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Posted to reviews@spark.apache.org by GitBox <gi...@apache.org> on 2021/07/16 22:55:24 UTC
[GitHub] [spark] xinrong-databricks opened a new pull request #33402: [SPARK-36189][PYTHON] Improve bool, string, numeric DataTypeOps tests by avoiding joins
xinrong-databricks opened a new pull request #33402:
URL: https://github.com/apache/spark/pull/33402
### What changes were proposed in this pull request?
Improve bool, string, numeric DataTypeOps tests by avoiding joins.
### Why are the changes needed?
The majority of DataTypeOps tests have operations on different Series, so joining is needed, which takes a long time.
We shall avoid joins for a shorter test duration.
### Does this PR introduce _any_ user-facing change?
No.
### How was this patch tested?
Unit tests.
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[GitHub] [spark] SparkQA commented on pull request #33402: [SPARK-36189][PYTHON] Improve bool, string, numeric DataTypeOps tests by avoiding joins
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SparkQA commented on pull request #33402:
URL: https://github.com/apache/spark/pull/33402#issuecomment-883569468
**[Test build #141349 has finished](https://amplab.cs.berkeley.edu/jenkins/job/SparkPullRequestBuilder/141349/testReport)** for PR 33402 at commit [`2259f0f`](https://github.com/apache/spark/commit/2259f0fcb16e5ebed50cad7e84a3562882177656).
* This patch passes all tests.
* This patch merges cleanly.
* This patch adds no public classes.
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[GitHub] [spark] xinrong-databricks commented on a change in pull request #33402: [SPARK-36189][PYTHON] Improve bool, string, numeric DataTypeOps tests by avoiding joins
Posted by GitBox <gi...@apache.org>.
xinrong-databricks commented on a change in pull request #33402:
URL: https://github.com/apache/spark/pull/33402#discussion_r674379508
##########
File path: python/pyspark/pandas/tests/data_type_ops/test_boolean_ops.py
##########
@@ -24,289 +24,273 @@
from pandas.api.types import CategoricalDtype
from pyspark import pandas as ps
-from pyspark.pandas.config import option_context
from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils
from pyspark.pandas.typedef.typehints import (
extension_float_dtypes_available,
extension_object_dtypes_available,
)
-from pyspark.sql.types import BooleanType
from pyspark.testing.pandasutils import PandasOnSparkTestCase
class BooleanOpsTest(PandasOnSparkTestCase, TestCasesUtils):
@property
- def pser(self):
- return pd.Series([True, True, False])
+ def bool_pdf(self):
+ return pd.DataFrame({"this": [True, False, True], "that": [False, True, True]})
@property
- def psser(self):
- return ps.from_pandas(self.pser)
-
- @property
- def float_pser(self):
- return pd.Series([1, 2, 3], dtype=float)
-
- @property
- def float_psser(self):
- return ps.from_pandas(self.float_pser)
-
- @property
- def other_pser(self):
- return pd.Series([False, False, True])
-
- @property
- def other_psser(self):
- return ps.from_pandas(self.other_pser)
+ def bool_psdf(self):
+ return ps.from_pandas(self.bool_pdf)
def test_add(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser + 1, psser + 1)
- self.assert_eq(pser + 0.1, psser + 0.1)
- self.assert_eq(pser + pser.astype(int), psser + psser.astype(int))
- self.assert_eq(pser + pser, psser + psser)
- self.assert_eq(pser + True, psser + True)
- self.assert_eq(pser + False, psser + False)
-
- with option_context("compute.ops_on_diff_frames", True):
- for pser, psser in self.numeric_pser_psser_pairs:
- self.assert_eq(self.pser + pser, (self.psser + psser).sort_index())
-
- for pser, psser in self.non_numeric_pser_psser_pairs:
- if isinstance(psser.spark.data_type, BooleanType):
- self.assert_eq(self.pser + pser, (self.psser + psser).sort_index())
- else:
- self.assertRaises(TypeError, lambda: self.psser + psser)
+ pdf, psdf = self.pdf, self.psdf
+
+ b_pser, b_psser = pdf["bool"], psdf["bool"]
+ self.assert_eq(b_pser + 1, b_psser + 1)
+ self.assert_eq(b_pser + 0.1, b_psser + 0.1)
+ self.assert_eq(b_pser + b_pser.astype(int), b_psser + b_psser.astype(int))
+ self.assert_eq(b_pser + b_pser, b_psser + b_psser)
+ self.assert_eq(b_pser + True, b_psser + True)
+ self.assert_eq(b_pser + False, b_psser + False)
+
+ for col in self.numeric_df_cols:
+ pser, psser = pdf[col], psdf[col]
+ self.assert_eq(b_pser + pser, b_psser + psser)
+ for col in self.non_numeric_df_cols:
+ pser, psser = pdf[col], psdf[col]
+ if col == "bool":
+ self.assert_eq(b_pser + pser, b_psser + psser)
+ else:
+ self.assertRaises(TypeError, lambda: b_psser + psser)
def test_sub(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser - 1, psser - 1)
- self.assert_eq(pser - 0.1, psser - 0.1)
- self.assert_eq(pser - pser.astype(int), psser - psser.astype(int))
- self.assertRaises(TypeError, lambda: psser - psser)
- self.assertRaises(TypeError, lambda: psser - True)
+ pdf, psdf = self.pdf, self.psdf
+
+ b_pser, b_psser = pdf["bool"], psdf["bool"]
+ self.assert_eq(b_pser - 1, b_psser - 1)
+ self.assert_eq(b_pser - 0.1, b_psser - 0.1)
+ self.assert_eq(b_pser - b_pser.astype(int), b_psser - b_psser.astype(int))
+ self.assertRaises(TypeError, lambda: b_psser - b_psser)
+ self.assertRaises(TypeError, lambda: b_psser - True)
- with option_context("compute.ops_on_diff_frames", True):
- for pser, psser in self.numeric_pser_psser_pairs:
- self.assert_eq(self.pser - pser, (self.psser - psser).sort_index())
+ for col in self.numeric_df_cols:
+ self.assert_eq(b_pser - pdf[col], b_psser - psdf[col])
- for psser in self.non_numeric_pssers.values():
- self.assertRaises(TypeError, lambda: self.psser - psser)
+ for col in self.non_numeric_df_cols:
+ self.assertRaises(TypeError, lambda: b_psser - psdf[col])
def test_mul(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser * 1, psser * 1)
- self.assert_eq(pser * 0.1, psser * 0.1)
- self.assert_eq(pser * pser.astype(int), psser * psser.astype(int))
- self.assert_eq(pser * pser, psser * psser)
- self.assert_eq(pser * True, psser * True)
- self.assert_eq(pser * False, psser * False)
-
- with option_context("compute.ops_on_diff_frames", True):
Review comment:
https://github.com/apache/spark/blob/master/python/pyspark/pandas/tests/test_ops_on_diff_frames.py are with `compute.ops_on_diff_frames` option on. Would you think that's enough? If not, I would like to follow up on this.
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URL: https://github.com/apache/spark/pull/33402#issuecomment-882655186
CC @ueshin @HyukjinKwon @itholic @Yikun
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[GitHub] [spark] HyukjinKwon closed pull request #33402: [SPARK-36189][PYTHON] Improve bool, string, numeric DataTypeOps tests by avoiding joins
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URL: https://github.com/apache/spark/pull/33402
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[GitHub] [spark] HyukjinKwon commented on a change in pull request #33402: [SPARK-36189][PYTHON] Improve bool, string, numeric DataTypeOps tests by avoiding joins
Posted by GitBox <gi...@apache.org>.
HyukjinKwon commented on a change in pull request #33402:
URL: https://github.com/apache/spark/pull/33402#discussion_r673591078
##########
File path: python/pyspark/pandas/tests/data_type_ops/test_boolean_ops.py
##########
@@ -24,289 +24,273 @@
from pandas.api.types import CategoricalDtype
from pyspark import pandas as ps
-from pyspark.pandas.config import option_context
from pyspark.pandas.tests.data_type_ops.testing_utils import TestCasesUtils
from pyspark.pandas.typedef.typehints import (
extension_float_dtypes_available,
extension_object_dtypes_available,
)
-from pyspark.sql.types import BooleanType
from pyspark.testing.pandasutils import PandasOnSparkTestCase
class BooleanOpsTest(PandasOnSparkTestCase, TestCasesUtils):
@property
- def pser(self):
- return pd.Series([True, True, False])
+ def bool_pdf(self):
+ return pd.DataFrame({"this": [True, False, True], "that": [False, True, True]})
@property
- def psser(self):
- return ps.from_pandas(self.pser)
-
- @property
- def float_pser(self):
- return pd.Series([1, 2, 3], dtype=float)
-
- @property
- def float_psser(self):
- return ps.from_pandas(self.float_pser)
-
- @property
- def other_pser(self):
- return pd.Series([False, False, True])
-
- @property
- def other_psser(self):
- return ps.from_pandas(self.other_pser)
+ def bool_psdf(self):
+ return ps.from_pandas(self.bool_pdf)
def test_add(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser + 1, psser + 1)
- self.assert_eq(pser + 0.1, psser + 0.1)
- self.assert_eq(pser + pser.astype(int), psser + psser.astype(int))
- self.assert_eq(pser + pser, psser + psser)
- self.assert_eq(pser + True, psser + True)
- self.assert_eq(pser + False, psser + False)
-
- with option_context("compute.ops_on_diff_frames", True):
- for pser, psser in self.numeric_pser_psser_pairs:
- self.assert_eq(self.pser + pser, (self.psser + psser).sort_index())
-
- for pser, psser in self.non_numeric_pser_psser_pairs:
- if isinstance(psser.spark.data_type, BooleanType):
- self.assert_eq(self.pser + pser, (self.psser + psser).sort_index())
- else:
- self.assertRaises(TypeError, lambda: self.psser + psser)
+ pdf, psdf = self.pdf, self.psdf
+
+ b_pser, b_psser = pdf["bool"], psdf["bool"]
+ self.assert_eq(b_pser + 1, b_psser + 1)
+ self.assert_eq(b_pser + 0.1, b_psser + 0.1)
+ self.assert_eq(b_pser + b_pser.astype(int), b_psser + b_psser.astype(int))
+ self.assert_eq(b_pser + b_pser, b_psser + b_psser)
+ self.assert_eq(b_pser + True, b_psser + True)
+ self.assert_eq(b_pser + False, b_psser + False)
+
+ for col in self.numeric_df_cols:
+ pser, psser = pdf[col], psdf[col]
+ self.assert_eq(b_pser + pser, b_psser + psser)
+ for col in self.non_numeric_df_cols:
+ pser, psser = pdf[col], psdf[col]
+ if col == "bool":
+ self.assert_eq(b_pser + pser, b_psser + psser)
+ else:
+ self.assertRaises(TypeError, lambda: b_psser + psser)
def test_sub(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser - 1, psser - 1)
- self.assert_eq(pser - 0.1, psser - 0.1)
- self.assert_eq(pser - pser.astype(int), psser - psser.astype(int))
- self.assertRaises(TypeError, lambda: psser - psser)
- self.assertRaises(TypeError, lambda: psser - True)
+ pdf, psdf = self.pdf, self.psdf
+
+ b_pser, b_psser = pdf["bool"], psdf["bool"]
+ self.assert_eq(b_pser - 1, b_psser - 1)
+ self.assert_eq(b_pser - 0.1, b_psser - 0.1)
+ self.assert_eq(b_pser - b_pser.astype(int), b_psser - b_psser.astype(int))
+ self.assertRaises(TypeError, lambda: b_psser - b_psser)
+ self.assertRaises(TypeError, lambda: b_psser - True)
- with option_context("compute.ops_on_diff_frames", True):
- for pser, psser in self.numeric_pser_psser_pairs:
- self.assert_eq(self.pser - pser, (self.psser - psser).sort_index())
+ for col in self.numeric_df_cols:
+ self.assert_eq(b_pser - pdf[col], b_psser - psdf[col])
- for psser in self.non_numeric_pssers.values():
- self.assertRaises(TypeError, lambda: self.psser - psser)
+ for col in self.non_numeric_df_cols:
+ self.assertRaises(TypeError, lambda: b_psser - psdf[col])
def test_mul(self):
- pser = self.pser
- psser = self.psser
- self.assert_eq(pser * 1, psser * 1)
- self.assert_eq(pser * 0.1, psser * 0.1)
- self.assert_eq(pser * pser.astype(int), psser * psser.astype(int))
- self.assert_eq(pser * pser, psser * psser)
- self.assert_eq(pser * True, psser * True)
- self.assert_eq(pser * False, psser * False)
-
- with option_context("compute.ops_on_diff_frames", True):
Review comment:
The change looks good but can we keep (or separate) a basic set of test with `compute.ops_on_diff_frames` option on? Feel free to do it in a separate PR if you would like to.
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Merged to master and branch-3.2.
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