blob: 44da330738c84c628b8ae945d22c75cab46d5525 [file] [log] [blame]
################################################################################
# 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.
################################################################################
"""
Entry point classes of Flink Table API:
- :class:`TableEnvironment` and :class:`StreamTableEnvironment`
Main entry point for Flink Table API & SQL functionality. :class:`TableEnvironment` is used
in pure Table API & SQL jobs. Meanwhile, :class:`StreamTableEnvironment` needs to be used when
mixing use of Table API and DataStream API.
- :class:`Table`
The core component of the Table API. Use the methods of :class:`Table` to transform data.
- :class:`StatementSet`
The core component of the Table API. It's used to create jobs with multiple sinks.
- :class:`EnvironmentSettings`
Defines all the parameters used to initialize a :class:`TableEnvironment`.
- :class:`TableConfig`
A config to define the runtime behavior of the Table API.
It is used together with :class:`pyflink.datastream.StreamExecutionEnvironment` to create
:class:`StreamTableEnvironment`.
Classes to define user-defined functions:
- :class:`ScalarFunction`
Base interface for user-defined scalar function.
- :class:`TableFunction`
Base interface for user-defined table function.
- :class:`AggregateFunction`
Base interface for user-defined aggregate function.
- :class:`TableAggregateFunction`
Base interface for user-defined table aggregate function.
- :class:`FunctionContext`
Used to obtain global runtime information about the context in which the
user-defined function is executed, such as the metric group, and global job parameters, etc.
Classes to define window:
- :class:`window.GroupWindow`
Group windows group rows based on time or row-count intervals. See :class:`window.Tumble`,
:class:`window.Session` and :class:`window.Slide` for more details on how to create a tumble
window, session window, hop window separately.
- :class:`window.OverWindow`
Over window aggregates compute an aggregate for each input row over a range
of its neighboring rows. See :class:`window.Over` for more details on how to create an over
window.
Classes for catalog:
- :class:`catalog.Catalog`
Responsible for reading and writing metadata such as database/table/views/UDFs
from and to a catalog.
- :class:`catalog.HiveCatalog`
Responsible for reading and writing metadata stored in Hive.
Classes to define source & sink:
- :class:`TableDescriptor`
TableDescriptor is a template for creating a CatalogTable instance. It closely resembles the
"CREATE TABLE" SQL DDL statement, containing schema, connector options, and other
characteristics. Since tables in Flink are typically backed by external systems, the
descriptor describes how a connector (and possibly its format) are configured.
- :class:`FormatDescriptor`
Describes a format and its options for use with :class:`TableDescriptor`.
- :class:`Schema`
Describes the schema for use with :class:`TableDescriptor`. It represents the schema part of a
`CREATE TABLE (schema) WITH (options)` DDL statement in SQL. It defines columns of
different kind, constraints, time attributes, and watermark strategies. It is possible to
reference objects (such as functions or types) across different catalogs.
Classes for module:
- :class:`Module`
Defines a set of metadata, including functions, user defined types, operators, rules,
etc. Metadata from modules are regarded as built-in or system metadata that users can take
advantages of.
- :class:`module.HiveModule`
Implementation of :class:`Module` to provide Hive built-in metadata.
Other important classes:
- :class:`DataTypes`
Defines a list of data types available in Table API.
- :class:`Expression`
Represents a logical tree for producing a computation result for a column in a :class:`Table`.
Might be literal values, function calls, or field references.
- :class:`TableSchema`
Represents a table's structure with field names and data types.
- :class:`SqlDialect`
Enumeration of valid SQL compatibility modes.
- :class:`ChangelogMode`
The set of changes contained in a changelog.
- :class:`ExplainDetail`
Defines the types of details for explain result.
"""
from __future__ import absolute_import
from pyflink.table.changelog_mode import ChangelogMode
from pyflink.table.data_view import DataView, ListView, MapView
from pyflink.table.environment_settings import EnvironmentSettings
from pyflink.table.explain_detail import ExplainDetail
from pyflink.table.expression import Expression
from pyflink.table.module import Module, ModuleEntry
from pyflink.table.result_kind import ResultKind
from pyflink.table.schema import Schema
from pyflink.table.sinks import CsvTableSink, TableSink, WriteMode
from pyflink.table.sources import CsvTableSource, TableSource
from pyflink.table.sql_dialect import SqlDialect
from pyflink.table.statement_set import StatementSet
from pyflink.table.table import GroupWindowedTable, GroupedTable, OverWindowedTable, Table, \
WindowGroupedTable
from pyflink.table.table_config import TableConfig
from pyflink.table.table_descriptor import TableDescriptor, FormatDescriptor
from pyflink.table.table_environment import (TableEnvironment, StreamTableEnvironment)
from pyflink.table.table_result import TableResult
from pyflink.table.table_schema import TableSchema
from pyflink.table.types import DataTypes, UserDefinedType, Row, RowKind
from pyflink.table.udf import FunctionContext, ScalarFunction, TableFunction, AggregateFunction, \
TableAggregateFunction
__all__ = [
'TableEnvironment',
'StreamTableEnvironment',
'Table',
'StatementSet',
'EnvironmentSettings',
'TableConfig',
'GroupedTable',
'GroupWindowedTable',
'OverWindowedTable',
'WindowGroupedTable',
'ScalarFunction',
'TableFunction',
'AggregateFunction',
'TableAggregateFunction',
'FunctionContext',
'DataView',
'ListView',
'MapView',
'TableDescriptor',
'FormatDescriptor',
'Schema',
'Module',
'ModuleEntry',
'SqlDialect',
'DataTypes',
'UserDefinedType',
'Expression',
'TableSchema',
'TableResult',
'Row',
'RowKind',
'ChangelogMode',
'ExplainDetail',
'TableSource',
'TableSink',
'CsvTableSource',
'CsvTableSink',
'WriteMode',
'ResultKind'
]