So the spark integration build started to fail, and with the following test error:
====================================================================== ERROR: test_toPandas_batch_order (pyspark.sql.tests.test_arrow.EncryptionArrowTests) ---------------------------------------------------------------------- Traceback (most recent call last): File "/spark/python/pyspark/sql/tests/test_arrow.py", line 422, in test_toPandas_batch_order run_test(*case) File "/spark/python/pyspark/sql/tests/test_arrow.py", line 409, in run_test pdf, pdf_arrow = self._toPandas_arrow_toggle(df) File "/spark/python/pyspark/sql/tests/test_arrow.py", line 152, in _toPandas_arrow_toggle pdf_arrow = df.toPandas() File "/spark/python/pyspark/sql/pandas/conversion.py", line 115, in toPandas return _check_dataframe_localize_timestamps(pdf, timezone) File "/spark/python/pyspark/sql/pandas/types.py", line 180, in _check_dataframe_localize_timestamps pdf[column] = _check_series_localize_timestamps(series, timezone) File "/opt/conda/envs/arrow/lib/python3.7/site-packages/pandas/core/frame.py", line 3487, in __setitem__ self._set_item(key, value) File "/opt/conda/envs/arrow/lib/python3.7/site-packages/pandas/core/frame.py", line 3565, in _set_item NDFrame._set_item(self, key, value) File "/opt/conda/envs/arrow/lib/python3.7/site-packages/pandas/core/generic.py", line 3381, in _set_item self._data.set(key, value) File "/opt/conda/envs/arrow/lib/python3.7/site-packages/pandas/core/internals/managers.py", line 1090, in set blk.set(blk_locs, value_getitem(val_locs)) File "/opt/conda/envs/arrow/lib/python3.7/site-packages/pandas/core/internals/blocks.py", line 380, in set self.values[locs] = values ValueError: assignment destination is read-only It's from a test that is doing conversions from spark to arrow to pandas (so calling pyarrow.Table.to_pandas here <https://github.com/apache/spark/blob/018bdcc53c925072b07956de0600452ad255b9c7/python/pyspark/sql/pandas/conversion.py#L111-L115>), and on the resulting DataFrame, it is iterating through all columns, potentially fixing timezones, and writing each column back into the DataFrame (here <https://github.com/apache/spark/blob/018bdcc53c925072b07956de0600452ad255b9c7/python/pyspark/sql/pandas/types.py#L179-L181> ). Since it is giving an error about read-only, it might be related to zero-copy behaviour of to_pandas, and thus might be related to the refactor of the arrow->pandas conversion that landed yesterday ( https://github.com/apache/arrow/pull/6067, it says it changed to do zero-copy for 1-column blocks if possible). I am not sure if something should be fixed in pyarrow for this, but the obvious thing that pyspark can do is specify they don't want zero-copy. Joris On Wed, 15 Jan 2020 at 14:32, Crossbow <cross...@ursalabs.org> wrote: > > Arrow Build Report for Job nightly-2020-01-15-0 > > All tasks: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0 > > Failed Tasks: > - gandiva-jar-osx: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-travis-gandiva-jar-osx > - test-conda-python-3.7-spark-master: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-circle-test-conda-python-3.7-spark-master > - wheel-manylinux2014-cp35m: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-azure-wheel-manylinux2014-cp35m > > Succeeded Tasks: > - centos-6: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-azure-centos-6 > - centos-7: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-azure-centos-7 > - centos-8: > URL: > https://github.com/ursa-labs/crossbow/branches/all?query=nightly-2020-01-15-0-azure-centos-8 > - 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