Repository: spark Updated Branches: refs/heads/branch-2.3 521494d7b -> 44933033e
[SPARK-23290][SQL][PYTHON][BACKPORT-2.3] Use datetime.date for date type when converting Spark DataFrame to Pandas DataFrame. ## What changes were proposed in this pull request? This is a backport of #20506. In #18664, there was a change in how `DateType` is being returned to users ([line 1968 in dataframe.py](https://github.com/apache/spark/pull/18664/files#diff-6fc344560230bf0ef711bb9b5573f1faR1968)). This can cause client code which works in Spark 2.2 to fail. See [SPARK-23290](https://issues.apache.org/jira/browse/SPARK-23290?focusedCommentId=16350917&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-16350917) for an example. This pr modifies to use `datetime.date` for date type as Spark 2.2 does. ## How was this patch tested? Tests modified to fit the new behavior and existing tests. Author: Takuya UESHIN <ues...@databricks.com> Closes #20515 from ueshin/issues/SPARK-23290_2.3. Project: http://git-wip-us.apache.org/repos/asf/spark/repo Commit: http://git-wip-us.apache.org/repos/asf/spark/commit/44933033 Tree: http://git-wip-us.apache.org/repos/asf/spark/tree/44933033 Diff: http://git-wip-us.apache.org/repos/asf/spark/diff/44933033 Branch: refs/heads/branch-2.3 Commit: 44933033e9216ccb2e533b9dc6e6cb03cce39817 Parents: 521494d Author: Takuya UESHIN <ues...@databricks.com> Authored: Tue Feb 6 18:29:37 2018 +0900 Committer: hyukjinkwon <gurwls...@gmail.com> Committed: Tue Feb 6 18:29:37 2018 +0900 ---------------------------------------------------------------------- python/pyspark/serializers.py | 9 ++++-- python/pyspark/sql/dataframe.py | 7 ++--- python/pyspark/sql/tests.py | 57 ++++++++++++++++++++++++++---------- python/pyspark/sql/types.py | 15 ++++++++++ 4 files changed, 66 insertions(+), 22 deletions(-) ---------------------------------------------------------------------- http://git-wip-us.apache.org/repos/asf/spark/blob/44933033/python/pyspark/serializers.py ---------------------------------------------------------------------- diff --git a/python/pyspark/serializers.py b/python/pyspark/serializers.py index 88d6a19..e870325 100644 --- a/python/pyspark/serializers.py +++ b/python/pyspark/serializers.py @@ -267,12 +267,15 @@ class ArrowStreamPandasSerializer(Serializer): """ Deserialize ArrowRecordBatches to an Arrow table and return as a list of pandas.Series. """ - from pyspark.sql.types import _check_dataframe_localize_timestamps + from pyspark.sql.types import from_arrow_schema, _check_dataframe_convert_date, \ + _check_dataframe_localize_timestamps import pyarrow as pa reader = pa.open_stream(stream) + schema = from_arrow_schema(reader.schema) for batch in reader: - # NOTE: changed from pa.Columns.to_pandas, timezone issue in conversion fixed in 0.7.1 - pdf = _check_dataframe_localize_timestamps(batch.to_pandas(), self._timezone) + pdf = batch.to_pandas() + pdf = _check_dataframe_convert_date(pdf, schema) + pdf = _check_dataframe_localize_timestamps(pdf, self._timezone) yield [c for _, c in pdf.iteritems()] def __repr__(self): http://git-wip-us.apache.org/repos/asf/spark/blob/44933033/python/pyspark/sql/dataframe.py ---------------------------------------------------------------------- diff --git a/python/pyspark/sql/dataframe.py b/python/pyspark/sql/dataframe.py index 2e55407..59a4170 100644 --- a/python/pyspark/sql/dataframe.py +++ b/python/pyspark/sql/dataframe.py @@ -1923,7 +1923,8 @@ class DataFrame(object): if self.sql_ctx.getConf("spark.sql.execution.arrow.enabled", "false").lower() == "true": try: - from pyspark.sql.types import _check_dataframe_localize_timestamps + from pyspark.sql.types import _check_dataframe_convert_date, \ + _check_dataframe_localize_timestamps from pyspark.sql.utils import require_minimum_pyarrow_version import pyarrow require_minimum_pyarrow_version() @@ -1931,6 +1932,7 @@ class DataFrame(object): if tables: table = pyarrow.concat_tables(tables) pdf = table.to_pandas() + pdf = _check_dataframe_convert_date(pdf, self.schema) return _check_dataframe_localize_timestamps(pdf, timezone) else: return pd.DataFrame.from_records([], columns=self.columns) @@ -2009,7 +2011,6 @@ def _to_corrected_pandas_type(dt): """ When converting Spark SQL records to Pandas DataFrame, the inferred data type may be wrong. This method gets the corrected data type for Pandas if that type may be inferred uncorrectly. - NOTE: DateType is inferred incorrectly as 'object', TimestampType is correct with datetime64[ns] """ import numpy as np if type(dt) == ByteType: @@ -2020,8 +2021,6 @@ def _to_corrected_pandas_type(dt): return np.int32 elif type(dt) == FloatType: return np.float32 - elif type(dt) == DateType: - return 'datetime64[ns]' else: return None http://git-wip-us.apache.org/repos/asf/spark/blob/44933033/python/pyspark/sql/tests.py ---------------------------------------------------------------------- diff --git a/python/pyspark/sql/tests.py b/python/pyspark/sql/tests.py index 0d5bc13..95b9c0e 100644 --- a/python/pyspark/sql/tests.py +++ b/python/pyspark/sql/tests.py @@ -2810,7 +2810,7 @@ class SQLTests(ReusedSQLTestCase): self.assertEquals(types[1], np.object) self.assertEquals(types[2], np.bool) self.assertEquals(types[3], np.float32) - self.assertEquals(types[4], 'datetime64[ns]') + self.assertEquals(types[4], np.object) # datetime.date self.assertEquals(types[5], 'datetime64[ns]') @unittest.skipIf(not _have_old_pandas, "Old Pandas not installed") @@ -3356,7 +3356,7 @@ class ArrowTests(ReusedSQLTestCase): @classmethod def setUpClass(cls): - from datetime import datetime + from datetime import date, datetime from decimal import Decimal ReusedSQLTestCase.setUpClass() @@ -3378,11 +3378,11 @@ class ArrowTests(ReusedSQLTestCase): StructField("7_date_t", DateType(), True), StructField("8_timestamp_t", TimestampType(), True)]) cls.data = [(u"a", 1, 10, 0.2, 2.0, Decimal("2.0"), - datetime(1969, 1, 1), datetime(1969, 1, 1, 1, 1, 1)), + date(1969, 1, 1), datetime(1969, 1, 1, 1, 1, 1)), (u"b", 2, 20, 0.4, 4.0, Decimal("4.0"), - datetime(2012, 2, 2), datetime(2012, 2, 2, 2, 2, 2)), + date(2012, 2, 2), datetime(2012, 2, 2, 2, 2, 2)), (u"c", 3, 30, 0.8, 6.0, Decimal("6.0"), - datetime(2100, 3, 3), datetime(2100, 3, 3, 3, 3, 3))] + date(2100, 3, 3), datetime(2100, 3, 3, 3, 3, 3))] @classmethod def tearDownClass(cls): @@ -3435,7 +3435,9 @@ class ArrowTests(ReusedSQLTestCase): def test_toPandas_arrow_toggle(self): df = self.spark.createDataFrame(self.data, schema=self.schema) pdf, pdf_arrow = self._toPandas_arrow_toggle(df) - self.assertFramesEqual(pdf_arrow, pdf) + expected = self.create_pandas_data_frame() + self.assertFramesEqual(expected, pdf) + self.assertFramesEqual(expected, pdf_arrow) def test_toPandas_respect_session_timezone(self): df = self.spark.createDataFrame(self.data, schema=self.schema) @@ -4036,18 +4038,42 @@ class VectorizedUDFTests(ReusedSQLTestCase): with self.assertRaisesRegexp(Exception, 'Unsupported data type'): df.select(f(col('map'))).collect() - def test_vectorized_udf_null_date(self): + def test_vectorized_udf_dates(self): from pyspark.sql.functions import pandas_udf, col from datetime import date - schema = StructType().add("date", DateType()) - data = [(date(1969, 1, 1),), - (date(2012, 2, 2),), - (None,), - (date(2100, 4, 4),)] + schema = StructType().add("idx", LongType()).add("date", DateType()) + data = [(0, date(1969, 1, 1),), + (1, date(2012, 2, 2),), + (2, None,), + (3, date(2100, 4, 4),)] df = self.spark.createDataFrame(data, schema=schema) - date_f = pandas_udf(lambda t: t, returnType=DateType()) - res = df.select(date_f(col("date"))) - self.assertEquals(df.collect(), res.collect()) + + date_copy = pandas_udf(lambda t: t, returnType=DateType()) + df = df.withColumn("date_copy", date_copy(col("date"))) + + @pandas_udf(returnType=StringType()) + def check_data(idx, date, date_copy): + import pandas as pd + msgs = [] + is_equal = date.isnull() + for i in range(len(idx)): + if (is_equal[i] and data[idx[i]][1] is None) or \ + date[i] == data[idx[i]][1]: + msgs.append(None) + else: + msgs.append( + "date values are not equal (date='%s': data[%d][1]='%s')" + % (date[i], idx[i], data[idx[i]][1])) + return pd.Series(msgs) + + result = df.withColumn("check_data", + check_data(col("idx"), col("date"), col("date_copy"))).collect() + + self.assertEquals(len(data), len(result)) + for i in range(len(result)): + self.assertEquals(data[i][1], result[i][1]) # "date" col + self.assertEquals(data[i][1], result[i][2]) # "date_copy" col + self.assertIsNone(result[i][3]) # "check_data" col def test_vectorized_udf_timestamps(self): from pyspark.sql.functions import pandas_udf, col @@ -4088,6 +4114,7 @@ class VectorizedUDFTests(ReusedSQLTestCase): self.assertEquals(len(data), len(result)) for i in range(len(result)): self.assertEquals(data[i][1], result[i][1]) # "timestamp" col + self.assertEquals(data[i][1], result[i][2]) # "timestamp_copy" col self.assertIsNone(result[i][3]) # "check_data" col def test_vectorized_udf_return_timestamp_tz(self): http://git-wip-us.apache.org/repos/asf/spark/blob/44933033/python/pyspark/sql/types.py ---------------------------------------------------------------------- diff --git a/python/pyspark/sql/types.py b/python/pyspark/sql/types.py index 0dc5823..093dae5 100644 --- a/python/pyspark/sql/types.py +++ b/python/pyspark/sql/types.py @@ -1694,6 +1694,21 @@ def from_arrow_schema(arrow_schema): for field in arrow_schema]) +def _check_dataframe_convert_date(pdf, schema): + """ Correct date type value to use datetime.date. + + Pandas DataFrame created from PyArrow uses datetime64[ns] for date type values, but we should + use datetime.date to match the behavior with when Arrow optimization is disabled. + + :param pdf: pandas.DataFrame + :param schema: a Spark schema of the pandas.DataFrame + """ + for field in schema: + if type(field.dataType) == DateType: + pdf[field.name] = pdf[field.name].dt.date + return pdf + + def _check_dataframe_localize_timestamps(pdf, timezone): """ Convert timezone aware timestamps to timezone-naive in the specified timezone or local timezone --------------------------------------------------------------------- To unsubscribe, e-mail: commits-unsubscr...@spark.apache.org For additional commands, e-mail: commits-h...@spark.apache.org
