[jira] [Issue Comment Deleted] (FLINK-10618) Introduce catalog for Flink tables

["Xuefu Zhang (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/FLINK-10618?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Xuefu Zhang updated FLINK-10618:
--------------------------------
    Comment: was deleted

(was: This task is superseded by FLINK-11482. )

> Introduce catalog for Flink tables
> ----------------------------------
>
>                 Key: FLINK-10618
>                 URL: https://issues.apache.org/jira/browse/FLINK-10618
>             Project: Flink
>          Issue Type: Sub-task
>          Components: SQL Client
>    Affects Versions: 1.6.1
>            Reporter: Xuefu Zhang
>            Assignee: Xuefu Zhang
>            Priority: Major
>             Fix For: 1.8.0
>
>
> This JIRA covers the 2nd aspect of Flink-Hive metastore integration.
> Besides meta objects such as tables that may come from an {{ExternalCatalog}}, Flink also deals with tables/views/functions that are created on the fly (in memory), or specified in a configuration file. Those objects don't belong to any {{ExternalCatalog}}, yet Flink either stores them in memory, which are non-persistent, or recreates them from a file, which is a big pain for the user. Those objects are only known to Flink but Flink has a poor management for them.
> Since they are typical objects in a database catalog, it's natural to have a catalog that manages those objects. The interface will be similar to {{ExternalCatalog}}, which contains meta objects that are not managed by Flink. There are several possible implementations of the Flink internal catalog interface: memory, file, external registry (such as confluent schema registry or Hive metastore), and relational database, etc. 
> The initial functionality as well as the catalog hierarchy could be very simple. The basic functionality of the catalog will be mostly create, alter, and drop tables, views, functions, etc. Obviously, this can evolve over the time.
> We plan to provide implementations: in-memory and in Hive metastore.



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