FLINK基础（136）：DS流与表转换(2) Handling of (Insert-Only) Streams（1）简介(FLINK1.13以上)

A StreamTableEnvironment offers the following methods to convert from and to DataStream API:

• fromDataStream(DataStream): Interprets a stream of insert-only changes and arbitrary type as a table. Event-time and watermarks are not propagated by default.

• fromDataStream(DataStream, Schema): Interprets a stream of insert-only changes and arbitrary type as a table. The optional schema allows to enrich column data types and add time attributes, watermarks strategies, other computed columns, or primary keys.

• createTemporaryView(String, DataStream): Registers the stream under a name to access it in SQL. It is a shortcut for createTemporaryView(String, fromDataStream(DataStream)).

• createTemporaryView(String, DataStream, Schema): Registers the stream under a name to access it in SQL. It is a shortcut for createTemporaryView(String, fromDataStream(DataStream, Schema)).

• toDataStream(DataStream): Converts a table into a stream of insert-only changes. The default stream record type is org.apache.flink.types.Row. A single rowtime attribute column is written back into the DataStream API’s record. Watermarks are propagated as well.

• toDataStream(DataStream, AbstractDataType): Converts a table into a stream of insert-only changes. This method accepts a data type to express the desired stream record type. The planner might insert implicit casts and reorders columns to map columns to fields of the (possibly nested) data type.

• toDataStream(DataStream, Class): A shortcut for toDataStream(DataStream, DataTypes.of(Class)) to quickly create the desired data type reflectively.

From a Table API’s perspective, converting from and to DataStream API is similar to reading from or writing to a virtual table connector that has been defined using a CREATE TABLE DDL in SQL.

The schema part in the virtual CREATE TABLE name (schema) WITH (options) statement can be automatically derived from the DataStream’s type information, enriched, or entirely defined manually using org.apache.flink.table.api.Schema.

The virtual DataStream table connector exposes the following metadata for every row:

Key	Data Type	Description	R/W
rowtime	TIMESTAMP_LTZ(3) NOT NULL	Stream record's timestamp.	R/W

The virtual DataStream table source implements SupportsSourceWatermark and thus allows calling the SOURCE_WATERMARK() built-in function as a watermark strategy to adopt watermarks from the DataStream API.