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This patch leverages the AdlFileSystem in Hadoop to allow Impala to talk to the Azure Data Lake Store. This patch has functional changes as well as adds test infrastructure for testing Impala over ADLS. We do not support ACLs on ADLS since the Hadoop ADLS connector does not integrate ADLS ACLs with Hadoop users/groups. For testing, we use the azure-data-lake-store-python client from Microsoft. This client seems to have some consistency issues. For example, a drop table through Impala will delete the files in ADLS, however, listing that directory through the python client immediately after the drop, will still show the files. This behavior is unexpected since ADLS claims to be strongly consistent. Some tests have been skipped due to this limitation with the tag SkipIfADLS.slow_client. Tracked by IMPALA-5335. The azure-data-lake-store-python client also only works on CentOS 6.6 and over, so the python dependencies for Azure will not be downloaded when the TARGET_FILESYSTEM is not "adls". While running ADLS tests, the expectation will be that it runs on a machine that is at least running CentOS 6.6. Note: This is only a test limitation, not a functional one. Clusters with older OSes like CentOS 6.4 will still work with ADLS. Added another dependency to bootstrap_build.sh for the ADLS Python client. Testing: Ran core tests with and without TARGET_FILESYSTEM as 'adls' to make sure that all tests pass and that nothing breaks. Change-Id: Ic56b9988b32a330443f24c44f9cb2c80842f7542 Reviewed-on: http://gerrit.cloudera.org:8080/6910 Tested-by: Impala Public Jenkins Reviewed-by: Sailesh Mukil <sailesh@cloudera.com>
92 lines
4.0 KiB
Python
92 lines
4.0 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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import pytest
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from tests.beeswax.impala_beeswax import ImpalaBeeswaxException
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from tests.common.impala_test_suite import ImpalaTestSuite
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from tests.common.skip import SkipIfS3, SkipIfADLS, SkipIfIsilon, SkipIfLocal
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from tests.common.test_dimensions import create_single_exec_option_dimension
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# Tests to validate HDFS partitioning.
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class TestPartitioning(ImpalaTestSuite):
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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(TestPartitioning, cls).add_test_dimensions()
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cls.ImpalaTestMatrix.add_dimension(create_single_exec_option_dimension())
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# There is no reason to run these tests using all dimensions.
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cls.ImpalaTestMatrix.add_constraint(lambda v:\
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v.get_value('table_format').file_format == 'text' and\
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v.get_value('table_format').compression_codec == 'none')
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@SkipIfLocal.root_path
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def test_partition_col_types(self, vector, unique_database):
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self.run_test_case('QueryTest/partition-col-types', vector,
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use_db=unique_database)
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# Missing Coverage: Impala deals with boolean partitions created by Hive on a non-hdfs
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# filesystem.
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@SkipIfS3.hive
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@SkipIfADLS.hive
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@SkipIfIsilon.hive
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@SkipIfLocal.hive
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def test_boolean_partitions(self, vector, unique_database):
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# This test takes about a minute to complete due to the Hive commands that are
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# executed. To cut down on runtime, limit the test to exhaustive exploration
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# strategy.
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if self.exploration_strategy() != 'exhaustive': pytest.skip()
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full_name = unique_database + ".bool_test"
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self.execute_query("create table %s (i int) partitioned by (b boolean)" % full_name)
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# Insert some data using Hive. Due to HIVE-6590, Hive may create multiple
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# partitions, mapping to the same boolean literal value.
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# For example, Hive may create partitions: /b=FALSE and /b=false, etc
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self.run_stmt_in_hive("INSERT INTO TABLE %s PARTITION(b=false) SELECT 1 from "\
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"functional.alltypes limit 1" % full_name)
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self.run_stmt_in_hive("INSERT INTO TABLE %s PARTITION(b=FALSE) SELECT 2 from "\
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"functional.alltypes limit 1" % full_name)
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self.run_stmt_in_hive("INSERT INTO TABLE %s PARTITION(b=true) SELECT 10 from "\
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"functional.alltypes limit 1" % full_name)
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# Update the Impala metadata
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self.execute_query("invalidate metadata " + full_name)
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# List the partitions. Show table stats returns 1 row for each partition + 1 summary
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# row
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result = self.execute_query("show table stats %s" % full_name)
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assert len(result.data) == 3 + 1
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# Verify Impala properly merges the results of the bad Hive metadata.
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assert '13' == self.execute_scalar("select sum(i) from %s" % full_name);
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assert '10' == self.execute_scalar("select sum(i) from %s where b=true" % full_name)
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assert '3' == self.execute_scalar("select sum(i) from %s where b=false" % full_name)
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# INSERT into a boolean column is disabled in Impala due to this Hive bug.
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try:
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self.execute_query("insert into %s partition(bool_col=true) select 1" % full_name)
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except ImpalaBeeswaxException, e:
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assert 'AnalysisException: INSERT into table with BOOLEAN partition column (%s) '\
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'is not supported: %s' % ('b', full_name) in str(e)
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