# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not use this file except in compliance # with the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, # software distributed under the License is distributed on an # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY # KIND, either express or implied. See the License for the # specific language governing permissions and limitations # under the License. # # Tests for Hive-IMPALA text compression codec interoperability import pytest from tests.common.custom_cluster_test_suite import CustomClusterTestSuite from tests.common.environ import HIVE_MAJOR_VERSION from tests.common.skip import SkipIfS3 from tests.common.test_dimensions import create_exec_option_dimension from tests.common.test_result_verifier import verify_query_result_is_equal # compression codecs impala support reading in text file type TEXT_CODECS = ['snappy', 'gzip', 'zstd', 'bzip2', 'deflate', 'default'] class TestTextInterop(CustomClusterTestSuite): @classmethod def get_workload(self): return 'functional-query' @classmethod def setup_class(cls): if cls.exploration_strategy() != 'exhaustive': pytest.skip('runs only in exhaustive') super(TestTextInterop, cls).setup_class() @classmethod def add_test_dimensions(cls): super(CustomClusterTestSuite, cls).add_test_dimensions() # Fix the exec_option vector to have a single value. cls.ImpalaTestMatrix.add_dimension(create_exec_option_dimension( cluster_sizes=[0], disable_codegen_options=[False], batch_sizes=[0], sync_ddl=[1])) cls.ImpalaTestMatrix.add_constraint( lambda v: v.get_value('table_format').file_format == 'textfile') @SkipIfS3.hive @pytest.mark.execute_serially def test_hive_impala_interop(self, unique_database, cluster_properties): """Tests compressed text file written by Hive with different codecs can be read from impala. And verify results.""" # Setup source table. source_table = "{0}.{1}".format(unique_database, "t1_source") # TODO: Once IMPALA-8721 is fixed add coverage for TimeStamp data type. self.execute_query_expect_success(self.client, "create table {0} stored as textfile as select id, bool_col, tinyint_col, " "smallint_col, int_col, bigint_col, float_col, double_col, date_string_col," "string_col, year, month from functional_parquet.alltypes".format(source_table)) self.execute_query_expect_success(self.client, "insert into {0}(id) values (7777), (8888), (9999), (11111), (22222), (33333)" .format(source_table)) # For Hive 3+, workaround for HIVE-22371 (CTAS puts files in the wrong place) by # explicitly creating an external table so that files are in the external warehouse # directory. Use external.table.purge=true so that it is equivalent to a Hive 2 # managed table. Hive 2 stays the same. external = "" tblproperties = "" if HIVE_MAJOR_VERSION >= 3: external = "external" tblproperties = "TBLPROPERTIES('external.table.purge'='TRUE')" # Loop through the compression codecs and run interop tests. for codec in TEXT_CODECS: # Write data in Hive and read from Impala # switch codec to format hive can accept switcher = { 'snappy': 'org.apache.hadoop.io.compress.SnappyCodec', 'gzip': 'org.apache.hadoop.io.compress.GzipCodec', 'zstd': 'org.apache.hadoop.io.compress.ZStandardCodec', 'bzip2': 'org.apache.hadoop.io.compress.BZip2Codec', 'deflate': 'org.apache.hadoop.io.compress.DeflateCodec', 'default': 'org.apache.hadoop.io.compress.DefaultCodec' } hive_table = "{0}.{1}".format(unique_database, "t1_hive") self.run_stmt_in_hive("drop table if exists {0}".format(hive_table)) self.run_stmt_in_hive("set hive.exec.compress.output=true;\ set mapreduce.output.fileoutputformat.compress.codec={0};\ create {1} table {2} stored as textfile {3} as select * from {4}" .format(switcher.get(codec, 'Invalid codec'), external, hive_table, tblproperties, source_table)) # Make sure hive CTAS table is not empty assert self.run_stmt_in_hive("select count(*) from {0}".format( hive_table)).split("\n")[1] != "0", "CTAS created Hive table is empty." # Make sure Impala's metadata is in sync. if cluster_properties.is_catalog_v2_cluster(): self.wait_for_table_to_appear(unique_database, hive_table, timeout_s=10) else: self.client.execute("invalidate metadata {0}".format(hive_table)) # Read Hive data in Impala and verify results. base_result = self.execute_query_expect_success(self.client, "select * from {0} order by id".format(source_table)) test_result = self.execute_query_expect_success(self.client, "select * from {0} order by id".format(hive_table)) verify_query_result_is_equal(test_result.data, base_result.data)