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82bd087fb1
This takes steps to make Python 2 behave like Python 3 as
a way to flush out issues with running on Python 3. Specifically,
it handles two main differences:
1. Python 3 requires absolute imports within packages. This
can be emulated via "from __future__ import absolute_import"
2. Python 3 changed division to "true" division that doesn't
round to an integer. This can be emulated via
"from __future__ import division"
This changes all Python files to add imports for absolute_import
and division. For completeness, this also includes print_function in the
import.
I scrutinized each old-division location and converted some locations
to use the integer division '//' operator if it needed an integer
result (e.g. for indices, counts of records, etc). Some code was also using
relative imports and needed to be adjusted to handle absolute_import.
This fixes all Pylint warnings about no-absolute-import and old-division,
and these warnings are now banned.
Testing:
- Ran core tests
Change-Id: Idb0fcbd11f3e8791f5951c4944be44fb580e576b
Reviewed-on: http://gerrit.cloudera.org:8080/19588
Reviewed-by: Joe McDonnell <joemcdonnell@cloudera.com>
Tested-by: Joe McDonnell <joemcdonnell@cloudera.com>
69 lines
3.2 KiB
Python
69 lines
3.2 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from __future__ import absolute_import, division, print_function
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import pytest
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from tests.common.custom_cluster_test_suite import CustomClusterTestSuite
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from tests.common.test_dimensions import (
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create_exec_option_dimension,
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create_single_exec_option_dimension,
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create_uncompressed_text_dimension)
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class TestStatsExtrapolation(CustomClusterTestSuite):
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"""Minimal end-to-end test for the --enable_stats_extrapolation impalad flag. This test
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primarly checks that the flag is propagated to the FE. More testing is done in FE unit
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tests and metadata/test_stats_extrapolation.py."""
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@classmethod
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def get_workload(self):
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return 'functional-query'
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@classmethod
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def add_test_dimensions(cls):
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super(TestStatsExtrapolation, cls).add_test_dimensions()
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cls.ImpalaTestMatrix.add_dimension(create_single_exec_option_dimension())
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cls.ImpalaTestMatrix.add_dimension(
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create_uncompressed_text_dimension(cls.get_workload()))
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@pytest.mark.execute_serially
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@CustomClusterTestSuite.with_args(impalad_args="--enable_stats_extrapolation=true")
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def test_stats_extrapolation(self, vector, unique_database):
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# Test row count extrapolation
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self.client.execute("set explain_level=2")
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explain_result = self.client.execute("explain select * from functional.alltypes")
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assert "extrapolated-rows=7.30K" in " ".join(explain_result.data)
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# Test COMPUTE STATS TABLESAMPLE
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part_test_tbl = unique_database + ".alltypes"
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self.clone_table("functional.alltypes", part_test_tbl, True, vector)
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# Since our test tables are small, set the minimum sample size to 0 to make sure
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# we exercise the sampling code paths.
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self.client.execute("set COMPUTE_STATS_MIN_SAMPLE_SIZE=0")
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self.client.execute(
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"compute stats {0} tablesample system (13)".format(part_test_tbl))
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# Check that table stats were set.
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table_stats = self.client.execute("show table stats {0}".format(part_test_tbl))
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col_names = [fs.name.upper() for fs in table_stats.schema.fieldSchemas]
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extrap_rows_idx = col_names.index("EXTRAP #ROWS")
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for row in table_stats.data:
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assert int(row.split("\t")[extrap_rows_idx]) >= 0
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# Check that column stats were set.
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col_stats = self.client.execute("show column stats {0}".format(part_test_tbl))
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col_names = [fs.name.upper() for fs in col_stats.schema.fieldSchemas]
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ndv_col_idx = col_names.index("#DISTINCT VALUES")
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for row in col_stats.data:
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assert int(row.split("\t")[ndv_col_idx]) >= 0
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