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2f5aef64a5
TPC-DS v2.11.0, section 2.4.7, rename column customer.c_last_review_date
to customer.c_last_review_date_sk to align with other surrogate key
columns. impala-tpcds-kit has been modified to reflect this column name
change in
086d7113c8
However, the tpcds dataset schema in Impala test data remains unchanged.
This patch did such a rename to align closer to TPC-DS v2.11.0. This
patch contains no data type adjustment because such adjustment requires
larger changes.
customer_multiblock_page_index.parquet added by IMPALA-10310 is
regenerated to follow the new schema of table customer. The SQL used to
create the file is ordered more specifically over both
c_current_cdemo_sk and c_customer_sk columns. The associated test
assertion in parquet-page-index.test is also updated.
A workaround in test_file_parser.py added by IMPALA-13543 is now removed
after this change is applied.
Testing:
- Pass core tests.
Change-Id: Ie446b3c534cb8f6f54265cd9b2f705cad91dd4ac
Reviewed-on: http://gerrit.cloudera.org:8080/22223
Reviewed-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
Tested-by: Impala Public Jenkins <impala-public-jenkins@cloudera.com>
503 lines
21 KiB
Python
503 lines
21 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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# This module is used for common utilities related to parsing test files
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from __future__ import absolute_import, division, print_function
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from builtins import map
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import codecs
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import collections
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import logging
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import os
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import os.path
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import re
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from collections import defaultdict
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from textwrap import dedent
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LOG = logging.getLogger('impala_test_suite')
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# constants
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SECTION_DELIMITER = "===="
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SUBSECTION_DELIMITER = "----"
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ALLOWED_TABLE_FORMATS = ['kudu', 'parquet', 'orc']
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# The QueryTestSectionReader provides utility functions that help to parse content
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# from a query test file
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class QueryTestSectionReader(object):
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@staticmethod
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def build_query(query_section_text):
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"""Build a query by stripping comments and trailing newlines and semi-colons."""
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query_section_text = remove_comments(query_section_text)
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return query_section_text.rstrip("\n;")
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@staticmethod
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def get_table_name_components(table_format, table_name, scale_factor=''):
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"""
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Returns a pair (db_name, tbl_name). If the table_name argument is
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fully qualified, return the database name mentioned there,
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otherwise get the default db name from the table format and scale
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factor.
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"""
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# If table name is fully qualified return the db prefix
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split = table_name.split('.')
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assert len(split) <= 2, 'Unexpected table format: %s' % table_name
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db_name = split[0] if len(split) == 2 else \
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QueryTestSectionReader.get_db_name(table_format, scale_factor)
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return (db_name, split[-1])
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@staticmethod
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def get_db_name(table_format, scale_factor=''):
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"""
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Get the database name to use.
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Database names are dependent on the scale factor, file format, compression type
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and compression codec. This method returns the appropriate database name to the
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caller based on the table format information provided.
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"""
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if table_format.file_format == 'text' and table_format.compression_codec == 'none':
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suffix = ''
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elif table_format.compression_codec == 'none':
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suffix = '_%s' % (table_format.file_format)
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elif table_format.compression_type == 'record':
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suffix = '_%s_record_%s' % (table_format.file_format,
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table_format.compression_codec)
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else:
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suffix = '_%s_%s' % (table_format.file_format, table_format.compression_codec)
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dataset = table_format.dataset.replace('-', '')
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return dataset + scale_factor + suffix
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def remove_comments(section_text):
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lines = [line for line in section_text.split('\n') if not line.strip().startswith('#')]
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return '\n'.join(lines)
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def parse_query_test_file(file_name, valid_section_names=None, encoding=None):
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"""
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Reads the specified query test file accepting the given list of valid section names
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Uses a default list of valid section names if valid_section_names is None
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Returns the result as a list of dictionaries. Each dictionary in the list corresponds
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to a test case and each key in the dictionary maps to a section in that test case.
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"""
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# Update the valid section names as we support other test types
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# (ex. planner, data error)
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section_names = valid_section_names
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if section_names is None:
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section_names = ['QUERY', 'HIVE_QUERY', 'RESULTS', 'TYPES', 'LABELS', 'SETUP',
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'CATCH', 'ERRORS', 'USER', 'RUNTIME_PROFILE', 'SHELL', 'DML_RESULTS',
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'HS2_TYPES', 'HIVE_MAJOR_VERSION', 'LINEAGE', 'IS_HDFS_ONLY']
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return parse_test_file(file_name, section_names, encoding=encoding,
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skip_unknown_sections=False)
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def parse_table_constraints(constraints_file):
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"""Reads a table constraints file, if one exists"""
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schema_include = defaultdict(list)
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schema_exclude = defaultdict(list)
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schema_only = defaultdict(list)
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if not os.path.isfile(constraints_file):
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LOG.info('No schema constraints file file found')
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else:
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with open(constraints_file, 'r') as constraints_file:
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for line in constraints_file.readlines():
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line = line.strip()
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if not line or line.startswith('#'):
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continue
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# Format: table_name:<name>, constraint_type:<type>, table_format:<t1>,<t2>,...
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table_name, constraint_type, table_formats =\
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[value.split(':')[1].strip() for value in line.split(',', 2)]
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# 'only' constraint -- If a format defines an only constraint, only those tables
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# collected for the same table_format will be created.
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if constraint_type == 'only':
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for f in map(parse_table_format_constraint, table_formats.split(',')):
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schema_only[f].append(table_name.lower())
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elif constraint_type == 'restrict_to':
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schema_include[table_name.lower()] +=\
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list(map(parse_table_format_constraint, table_formats.split(',')))
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elif constraint_type == 'exclude':
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schema_exclude[table_name.lower()] +=\
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list(map(parse_table_format_constraint, table_formats.split(',')))
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else:
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raise ValueError('Unknown constraint type: %s' % constraint_type)
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return schema_include, schema_exclude, schema_only
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def parse_table_format_constraint(table_format_constraint):
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# TODO: Expand how we parse table format constraints to support syntax such as
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# a table format string with a wildcard character. Right now we don't do anything.
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return table_format_constraint
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def parse_test_file(test_file_name, valid_section_names, skip_unknown_sections=True,
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encoding=None):
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"""
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Parses an Impala test file
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Test files have the format:
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==== <- Section
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---- [Name] <- Named subsection
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// some text
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---- [Name2] <- Named subsection
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...
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====
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The valid section names are passed in to this function. The encoding to use
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when reading the data can be specified with the 'encoding' flag.
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"""
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with open(test_file_name, 'rb') as test_file:
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file_data = test_file.read()
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if encoding:
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file_data = file_data.decode(encoding)
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else:
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file_data = file_data.decode('utf-8')
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if os.environ["USE_APACHE_HIVE"] == "true":
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# Remove Hive 4.0 feature for tpcds_schema_template.sql
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if "tpcds_schema_template" in test_file_name:
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# HIVE-20703
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file_data = file_data.replace(
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'set hive.optimize.sort.dynamic.partition.threshold=1;', '')
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# HIVE-18284
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file_data = file_data.replace('distribute by ss_sold_date_sk', '')
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return parse_test_file_text(file_data, valid_section_names,
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skip_unknown_sections)
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def parse_runtime_profile_table_formats(subsection_comment):
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prefix = "table_format="
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if not subsection_comment.startswith(prefix):
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raise RuntimeError('RUNTIME_PROFILE comment (%s) must be of the form '
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'"table_format=FORMAT[,FORMAT2,...]"' % subsection_comment)
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parsed_formats = subsection_comment[len(prefix):].split(',')
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table_formats = list()
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for table_format in parsed_formats:
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if table_format not in ALLOWED_TABLE_FORMATS:
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raise RuntimeError('RUNTIME_PROFILE table format (%s) must be in: %s' %
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(table_format, ALLOWED_TABLE_FORMATS))
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else:
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table_formats.append(table_format)
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return table_formats
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def parse_test_file_text(text, valid_section_names, skip_unknown_sections=True):
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sections = list()
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section_start_regex = re.compile(r'(?m)^%s' % SECTION_DELIMITER)
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match = section_start_regex.search(text)
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if match is not None:
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# Assume anything before the first section (==== tag) is a header and ignore it. To
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# ensure that test will not be skipped unintentionally we reject headers that start
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# with what looks like a subsection.
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header = text[:match.start()]
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if re.match(r'^%s' % SUBSECTION_DELIMITER, header):
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raise RuntimeError(dedent("""
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Header must not start with '%s'. Everything before the first line matching '%s'
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is considered header information and will be ignored. However a header must not
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start with '%s' to prevent test cases from accidentally being ignored.""" %
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(SUBSECTION_DELIMITER, SECTION_DELIMITER, SUBSECTION_DELIMITER)))
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text = text[match.start():]
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# Split the test file up into sections. For each section, parse all subsections.
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for section in section_start_regex.split(text):
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parsed_sections = collections.defaultdict(str)
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for sub_section in re.split(r'(?m)^%s' % SUBSECTION_DELIMITER, section[1:]):
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# Skip empty subsections
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if not sub_section.strip():
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continue
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lines = sub_section.split('\n')
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subsection_name = lines[0].strip()
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subsection_comment = None
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subsection_info = [s.strip() for s in subsection_name.split(':')]
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if len(subsection_info) == 2:
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subsection_name, subsection_comment = subsection_info
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if subsection_comment == "":
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# ignore empty subsection_comment
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subsection_comment = None
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lines_content = lines[1:-1]
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subsection_str = '\n'.join([line for line in lines_content])
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if len(lines_content) != 0:
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# Add trailing newline to last line if present. This disambiguates between the
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# case of no lines versus a single line with no text.
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# This extra newline is needed only for the verification of the subsections of
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# RESULTS, DML_RESULTS and ERRORS and will be removed in write_test_file()
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# when '--update_results' is added to output the updated golden file.
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subsection_str += "\n"
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if subsection_name not in valid_section_names:
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if skip_unknown_sections or not subsection_name:
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print(sub_section)
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print('Unknown section \'%s\'' % subsection_name)
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continue
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else:
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raise RuntimeError('Unknown subsection: %s' % subsection_name)
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if subsection_name == 'QUERY' and subsection_comment:
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parsed_sections['QUERY_NAME'] = subsection_comment
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if subsection_name == 'RESULTS' and subsection_comment:
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for comment in subsection_comment.split(','):
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if comment == 'MULTI_LINE':
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parsed_sections['MULTI_LINE'] = comment
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elif comment == 'RAW_STRING':
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parsed_sections['RAW_STRING'] = comment
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elif comment.startswith('VERIFY'):
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parsed_sections['VERIFIER'] = comment
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else:
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raise RuntimeError('Unknown subsection comment: %s' % comment)
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if subsection_name == 'CATCH':
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parsed_sections['CATCH'] = list()
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if subsection_comment is None:
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parsed_sections['CATCH'].append(subsection_str)
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elif subsection_comment == 'ANY_OF':
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parsed_sections['CATCH'].extend(lines_content)
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else:
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raise RuntimeError('Unknown subsection comment: %s' % subsection_comment)
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for exception_str in parsed_sections['CATCH']:
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assert exception_str.strip(), "Empty exception string."
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continue
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# The DML_RESULTS section is used to specify what the state of the table should be
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# after executing a DML query (in the QUERY section). The target table name must
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# be specified in a table comment, and then the expected rows in the table are the
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# contents of the section. If the TYPES and LABELS sections are provided, they
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# will be verified against the DML_RESULTS. Using both DML_RESULTS and RESULTS is
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# not supported.
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if subsection_name == 'DML_RESULTS':
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if subsection_comment is None:
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raise RuntimeError('DML_RESULTS requires that the table is specified '
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'in the comment.')
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parsed_sections['DML_RESULTS_TABLE'] = subsection_comment
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parsed_sections['VERIFIER'] = 'VERIFY_IS_EQUAL_SORTED'
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# The RUNTIME_PROFILE section is used to specify lines of text that should be
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# present in the query runtime profile. It takes an option comment containing a
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# table format. RUNTIME_PROFILE sections with a comment are only evaluated for the
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# specified format. If there is a RUNTIME_PROFILE section without a comment, it is
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# evaluated for all formats that don't have a commented section for this query.
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if subsection_name == 'RUNTIME_PROFILE':
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if subsection_comment:
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table_formats = parse_runtime_profile_table_formats(subsection_comment)
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for table_format in table_formats:
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subsection_name_for_format = 'RUNTIME_PROFILE_%s' % table_format
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parsed_sections[subsection_name_for_format] = subsection_str
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continue
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parsed_sections[subsection_name] = subsection_str
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if parsed_sections:
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sections.append(parsed_sections)
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return sections
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def split_section_lines(section_str):
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"""
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Given a section string as produced by parse_test_file_text(), split it into separate
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lines. The section string must have a trailing newline.
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"""
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if section_str == '':
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return []
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assert section_str[-1] == '\n'
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# Trim off the trailing newline and split into lines.
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return section_str[:-1].split('\n')
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def join_section_lines(lines):
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"""
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The inverse of split_section_lines().
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The extra newline at the end will be removed in write_test_file() so that when the
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actual contents of a subsection do not match the expected contents, we won't see
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extra newlines in those subsections (ERRORS, TYPES, LABELS, RESULTS and DML_RESULTS).
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"""
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return '\n'.join(lines) + '\n'
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def write_test_file(test_file_name, test_file_sections, encoding=None):
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"""
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Given a list of test file sections, write out the corresponding test file
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This is useful when updating the results of a test.
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The file encoding can be specified in the 'encoding' parameter. If not specified
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the default system encoding will be used.
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"""
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with codecs.open(test_file_name, 'w', encoding=encoding) as test_file:
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test_file_text = list()
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for test_case in test_file_sections:
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test_file_text.append(SECTION_DELIMITER)
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for section_name, section_value in test_case.items():
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# Have to special case query name and verifier because they have annotations
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# in the headers
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if section_name in ['QUERY_NAME', 'VERIFIER']:
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continue
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# TODO: We need a more generic way of persisting the old test file.
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# Special casing will blow up.
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full_section_name = section_name
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if section_name == 'QUERY' and test_case.get('QUERY_NAME'):
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full_section_name = '%s: %s' % (section_name, test_case['QUERY_NAME'])
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if section_name == 'RESULTS' and test_case.get('VERIFIER'):
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full_section_name = '%s: %s' % (section_name, test_case['VERIFIER'])
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test_file_text.append("%s %s" % (SUBSECTION_DELIMITER, full_section_name))
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# We remove the extra newlines added in parse_test_file_text() so that in the
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# updated golden file we will not see an extra newline at the end of each
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# subsection.
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section_value = ''.join(test_case[section_name]).strip()
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if section_value:
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test_file_text.append(section_value)
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test_file_text.append(SECTION_DELIMITER)
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test_file.write(('\n').join(test_file_text))
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test_file.write('\n') # end file with a newline
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def load_tpc_queries(workload, include_stress_queries=False, query_name_filters=[]):
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"""
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Returns a list of queries for the given workload. 'workload' should either be 'tpch',
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'tpcds', 'tpch_nested', or 'targeted-perf'. The types of queries that are returned:
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- 'standard' queries, i.e. from the spec for that workload. These queries will have
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filenames like '{workload}-q*.test' and one query per file.
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- 'stress' queries, if 'include_stress_queries' is true, which run against data from
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the workkload but were designed to stress specific aspects of Impala. These queries
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have filenames like '{workload}-stress-*.test' and may have multiple queries per file.
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- 'targeted' queries, if the workload is 'targeted-perf', which have no restrictions.
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The returned queries are filtered according to 'query_name_filters', a list of query
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name regexes, if specified.
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All queries are required to have a name specified, i.e. each test case should have:
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---- QUERY: WORKLOAD-<QUERY_NAME>
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"""
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LOG.info("Loading %s queries", workload)
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queries = dict()
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query_dir = os.path.join(
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os.environ['IMPALA_HOME'], "testdata", "workloads", workload, "queries")
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# Check whether the workload name corresponds to an existing directory.
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if not os.path.isdir(query_dir):
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raise ValueError("Workload %s not found in %s" % (workload, query_dir))
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# IMPALA-6715 and others from the past: This pattern enforces the queries we actually
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# find. Both workload directories contain other queries that are not part of the TPC
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# spec.
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file_workload = workload
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if workload in ["tpcds", "tpcds_partitioned"]:
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# TPCDS is assumed to always use decimal_v2, which is the default since 3.0
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file_workload = "tpcds-decimal_v2"
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if include_stress_queries:
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file_name_pattern = re.compile(r"^{0}-(q.*|stress-.*).test$".format(file_workload))
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else:
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file_name_pattern = re.compile(r"^{0}-(q.*).test$".format(file_workload))
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query_name_prefix = workload.upper()
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if workload == "tpcds_partitioned":
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# 'tpcds_partitioned' symlink to the same queries set of 'tpcds'.
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query_name_prefix = "TPCDS"
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query_name_pattern = re.compile(r"^{0}-(.*)$".format(query_name_prefix))
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if workload == "tpch_nested":
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query_name_pattern = re.compile(r"^TPCH-(.*)$")
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if workload == "targeted-perf":
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# We don't enforce any restrictions on targeted-perf queries.
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file_name_pattern = re.compile(r"(.*)")
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query_name_pattern = re.compile(r"(.*)")
|
|
|
|
if query_name_filters:
|
|
query_name_filters = list(map(str.strip, query_name_filters))
|
|
else:
|
|
query_name_filters = []
|
|
filter_regex = re.compile(r'|'.join(['^%s$' % n for n in query_name_filters]), re.I)
|
|
|
|
for query_file in os.listdir(query_dir):
|
|
is_standard = "stress" not in query_file and workload != "targeted-perf"
|
|
file_match = file_name_pattern.search(query_file)
|
|
if not file_match:
|
|
continue
|
|
file_path = os.path.join(query_dir, query_file)
|
|
test_cases = parse_query_test_file(file_path)
|
|
for test_case in test_cases:
|
|
query_sql = remove_comments(test_case["QUERY"])
|
|
|
|
if re.match(filter_regex, test_case["QUERY_NAME"]):
|
|
query_name_match = query_name_pattern.search(test_case["QUERY_NAME"])
|
|
# For standard queries, we require that the query name matches the file name.
|
|
if is_standard and file_match.group(1).upper() != query_name_match.group(1):
|
|
raise Exception("Query name '%s' does not match file name '%s'"
|
|
% (query_name_match.group(1), file_match.group(1).upper()))
|
|
queries[query_name_match.group(0)] = query_sql
|
|
|
|
# The standard tpc queries must have one query per file.
|
|
if is_standard and len(test_cases) != 1:
|
|
raise Exception("Expected exactly 1 query to be in file %s but got %s"
|
|
% (file_path, len(test_cases)))
|
|
return queries
|
|
|
|
|
|
def tpc_sort_key(s):
|
|
"""
|
|
Sorting key for sorting strings in the format "tpch-qxX-yY".
|
|
The valid format is expected to be split into parts by '-'.
|
|
If the format doesn't match, 0 or an empty string will be returned
|
|
as appropriate.
|
|
Args:
|
|
s (str): Input string to be sorted.
|
|
Returns:
|
|
tuple: A tuple of (int, int, str, str):
|
|
- The first integer is the value of "x", if present, otherwise 0.
|
|
- The second integer is the value of "y",
|
|
included only if "x" is present, otherwise returns an 0.
|
|
- The third element is the character "X", not numeric,
|
|
included only if "x" is present, otherwise returns an empty string ('').
|
|
- The fourth element is the character "Y", not numeric,
|
|
included only if "y" is present, otherwise returns an empty string ('').
|
|
"""
|
|
x, y = 0, 0
|
|
x_char, y_char = '', ''
|
|
parts = s.split("-")
|
|
if len(parts) < 2:
|
|
return x, y, x_char, y_char
|
|
match = re.search(r"^q(\d+)(\D)?", parts[1])
|
|
if match:
|
|
x = int(match.group(1)) if match.group(1) else 0
|
|
x_char = match.group(2) if match.group(2) else ''
|
|
if len(parts) == 3 and match:
|
|
match = re.search(r"^(\d+)(\D)?", parts[2])
|
|
if match:
|
|
y = int(match.group(1)) if match.group(1) else 0
|
|
y_char = match.group(2) if match.group(2) else ''
|
|
return x, y, x_char, y_char
|
|
|
|
|
|
def load_tpc_queries_name_sorted(workload):
|
|
"""
|
|
Returns a list of queries for the given workload. Only tpch and tpcds are supported,
|
|
and only the name of the queries will be returned. The names are be sorted and
|
|
converted to lowercase before being returned.
|
|
Args:
|
|
workload (str): tpch or tpcds.
|
|
"""
|
|
queries = list(load_tpc_queries(workload).keys())
|
|
queries = [s.lower() for s in queries]
|
|
queries = sorted(queries, key=tpc_sort_key)
|
|
if workload == 'tpcds':
|
|
# TPCDS is assumed to always use decimal_v2, in alignment with load_tpc_queries()
|
|
substring = "tpcds-decimal_v2"
|
|
queries = [x.replace(workload, substring) for x in queries]
|
|
return queries
|