[SPARK-23334][SQL][PYTHON] Fix pandas_udf with return type StringType() to handle str type properly in Python 2. #20507
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cc @BryanCutler @icexelloss @HyukjinKwon |
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Test build #87063 has finished for PR 20507 at commit
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python/pyspark/sql/tests.py
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| import pandas as pd | ||
| df = self.spark.range(10) | ||
| str_f = pandas_udf(lambda x: pd.Series(["%s" % i for i in x]), StringType()) | ||
| res = df.select(str_f(col('id'))) |
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How about variable names 'expected' and 'actual'?
python/pyspark/sql/tests.py
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| from pyspark.sql.functions import pandas_udf, col | ||
| import pandas as pd | ||
| df = self.spark.range(10) | ||
| str_f = pandas_udf(lambda x: pd.Series(["%s" % i for i in x]), StringType()) |
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Not a big deal. How about pd.Series(map(str, x))?
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Sounds good. I'll take it.
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Test build #87069 has finished for PR 20507 at commit
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python/pyspark/serializers.py
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| @@ -230,6 +230,9 @@ def create_array(s, t): | |||
| s = _check_series_convert_timestamps_internal(s.fillna(0), timezone) | |||
| # TODO: need cast after Arrow conversion, ns values cause error with pandas 0.19.2 | |||
| return pa.Array.from_pandas(s, mask=mask).cast(t, safe=False) | |||
| elif t is not None and pa.types.is_string(t) and sys.version < '3': | |||
| # TODO: need decode before converting to Arrow in Python 2 | |||
| return pa.Array.from_pandas(s.str.decode('utf-8'), mask=mask, type=t) | |||
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@ueshin, actually, how about s.apply(lambda v: v.decode("utf-8") if isinstance(v, str) else v) to allow non-ascii encodable unicodes too like u"아"? I was worried of performance but I ran a simple perf test vs s.str.decode('utf-8') for sure. Seems actually fine.
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Good catch! I'll take it. Thanks!
@BryanCutler Btw, do you think this is a bug of pyarrow in Python 2? |
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Test build #87083 has finished for PR 20507 at commit
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also cc @cloud-fan @gatorsmile @sameeragarwal |
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Sorry I've been travelling, but I'll try to look into this soon on the Arrow side to see if it is a bug in pyarrow. The workaround here seems fine to me. |
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Merged to master and branch-2.3. |
…() to handle str type properly in Python 2.
## What changes were proposed in this pull request?
In Python 2, when `pandas_udf` tries to return string type value created in the udf with `".."`, the execution fails. E.g.,
```python
from pyspark.sql.functions import pandas_udf, col
import pandas as pd
df = spark.range(10)
str_f = pandas_udf(lambda x: pd.Series(["%s" % i for i in x]), "string")
df.select(str_f(col('id'))).show()
```
raises the following exception:
```
...
java.lang.AssertionError: assertion failed: Invalid schema from pandas_udf: expected StringType, got BinaryType
at scala.Predef$.assert(Predef.scala:170)
at org.apache.spark.sql.execution.python.ArrowEvalPythonExec$$anon$2.<init>(ArrowEvalPythonExec.scala:93)
...
```
Seems like pyarrow ignores `type` parameter for `pa.Array.from_pandas()` and consider it as binary type when the type is string type and the string values are `str` instead of `unicode` in Python 2.
This pr adds a workaround for the case.
## How was this patch tested?
Added a test and existing tests.
Author: Takuya UESHIN <ueshin@databricks.com>
Closes #20507 from ueshin/issues/SPARK-23334.
(cherry picked from commit 63c5bf1)
Signed-off-by: hyukjinkwon <gurwls223@gmail.com>
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Thanks! @HyukjinKwon @BryanCutler |
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I made https://issues.apache.org/jira/browse/ARROW-2101 to track the issue in Arrow |
What changes were proposed in this pull request?
In Python 2, when
pandas_udftries to return string type value created in the udf with"..", the execution fails. E.g.,raises the following exception:
Seems like pyarrow ignores
typeparameter forpa.Array.from_pandas()and consider it as binary type when the type is string type and the string values arestrinstead ofunicodein Python 2.This pr adds a workaround for the case.
How was this patch tested?
Added a test and existing tests.