object):
+ def can_convert(self, obj):
+ def prefer_timestamp_ntz():
+ from pyspark.sql import SparkSession
+
+ session = SparkSession._activeSession
+
+ with SparkContext._lock:
+ context = SparkContext._active_spark_context
+ if context is not None and session is not None:
+ return session._is_timestamp_ntz_preferred()
+ else:
+ return False
+
+ return isinstance(obj, datetime.datetime) and obj.tzinfo is None and prefer_timestamp_ntz()
+
+ def convert(self, obj, gateway_client):
+ from pyspark import SparkContext
+
+ seconds = calendar.timegm(obj.utctimetuple())
+ jvm = SparkContext._jvm
+ return jvm.org.apache.spark.sql.catalyst.util.DateTimeUtils.microsToLocalDateTime(
+ int(seconds) * 1000000 + obj.microsecond
Review comment:
Python one doesn't have overflow :). This is also consistent with other places of conversion in Python.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703936859
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Do you suggest something like `(right - left).astype("int")`? This won't work because:
1. interval can't be converted to longs. To natively support this, it requires interval implementation on PySpark
2. Here in pandas context, `TIMESTAMP_NZT` is considered as unix timestamp in UTC, and `TIMESTAMP_LZT` is considered as a local (session) time. But in Spark SQL `TIMESTAMP_LZT - TIMESTAMP_NZT` or `TIMESTAMP_LZT - TIMESTAMP_NZT` will assume both are in local session timezone or an unknown timezone. e.g.):
```scala
scala> sql("SELECT TIMESTAMP '1970-01-01 00:00:00' - TIMESTAMP_NTZ '1970-01-01 00:00:00'").show(false)
```
should result in something like `INTERVAL '0 09:00:00' DAY TO SECOND` (I am in KST) but it result in `INTERVAL '0 00:00:00' DAY TO SECOND`
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r701796596
##########
File path: python/pyspark/sql/types.py
##########
@@ -202,7 +202,7 @@ def typeName(cls):
def toInternal(self, dt):
if dt is not None:
- seconds = calendar.timegm(dt.timetuple())
+ seconds = calendar.timegm(dt.utctimetuple())
Review comment:
doesn't make any difference in spark. just semantical correction.
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Merged to master.
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* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZConverter(object):`
* `case class UnixSecondsUTC(child: Expression) extends TimestampToLongBase `
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HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913986456
I cleaned up a bit more.
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This PR is ready for a review.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r704158782
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
offline discussed.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703364329
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
This is to work around pandas' behaviour on internal types. PySpark didn't yet implement internal types so we can't let Spark do the implicit cast here.
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703936859
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Do you suggest something like `(right - left).astype("int")`? This won't work because:
1. interval can't be converted to longs. To natively support this, it requires internal implementation on PySpark
2. Here in pandas context, `TimestampNTZType` is considered as unix timestamp in UTC, and `TimestampType` is considered as a local (session) time. But in Spark SQL `TIMESTAMP_LZT - TIMESTAMP_NZT` or `TIMESTAMP_LZT - TIMESTAMP_NZT` will assume both are in local session timezone or an unknown timezone. e.g.):
```scala
scala> sql("SELECT TIMESTAMP '1970-01-01 00:00:00' - TIMESTAMP_NTZ '1970-01-01 00:00:00'").show(false)
```
should result in something like `INTERVAL '0 09:00:00' DAY TO SECOND` (I am in KST) but it result in `INTERVAL '0 00:00:00' DAY TO SECOND`
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Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703936859
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Do you suggest something like `(right - left).astype("int")`? This won't work because:
1. interval can't be converted to longs. To natively support this, it requires internal implementation on PySpark
2. Here in pandas context, `TIMESTAMP_NZT` is considered as unix timestamp in UTC, and `TIMESTAMP_LZT` is considered as a local (session) time. But in Spark SQL `TIMESTAMP_LZT - TIMESTAMP_NZT` or `TIMESTAMP_LZT - TIMESTAMP_NZT` will assume both are in local session timezone or an unknown timezone. e.g.):
```scala
scala> sql("SELECT TIMESTAMP '1970-01-01 00:00:00' - TIMESTAMP_NTZ '1970-01-01 00:00:00'").show(false)
```
should result in something like `INTERVAL '0 09:00:00' DAY TO SECOND` (I am in KST) but it result in `INTERVAL '0 00:00:00' DAY TO SECOND`
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703936859
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Do you suggest something like `(right - left).astype("int")`? This won't work because:
1. interval can't be converted to longs. To natively support this, it requires internal implementation on PySpark
2. Here `TimestampNTZType` is considered as unix timestamp in UTC, and `TimestampType` is considered as a local (session) time. But `TIMESTAMP_LZT - TIMESTAMP_NZT` or `TIMESTAMP_LZT - TIMESTAMP_NZT` will assume both are in local session timezone or an unknown timezone. e.g.):
```scala
scala> sql("SELECT TIMESTAMP '1970-01-01 00:00:00' - TIMESTAMP_NTZ '1970-01-01 00:00:00'").show(false)
```
should result in something like `INTERVAL '0 09:00:00' DAY TO SECOND` (I am in KST) but it result in `INTERVAL '0 00:00:00' DAY TO SECOND`
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[GitHub] [spark] SparkQA commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
SparkQA commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-912661061
**[Test build #142983 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/142983/testReport)** for PR 33877 at commit [`b4fc1fa`](https://github.com/apache/spark/commit/b4fc1fa67a66e433b1ec01278e8e96ac52531acc).
* This patch **fails PySpark unit tests**.
* This patch merges cleanly.
* This patch adds the following public classes _(experimental)_:
* `class DatetimeNTZConverter(object):`
* `case class UnixSecondsUTC(child: Expression) extends TimestampToLongBase `
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[GitHub] [spark] cloud-fan commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703517710
##########
File path: python/pyspark/pandas/data_type_ops/datetime_ops.py
##########
@@ -58,15 +66,18 @@ def sub(self, left: IndexOpsLike, right: Any) -> SeriesOrIndex:
"The timestamp subtraction returns an integer in seconds, "
"whereas pandas returns 'timedelta64[ns]'."
)
- if isinstance(right, IndexOpsMixin) and isinstance(right.spark.data_type, TimestampType):
+ if isinstance(right, IndexOpsMixin) and isinstance(
+ right.spark.data_type, (TimestampType, TimestampNTZType)
+ ):
warnings.warn(msg, UserWarning)
return left.astype("long") - right.astype("long")
Review comment:
Not very familiar with pandas. Can you give a real example that will hit this code path?
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[GitHub] [spark] xinrong-databricks commented on a change in pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r699575464
##########
File path: python/pyspark/pandas/typedef/typehints.py
##########
@@ -313,7 +315,9 @@ def pandas_on_spark_type(tpe: Union[str, type, Dtype]) -> Tuple[Dtype, types.Dat
return dtype, spark_type
-def infer_pd_series_spark_type(pser: pd.Series, dtype: Dtype) -> types.DataType:
+def infer_pd_series_spark_type(
+ pser: pd.Series, dtype: Dtype, prefer_timestamp_ntz: bool = False
+) -> types.DataType:
"""Infer Spark DataType from pandas Series dtype.
:param pser: :class:`pandas.Series` to be inferred
Review comment:
nit: Shall we add docstring for the `prefer_timestamp_ntz` parameter?
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[GitHub] [spark] HyukjinKwon edited a comment on pull request #33877: [SPARK-36625][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon edited a comment on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-909131812
cc @ueshin, @xinrong-databricks and @itholic FYI
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Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-913378239
This PR is ready for a review.
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[GitHub] [spark] HyukjinKwon commented on pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on pull request #33877:
URL: https://github.com/apache/spark/pull/33877#issuecomment-915676100
fyi, im gonna revisit all the dt operations in pandas api on Spark in q4.
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[GitHub] [spark] cloud-fan commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
Posted by GitBox <gi...@apache.org>.
cloud-fan commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703299464
##########
File path: python/pyspark/sql/utils.py
##########
@@ -210,3 +210,14 @@ def to_str(value):
return value
else:
return str(value)
+
+
+def is_timestamp_ntz_preferred():
Review comment:
shouldn't this be a method of `SparkSession` in pyspark?
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[GitHub] [spark] cloud-fan commented on a change in pull request #33877: [SPARK-36625][SPARK-36661][PYTHON] Support TimestampNTZ in pandas API on Spark
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cloud-fan commented on a change in pull request #33877:
URL: https://github.com/apache/spark/pull/33877#discussion_r703300116
##########
File path: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/datetimeExpressions.scala
##########
@@ -708,6 +708,19 @@ case class UnixSeconds(child: Expression) extends TimestampToLongBase {
copy(child = newChild)
}
+// Internal expression used to get the raw UTC timestamp in pandas API on Spark.
Review comment:
shouldn't we cast NTZ to LTZ first and then cast LTZ to long?
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