DynamicTableSink. The new interface
consumes internal data structures. See FLIP-95 for more information.StreamExecutionEnvironment.DataStream and returns the sink transformation DataStreamSink.DataStreamSink.DataStream API.DataStream API.StreamTableEnvironment.create(StreamExecutionEnvironment) and TableEnvironment.getConfig() for
manipulating TableConfig.SinkFunction instance.SourceFunction instance.StatementSet that integrates with the Java-specific DataStream API.Context contains more information, and already contains table schema too.
Please use TableSinkFactory.createTableSink(Context) instead.Context contains more information, and already contains table schema too.
Please use TableSourceFactory.createTableSource(Context) instead.DataStream in a given path.DataStream in a given path.StreamTableEnvironment.createTemporaryView(String, DataStream, Schema) instead. In most
cases, StreamTableEnvironment.createTemporaryView(String, DataStream) should already be sufficient. It
integrates with the new type system and supports all kinds of DataTypes that the
table runtime can consume. The semantics might be slightly different for raw and
structured types.FileSink. It is kept only to
support tests for the legacy connector stack.FileSource. It is kept only to
support tests for the legacy connector stack.FileSink. It is kept only to
support tests for the legacy connector stack.FileSource. It is kept only to
support tests for the legacy connector stack.FileSink. It is kept only to
support tests for the legacy connector stack.TableSink to emit data as CSV files.TableSink to emit data as CSV files.TableSink to emit data as CSV files using comma as field delimiter, with
default parallelism and write mode.TableSink to emit data as CSV files, with default parallelism and write
mode.FileSink. It is kept only to
support tests for the legacy connector stack.FileSource. It is kept only to
support tests for the legacy connector stack.InputFormatTableSource and LookupableTableSource for simple CSV files with
a (logically) unlimited number of fields.InputFormatTableSource and LookupableTableSource for simple CSV files with
a (logically) unlimited number of fields.InputFormatTableSource and LookupableTableSource for simple CSV files with
a (logically) unlimited number of fields.FileSource. It is kept only to
support tests for the legacy connector stack.DataGenConnectorOptions.with its configuration options.DataGenerator.StreamTableSource that emits each number from a given interval exactly once, possibly
in parallel.DataGenTableSource in a stream environment.LogicalTypes to DataGeneratorContainer's.DataStream as a runtime implementation for ScanTableSource.DataStream as a runtime implementation for DynamicTableSink.DecimalData values.StreamExecutionEnvironment.execute(String) instead or directly call
the execute methods of the Table API such as TableEnvironment.executeSql(String).CsvTableSource.Builder.field(String, DataType) instead which uses
the new type system based on DataTypes. Please make sure to use either the
old or the new type system consistently to avoid unintended behavior. See the website
documentation for more information.ConfigOption.ConfigOption.ConfigOption.ConfigOption.ConfigOption.ConfigOption.DataStream of changelog entries into a Table.DataStream of changelog entries into a Table.DataStream of changelog entries into a Table.DataStream into a Table.DataStream into a Table.StreamTableEnvironment.fromDataStream(DataStream, Schema) instead. In most cases, StreamTableEnvironment.fromDataStream(DataStream) should already be sufficient. It integrates with the new
type system and supports all kinds of DataTypes that the table runtime can
consume. The semantics might be slightly different for raw and structured types.DataStream.InputFormat for reading the data of the table.OutputFormat for writing the data of the table.DataStreamSinkProvider.consumeDataStream(DataStream)
applies multiple transformations, make sure to set the same custom parallelism to each
operator to not mess up the changelog.TableFormatFactory.supportedProperties() method that are accepted
for schema derivation using deriveFormatFields(DescriptorProperties).DynamicTableSource. The new interface
produces internal data structures. See FLIP-95 for more information.DataStream.DataStream.Csv format in the dedicated flink-formats/flink-csv
module instead.DynamicTableSink. The new interface
consumes internal data structures. See FLIP-95 for more information.DataStream from a StreamExecutionEnvironment.DataGeneratorContainer for a particular logical type.TableEnvironment.createTemporarySystemFunction(String, UserDefinedFunction) instead.
Please note that the new method also uses the new type system and reflective extraction
logic. It might be necessary to update the function implementation as well. See the
documentation of TableFunction for more information on the new function design.TableEnvironment.createTemporarySystemFunction(String, UserDefinedFunction) instead.
Please note that the new method also uses the new type system and reflective extraction
logic. It might be necessary to update the function implementation as well. See the
documentation of AggregateFunction for more information on the new function
design.TableEnvironment.createTemporarySystemFunction(String, UserDefinedFunction) instead.
Please note that the new method also uses the new type system and reflective extraction
logic. It might be necessary to update the function implementation as well. See the
documentation of TableAggregateFunction for more information on the new function
design.DynamicTableSink. The new interface
consumes internal data structures. See FLIP-95 for more information.RowData type.Rowtime for details.Schema for details.DataGeneratorContainer for a particular logical type.Table to write is append-only or not.Table to write.SinkFunction instance as a runtime implementation for DynamicTableSink.SourceFunction instance as a runtime implementation for ScanTableSource.StatementSet that integrates with the Java-specific DataStream API.StreamStatementSet.DataStream API.StreamTableEnvironment.DynamicTableSink. The new interface
consumes internal data structures. See FLIP-95 for more information.DynamicTableSinkFactory. The new
interface creates instances of DynamicTableSink. See FLIP-95 for more information.DynamicTableSource. The new interface
produces internal data structures. See FLIP-95 for more information.DynamicTableSourceFactory. The new
interface creates instances of DynamicTableSource. See FLIP-95 for more information.StreamTableEnvironment.toDataStream(Table, Class) instead. It integrates with the new type
system and supports all kinds of DataTypes that the table runtime can produce.
The semantics might be slightly different for raw and structured types. Use toDataStream(DataTypes.of(TypeInformation.of(Class))) if TypeInformation should
be used as source of truth.StreamTableEnvironment.toDataStream(Table, Class) instead. It integrates with the new type
system and supports all kinds of DataTypes that the table runtime can produce.
The semantics might be slightly different for raw and structured types. Use toDataStream(DataTypes.of(TypeInformation.of(Class))) if TypeInformation should
be used as source of truth.Table into a DataStream of changelog entries.Table into a DataStream of changelog entries.Table into a DataStream of changelog entries.Table into a DataStream.Table into a DataStream of the given DataType.StreamTableEnvironment.toChangelogStream(Table, Schema) instead. It integrates with the new
type system and supports all kinds of DataTypes and every ChangelogMode
that the table runtime can produce.StreamTableEnvironment.toChangelogStream(Table, Schema) instead. It integrates with the new
type system and supports all kinds of DataTypes and every ChangelogMode
that the table runtime can produce.DynamicTableSink. The new interface
consumes internal data structures. See FLIP-95 for more information.Copyright © 2014–2022 The Apache Software Foundation. All rights reserved.