[jira] [Commented] (FLINK-7146) FLINK SQLs support DDL

["Fabian Hueske (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/FLINK-7146?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16081851#comment-16081851 ] 

Fabian Hueske commented on FLINK-7146:
--------------------------------------

[~yuemeng] Can you split this issue into two subissues:

1. DDL for tables.
2. DDL to register user-defined functions.

DDL for tables will require a very good design to make it applicable for a wide variety of use cases:
- batch and streaming
- flat and nested data
- different encodings: JSON, CSV, Avro, Parquet, ORC, ...
- timestamp & watermark assignment strategies
- time attributes
- custom parameter for the source / sink system, e.g., Kafka properties

We are also currently discussing how to refactor the {{TableSource}} and {{TableSink}} (and related) interfaces to support these use cases.

> FLINK SQLs support DDL
> ----------------------
>
>                 Key: FLINK-7146
>                 URL: https://issues.apache.org/jira/browse/FLINK-7146
>             Project: Flink
>          Issue Type: New Feature
>          Components: Table API & SQL
>            Reporter: yuemeng
>
> For now,Flink SQL can't support DDL, we can only register a table by call registerTableInternal in TableEnvironment
> we should support DDL for sql such as create a table or create function like:
> {code}
> CREATE TABLE kafka_source (
>   id INT,
>   price INT
> ) PROPERTIES (
>   category = 'source',
>   type = 'kafka',
>   version = '0.9.0.1',
>   separator = ',',
>   topic = 'test',
>   brokers = 'xxxxxx:9092',
>   group_id = 'test'
> );
> CREATE TABLE db_sink (
>   id INT,
>   price DOUBLE
> ) PROPERTIES (
>   category = 'sink',
>   type = 'mysql',
>   table_name = 'udaf_test',
>   url = 'jdbc:mysql://127.0.0.1:3308/ds?useUnicode=true&characterEncoding=UTF8',
>   username = 'ds_dev',
>   password = 's]k51_(>R'
> );
> CREATE TEMPORARY function 'AVGUDAF' AS 'com.xxxxx.server.codegen.aggregate.udaf.avg.IntegerAvgUDAF';
> INSERT INTO db_sink SELECT id ,AVGUDAF(price) FROM kafka_source group by id
> {code}



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