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30dbf59ef2
With this change the Python tests will now be called as part of buildall and the corresponding Java tests have been disabled. The new tests can also be invoked calling ./tests/run-tests.sh directly. This includes a fix from Nong that caused wrong results for limit on non-io manager formats.
60 lines
2.4 KiB
Python
60 lines
2.4 KiB
Python
#!/usr/bin/env python
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# Copyright (c) 2012 Cloudera, Inc. All rights reserved.
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# Validates all aggregate functions across all datatypes
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#
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import logging
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import pytest
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from tests.common.test_vector import *
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from tests.common.impala_test_suite import ImpalaTestSuite
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agg_functions = ['sum', 'count', 'min', 'max', 'avg']
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data_types = ['int', 'bool', 'double', 'bigint', 'tinyint',
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'smallint', 'float', 'timestamp']
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result_lut = {
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# TODO: Add verification for other types
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'sum-tinyint': 45000, 'avg-tinyint': 5, 'count-tinyint': 9000,
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'min-tinyint': 1, 'max-tinyint': 9,
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'sum-smallint': 495000, 'avg-smallint': 50, 'count-smallint': 9900,
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'min-smallint': 1, 'max-smallint': 99,
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'sum-int': 4995000, 'avg-int': 500, 'count-int': 9990,
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'min-int': 1, 'max-int': 999,
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'sum-bigint': 49950000, 'avg-bigint': 5000, 'count-bigint': 9990,
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'min-bigint': 10, 'max-bigint': 9990,
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}
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class TestAggregation(ImpalaTestSuite):
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@classmethod
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def get_dataset(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(TestAggregation, cls).add_test_dimensions()
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# Add two more dimensions
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cls.TestMatrix.add_dimension(TestDimension('agg_func', *agg_functions))
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cls.TestMatrix.add_dimension(TestDimension('data_type', *data_types))
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# Only execute against text format, restrict bool types to min/max
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cls.TestMatrix.add_constraint(\
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lambda v: v.get_value('table_format').file_format == 'text')
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cls.TestMatrix.add_constraint(lambda v: v.get_value('exec_option')['batch_size'] == 0)
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cls.TestMatrix.add_constraint(lambda v: v.get_value('agg_func') in ['min', 'max'] if\
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v.get_value('data_type') == 'bool' else True)
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def test_aggregation(self, vector):
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data_type, agg_func = (vector.get_value('data_type'), vector.get_value('agg_func'))
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query = 'select %s(%s_col) from alltypesagg' % (agg_func, data_type)
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result = self.execute_scalar(query, vector.get_value('exec_option'))
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if 'int' in data_type:
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assert result_lut['%s-%s' % (agg_func, data_type)] == int(result)
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# AVG
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if vector.get_value('data_type') == 'timestamp' and\
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vector.get_value('agg_func') == 'avg':
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return
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query = 'select %s(DISTINCT(%s_col)) from alltypesagg' % (agg_func, data_type)
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result = self.execute_scalar(query, vector.get_value('exec_option'))
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