[jira] [Commented] (TAJO-710) Add support for nested schemas

["Jihoon Son (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/TAJO-710?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13946715#comment-13946715 ] 

Jihoon Son commented on TAJO-710:
---------------------------------

++1 for this issue!

> Add support for nested schemas
> ------------------------------
>
>                 Key: TAJO-710
>                 URL: https://issues.apache.org/jira/browse/TAJO-710
>             Project: Tajo
>          Issue Type: New Feature
>          Components: data type
>            Reporter: David Chen
>
> Add support for nested schemas. Here are some ways other systems handle nested schemas:
>  * Pig and Hive uses complex data types, such as bags, structs, arrays, etc.
>  * Impala doesn't support nested schemas and simply flattens the schema.
> From the discussion in TAJO-30:
> {quote}
> I have a plan for nested schema. Currently, Tajo only supports a flat schema like relational DBMS. So, even though Tajo is extended to nested data mode, it will not break the compatibility.
> I'm thinking that Tajo takes Parquet data model (= protobuf or BigQuery). When I consider nested data model, I thought two main points. Parquet data model satisfies with these points. The first point that I've thought is the processing model on nested data. Parquet data model is the same to that of BigQuery, and BigQuery already concreted the processing model including flattening, cross production on repeated fields, and aggregation on repeated fields [1][2]. The second point is file format. Parquet is a native file format for this model. Parquet already includes the efficient record assembly method. Besides, Parquet is already mature and is widely used in many systems.
> [1] http://research.google.com/pubs/pub36632.html
> [2] https://developers.google.com/bigquery/docs/data
> I'm thinking that we need three stages for this work. Firstly, we can start with a small change to improve our schema system. Then, we will add some physical operator to just flatten one nested row into a number of flattened rows. Finally, we will solve some query optimization issues like projection/filter push down on nested schema and will add some physical operators to directly process nested rows.
> If you have any idea, feel free to share with us.
> Thanks,
> Hyunsik
> {quote}



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