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Posted to issues@spark.apache.org by "Hyukjin Kwon (Jira)" <ji...@apache.org> on 2023/01/09 12:51:00 UTC
[jira] [Updated] (SPARK-41950) mlflow doctest fails for pandas API on SPark
[ https://issues.apache.org/jira/browse/SPARK-41950?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-41950:
---------------------------------
Issue Type: Test (was: Bug)
> mlflow doctest fails for pandas API on SPark
> --------------------------------------------
>
> Key: SPARK-41950
> URL: https://issues.apache.org/jira/browse/SPARK-41950
> Project: Spark
> Issue Type: Test
> Components: Pandas API on Spark
> Affects Versions: 3.4.0
> Reporter: Hyukjin Kwon
> Priority: Major
>
> {code}
> File "/__w/spark/spark/python/pyspark/pandas/mlflow.py", line 172, in pyspark.pandas.mlflow.load_model
> Failed example:
> prediction_df
> Exception raised:
> Traceback (most recent call last):
> File "/usr/lib/python3.9/doctest.py", line 1336, in __run
> exec(compile(example.source, filename, "single",
> File "<doctest pyspark.pandas.mlflow.load_model[18]>", line 1, in <module>
> prediction_df
> File "/__w/spark/spark/python/pyspark/pandas/frame.py", line 13322, in __repr__
> pdf = cast("DataFrame", self._get_or_create_repr_pandas_cache(max_display_count))
> File "/__w/spark/spark/python/pyspark/pandas/frame.py", line 13313, in _get_or_create_repr_pandas_cache
> self, "_repr_pandas_cache", {n: self.head(n + 1)._to_internal_pandas()}
> File "/__w/spark/spark/python/pyspark/pandas/frame.py", line 13308, in _to_internal_pandas
> return self._internal.to_pandas_frame
> File "/__w/spark/spark/python/pyspark/pandas/utils.py", line 588, in wrapped_lazy_property
> setattr(self, attr_name, fn(self))
> File "/__w/spark/spark/python/pyspark/pandas/internal.py", line 1056, in to_pandas_frame
> pdf = sdf.toPandas()
> File "/__w/spark/spark/python/pyspark/sql/pandas/conversion.py", line 208, in toPandas
> pdf = pd.DataFrame.from_records(self.collect(), columns=self.columns)
> File "/__w/spark/spark/python/pyspark/sql/dataframe.py", line 1197, in collect
> sock_info = self._jdf.collectToPython()
> File "/__w/spark/spark/python/lib/py4j-0.10.9.7-src.zip/py4j/java_gateway.py", line 1322, in __call__
> return_value = get_return_value(
> File "/__w/spark/spark/python/pyspark/sql/utils.py", line 209, in deco
> raise converted from None
> pyspark.sql.utils.PythonException:
> An exception was thrown from the Python worker. Please see the stack trace below.
> Traceback (most recent call last):
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/worker.py", line 829, in main
> process()
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/worker.py", line 821, in process
> serializer.dump_stream(out_iter, outfile)
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py", line 345, in dump_stream
> return ArrowStreamSerializer.dump_stream(self, init_stream_yield_batches(), stream)
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py", line 86, in dump_stream
> for batch in iterator:
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/sql/pandas/serializers.py", line 338, in init_stream_yield_batches
> for series in iterator:
> File "/__w/spark/spark/python/lib/pyspark.zip/pyspark/worker.py", line 519, in func
> for result_batch, result_type in result_iter:
> File "/usr/local/lib/python3.9/dist-packages/mlflow/pyfunc/__init__.py", line 1253, in udf
> yield _predict_row_batch(batch_predict_fn, row_batch_args)
> File "/usr/local/lib/python3.9/dist-packages/mlflow/pyfunc/__init__.py", line 1057, in _predict_row_batch
> result = predict_fn(pdf)
> File "/usr/local/lib/python3.9/dist-packages/mlflow/pyfunc/__init__.py", line 1237, in batch_predict_fn
> return loaded_model.predict(pdf)
> File "/usr/local/lib/python3.9/dist-packages/mlflow/pyfunc/__init__.py", line 413, in predict
> return self._predict_fn(data)
> File "/usr/local/lib/python3.9/dist-packages/sklearn/linear_model/_base.py", line 355, in predict
> return self._decision_function(X)
> File "/usr/local/lib/python3.9/dist-packages/sklearn/linear_model/_base.py", line 338, in _decision_function
> X = self._validate_data(X, accept_sparse=["csr", "csc", "coo"], reset=False)
> File "/usr/local/lib/python3.9/dist-packages/sklearn/base.py", line 518, in _validate_data
> self._check_feature_names(X, reset=reset)
> File "/usr/local/lib/python3.9/dist-packages/sklearn/base.py", line 451, in _check_feature_names
> raise ValueError(message)
> ValueError: The feature names should match those that were passed during fit.
> Feature names unseen at fit time:
> - 0
> - 1
> Feature names seen at fit time, yet now missing:
> - x1
> - x2
> {code}
> https://github.com/apache/spark/actions/runs/3871715040/jobs/6600578830
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