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[SPARK-50465][PYTHON][TESTS] Use assertDataFrameEqual in pyspark.sql.tests.test_group and test_readwriter #49023

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[SPARK-50465][PYTHON][TESTS] Use assertDataFrameEqual in pyspark.sql.tests.test_group and test_readwriter #49023

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12 changes: 6 additions & 6 deletions python/pyspark/sql/tests/test_group.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,11 +36,11 @@ def test_agg_func(self):
data = [Row(key=1, value=10), Row(key=1, value=20), Row(key=1, value=30)]
df = self.spark.createDataFrame(data)
g = df.groupBy("key")
self.assertEqual(g.max("value").collect(), [Row(**{"key": 1, "max(value)": 30})])
self.assertEqual(g.min("value").collect(), [Row(**{"key": 1, "min(value)": 10})])
self.assertEqual(g.sum("value").collect(), [Row(**{"key": 1, "sum(value)": 60})])
self.assertEqual(g.count().collect(), [Row(key=1, count=3)])
self.assertEqual(g.mean("value").collect(), [Row(**{"key": 1, "avg(value)": 20.0})])
assertDataFrameEqual(g.max("value"), [Row(**{"key": 1, "max(value)": 30})])
assertDataFrameEqual(g.min("value"), [Row(**{"key": 1, "min(value)": 10})])
assertDataFrameEqual(g.sum("value"), [Row(**{"key": 1, "sum(value)": 60})])
assertDataFrameEqual(g.count(), [Row(key=1, count=3)])
assertDataFrameEqual(g.mean("value"), [Row(**{"key": 1, "avg(value)": 20.0})])

data = [
Row(electronic="Smartphone", year=2018, sales=150000),
Expand All @@ -59,7 +59,7 @@ def test_aggregator(self):
df = self.df
g = df.groupBy()
self.assertEqual([99, 100], sorted(g.agg({"key": "max", "value": "count"}).collect()[0]))
self.assertEqual([Row(**{"AVG(key#0)": 49.5})], g.mean().collect())
assertDataFrameEqual([Row(**{"AVG(key#0)": 49.5})], g.mean().collect())

from pyspark.sql import functions

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21 changes: 11 additions & 10 deletions python/pyspark/sql/tests/test_readwriter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@
from pyspark.sql.functions import col, lit
from pyspark.sql.readwriter import DataFrameWriterV2
from pyspark.sql.types import StructType, StructField, StringType
from pyspark.testing import assertDataFrameEqual
from pyspark.testing.sqlutils import ReusedSQLTestCase


Expand All @@ -34,15 +35,15 @@ def test_save_and_load(self):
try:
df.write.json(tmpPath)
actual = self.spark.read.json(tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

schema = StructType([StructField("value", StringType(), True)])
actual = self.spark.read.json(tmpPath, schema)
self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
assertDataFrameEqual(df.select("value"), actual)

df.write.json(tmpPath, "overwrite")
actual = self.spark.read.json(tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

df.write.save(
format="json",
Expand All @@ -53,11 +54,11 @@ def test_save_and_load(self):
actual = self.spark.read.load(
format="json", path=tmpPath, noUse="this options will not be used in load."
)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

with self.sql_conf({"spark.sql.sources.default": "org.apache.spark.sql.json"}):
actual = self.spark.read.load(path=tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

csvpath = os.path.join(tempfile.mkdtemp(), "data")
df.write.option("quote", None).format("csv").save(csvpath)
Expand All @@ -71,15 +72,15 @@ def test_save_and_load_builder(self):
try:
df.write.json(tmpPath)
actual = self.spark.read.json(tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

schema = StructType([StructField("value", StringType(), True)])
actual = self.spark.read.json(tmpPath, schema)
self.assertEqual(sorted(df.select("value").collect()), sorted(actual.collect()))
assertDataFrameEqual(df.select("value"), actual)

df.write.mode("overwrite").json(tmpPath)
actual = self.spark.read.json(tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

df.write.mode("overwrite").options(
noUse="this options will not be used in save."
Expand All @@ -89,11 +90,11 @@ def test_save_and_load_builder(self):
actual = self.spark.read.format("json").load(
path=tmpPath, noUse="this options will not be used in load."
)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)

with self.sql_conf({"spark.sql.sources.default": "org.apache.spark.sql.json"}):
actual = self.spark.read.load(path=tmpPath)
self.assertEqual(sorted(df.collect()), sorted(actual.collect()))
assertDataFrameEqual(df, actual)
finally:
shutil.rmtree(tmpPath)

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