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The Impala CatalogService manages the caching and dissemination of cluster-wide metadata. The CatalogService combines the metadata from the Hive Metastore, the NameNode, and potentially additional sources in the future. The CatalogService uses the StateStore to broadcast metadata updates across the cluster. The CatalogService also directly handles executing metadata updates request from impalad servers (DDL requests). It exposes a Thrift interface to allow impalads to directly connect execute their DDL operations. The CatalogService has two main components - a C++ server that implements StateStore integration, Thrift service implementiation, and exporting of the debug webpage/metrics. The other main component is the Java Catalog that manages caching and updating of of all the metadata. For each StateStore heartbeat, a delta of all metadata updates is broadcast to the rest of the cluster. Some Notes On the Changes --- * The metadata is all sent as thrift structs. To do this all catalog objects (Tables/Views, Databases, UDFs) have thrift struct to represent them. These are sent with each statestore delta update. * The existing Catalog class has been seperated into two seperate sub-classes. An ImpladCatalog and a CatalogServiceCatalog. See the comments on those classes for more details. What is working: * New CatalogService created * Working with statestore delta updates and latest UDF changes * DDL performed on Node 1 is now visible on all other nodes without a "refresh". * Each DDL operation against the Catalog Service will return the catalog version that contains the change. An impalad will wait for the statestore heartbeat that contains this version before returning from the DDL comment. * All table types (Hbase, Hdfs, Views) getting their metadata propagated properly * Block location information included in CS updates and used by Impalads * Column and table stats included in CS updates and used by Impalads * Query tests are all passing Still TODO: * Directly return catalog object metadata from DDL requests * Poll the Hive Metastore to detect new/dropped/modified tables * Reorganize the FE code for the Catalog Service. I don't think we want everything in the same JAR. Change-Id: I8c61296dac28fb98bcfdc17361f4f141d3977eda Reviewed-on: http://gerrit.ent.cloudera.com:8080/601 Reviewed-by: Lenni Kuff <lskuff@cloudera.com> Tested-by: Lenni Kuff <lskuff@cloudera.com>
57 lines
2.3 KiB
Python
57 lines
2.3 KiB
Python
#!/usr/bin/env python
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# Copyright (c) 2012 Cloudera, Inc. All rights reserved.
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# Targeted Impala insert tests
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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 *
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from tests.common.test_dimensions import create_exec_option_dimension
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# TODO: Add Gzip back. IMPALA-424
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PARQUET_CODECS = ['none', 'snappy']
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class TestInsertQueries(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(TestInsertQueries, cls).add_test_dimensions()
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# Fix the exec_option vector to have a single value. This is needed should we decide
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# to run the insert tests in parallel (otherwise there will be two tests inserting
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# into the same table at the same time for the same file format).
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# TODO: When we do decide to run these tests in parallel we could create unique temp
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# tables for each test case to resolve the concurrency problems.
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cls.TestMatrix.add_dimension(create_exec_option_dimension(
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cluster_sizes=[0], disable_codegen_options=[False], batch_sizes=[0]))
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cls.TestMatrix.add_dimension(TestDimension("compression_codec", *PARQUET_CODECS));
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# Insert is currently only supported for text and parquet
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# For parquet, we want to iterate through all the compression codecs
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# TODO: each column in parquet can have a different codec. We could
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# test all the codecs in one table/file with some additional flags.
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cls.TestMatrix.add_constraint(lambda v:\
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v.get_value('table_format').file_format == 'parquet' or \
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(v.get_value('table_format').file_format == 'text' and \
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v.get_value('compression_codec') == 'none'))
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cls.TestMatrix.add_constraint(lambda v:\
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v.get_value('table_format').compression_codec == 'none')
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@classmethod
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def setup_class(cls):
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super(TestInsertQueries, cls).setup_class()
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cls.client.refresh()
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@pytest.mark.execute_serially
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def test_insert1(self, vector):
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vector.get_value('exec_option')['PARQUET_COMPRESSION_CODEC'] = \
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vector.get_value('compression_codec')
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self.run_test_case('QueryTest/insert', vector)
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@pytest.mark.execute_serially
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def test_insert_overwrite(self, vector):
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self.run_test_case('QueryTest/insert_overwrite', vector)
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