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106 lines
3.8 KiB
Python
106 lines
3.8 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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"""Compatibility layer for different database engines
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This modules stores logic specific to different database engines. Things
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like time-related functions that are similar but not identical, or
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information as to expose certain features or not and how to expose them.
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For instance, Hive/Presto supports partitions and have a specific API to
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list partitions. Other databases like Vertica also support partitions but
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have different API to get to them. Other databases don't support partitions
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at all. The classes here will use a common interface to specify all this.
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The general idea is to use static classes and an inheritance scheme.
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"""
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import inspect
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import logging
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import pkgutil
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from importlib import import_module
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from pathlib import Path
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from typing import Any, Dict, List, Set, Type
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import sqlalchemy.databases
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from pkg_resources import iter_entry_points
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from superset.db_engine_specs.base import BaseEngineSpec
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logger = logging.getLogger(__name__)
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def is_engine_spec(attr: Any) -> bool:
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return (
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inspect.isclass(attr)
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and issubclass(attr, BaseEngineSpec)
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and attr != BaseEngineSpec
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)
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def get_engine_specs() -> Dict[str, Type[BaseEngineSpec]]:
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engine_specs: List[Type[BaseEngineSpec]] = []
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# load standard engines
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db_engine_spec_dir = str(Path(__file__).parent)
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for module_info in pkgutil.iter_modules([db_engine_spec_dir], prefix="."):
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module = import_module(module_info.name, package=__name__)
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engine_specs.extend(
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getattr(module, attr)
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for attr in module.__dict__
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if is_engine_spec(getattr(module, attr))
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)
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# load additional engines from external modules
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for ep in iter_entry_points("superset.db_engine_specs"):
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try:
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engine_spec = ep.load()
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except Exception: # pylint: disable=broad-except
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logger.warning("Unable to load Superset DB engine spec: %s", engine_spec)
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continue
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engine_specs.append(engine_spec)
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# build map from name/alias -> spec
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engine_specs_map: Dict[str, Type[BaseEngineSpec]] = {}
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for engine_spec in engine_specs:
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names = [engine_spec.engine]
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if engine_spec.engine_aliases:
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names.extend(engine_spec.engine_aliases)
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for name in names:
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engine_specs_map[name] = engine_spec
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return engine_specs_map
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def get_available_engine_specs() -> List[Type[BaseEngineSpec]]:
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# native SQLAlchemy dialects
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backends: Set[str] = {
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getattr(sqlalchemy.databases, attr).dialect.name
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for attr in sqlalchemy.databases.__all__
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}
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# installed 3rd-party dialects
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for ep in iter_entry_points("sqlalchemy.dialects"):
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try:
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dialect = ep.load()
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except Exception: # pylint: disable=broad-except
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logger.warning("Unable to load SQLAlchemy dialect: %s", dialect)
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else:
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backends.add(dialect.name)
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engine_specs = get_engine_specs()
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return [engine_specs[backend] for backend in backends if backend in engine_specs]
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