[
https://issues.apache.org/jira/browse/SPARK-36283?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Darcy Shen updated SPARK-36283:
-------------------------------
Description:
h2. Case 1: Create PySpark Dataframe using Pandas DataFrame with Arrow
disabled and without schema
{code:python}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
2)])})
df = spark.createDataFrame(pdf)
df.show()
{code}
h3. Incorrect result
{code}
+----------+
| point|
+----------+
|(0.0, 0.0)|
|(0.0, 0.0)|
+----------+
{code}
h2. Case 2: Create PySpark Dataframe using Pandas DataFrame with Arrow disabled
and with unmatched schema
{code}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
2)])})
schema = StructType([StructField('point', ExamplePointUDT(), False)])
df = spark.createDataFrame(pdf, schema)
df.show()
{code}
h3. Error throwed as expected
{code}
Traceback (most recent call last):
File "bug2.py", line 54, in <module>
df = spark.createDataFrame(pdf, schema)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
line 673, in createDataFrame
return super(SparkSession, self).createDataFrame(
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/pandas/conversion.py",
line 300, in createDataFrame
return self._create_dataframe(data, schema, samplingRatio, verifySchema)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
line 700, in _create_dataframe
rdd, schema = self._createFromLocal(map(prepare, data), schema)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
line 509, in _createFromLocal
data = list(data)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
line 682, in prepare
verify_func(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1409, in verify
verify_value(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1390, in verify_struct
verifier(v)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1409, in verify
verify_value(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1304, in verify_udf
verifier(dataType.toInternal(obj))
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1409, in verify
verify_value(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1354, in verify_array
element_verifier(i)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1409, in verify
verify_value(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1403, in verify_default
verify_acceptable_types(obj)
File
"/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
line 1291, in verify_acceptable_types
raise TypeError(new_msg("%s can not accept object %r in type %s"
TypeError: element in array field point: DoubleType can not accept object 1 in
type <class 'int'>
{code}
h2. Case 3: Create PySpark Dataframe using Pandas DataFrame with Arrow disabled
and with matched schema
{code}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1.0, 1.0),
ExamplePoint(2.0, 2.0)])})
schema = StructType([StructField('point', ExamplePointUDT(), False)])
df = spark.createDataFrame(pdf, schema)
df.show()
{code}
h3. Correct result
{code}
+----------+
| point|
+----------+
|(1.0, 1.0)|
|(2.0, 2.0)|
+----------+
{code}
was:
h2. Case 1
Create PySpark Dataframe using Pandas DataFrame with Arrow disabled and
without schema:
{code:python}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
2)])})
df = spark.createDataFrame(pdf)
df.show()
{code}
h2. Case 2
Create PySpark Dataframe using Pandas DataFrame with Arrow disabled and with
unmatched schema:
{code}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
2)])})
schema = StructType([StructField('point', ExamplePointUDT(), False)])
df = spark.createDataFrame(pdf, schema)
df.show()
{code}
h3. Case 3
Create PySpark Dataframe using Pandas DataFrame with Arrow disabled and with
matched schema:
{code}
spark = SparkSession.builder.getOrCreate()
spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1.0, 1.0),
ExamplePoint(2.0, 2.0)])})
schema = StructType([StructField('point', ExamplePointUDT(), False)])
df = spark.createDataFrame(pdf, schema)
df.show()
{code}
> Bug when creating dataframe without schema and with Arrow disabled
> ------------------------------------------------------------------
>
> Key: SPARK-36283
> URL: https://issues.apache.org/jira/browse/SPARK-36283
> Project: Spark
> Issue Type: Sub-task
> Components: PySpark
> Affects Versions: 3.1.1
> Reporter: Darcy Shen
> Priority: Major
>
> h2. Case 1: Create PySpark Dataframe using Pandas DataFrame with Arrow
> disabled and without schema
> {code:python}
> spark = SparkSession.builder.getOrCreate()
> spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
> pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
> 2)])})
> df = spark.createDataFrame(pdf)
> df.show()
> {code}
> h3. Incorrect result
> {code}
> +----------+
> | point|
> +----------+
> |(0.0, 0.0)|
> |(0.0, 0.0)|
> +----------+
> {code}
> h2. Case 2: Create PySpark Dataframe using Pandas DataFrame with Arrow
> disabled and with unmatched schema
> {code}
> spark = SparkSession.builder.getOrCreate()
> spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
> pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1, 1), ExamplePoint(2,
> 2)])})
> schema = StructType([StructField('point', ExamplePointUDT(), False)])
> df = spark.createDataFrame(pdf, schema)
> df.show()
> {code}
> h3. Error throwed as expected
> {code}
> Traceback (most recent call last):
> File "bug2.py", line 54, in <module>
> df = spark.createDataFrame(pdf, schema)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
> line 673, in createDataFrame
> return super(SparkSession, self).createDataFrame(
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/pandas/conversion.py",
> line 300, in createDataFrame
> return self._create_dataframe(data, schema, samplingRatio, verifySchema)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
> line 700, in _create_dataframe
> rdd, schema = self._createFromLocal(map(prepare, data), schema)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
> line 509, in _createFromLocal
> data = list(data)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/session.py",
> line 682, in prepare
> verify_func(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1409, in verify
> verify_value(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1390, in verify_struct
> verifier(v)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1409, in verify
> verify_value(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1304, in verify_udf
> verifier(dataType.toInternal(obj))
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1409, in verify
> verify_value(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1354, in verify_array
> element_verifier(i)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1409, in verify
> verify_value(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1403, in verify_default
> verify_acceptable_types(obj)
> File
> "/Users/da/.pyenv/versions/spark-36283/lib/python3.8/site-packages/pyspark/sql/types.py",
> line 1291, in verify_acceptable_types
> raise TypeError(new_msg("%s can not accept object %r in type %s"
> TypeError: element in array field point: DoubleType can not accept object 1
> in type <class 'int'>
> {code}
> h2. Case 3: Create PySpark Dataframe using Pandas DataFrame with Arrow
> disabled and with matched schema
> {code}
> spark = SparkSession.builder.getOrCreate()
> spark.conf.set("spark.sql.execution.arrow.pyspark.enabled", "false")
> pdf = pd.DataFrame({'point': pd.Series([ExamplePoint(1.0, 1.0),
> ExamplePoint(2.0, 2.0)])})
> schema = StructType([StructField('point', ExamplePointUDT(), False)])
> df = spark.createDataFrame(pdf, schema)
> df.show()
> {code}
> h3. Correct result
> {code}
> +----------+
> | point|
> +----------+
> |(1.0, 1.0)|
> |(2.0, 2.0)|
> +----------+
> {code}
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