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From "Anton Kedin (JIRA)" <j...@apache.org>
Subject [jira] [Closed] (BEAM-3157) BeamSql transform should support other PCollection types
Date Fri, 13 Apr 2018 16:49:00 GMT

     [ https://issues.apache.org/jira/browse/BEAM-3157?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Anton Kedin closed BEAM-3157.
-----------------------------
       Resolution: Fixed
    Fix Version/s: Not applicable

> BeamSql transform should support other PCollection types
> --------------------------------------------------------
>
>                 Key: BEAM-3157
>                 URL: https://issues.apache.org/jira/browse/BEAM-3157
>             Project: Beam
>          Issue Type: Improvement
>          Components: dsl-sql
>            Reporter: Ismaël Mejía
>            Assignee: Anton Kedin
>            Priority: Major
>             Fix For: Not applicable
>
>          Time Spent: 5h 20m
>  Remaining Estimate: 0h
>
> Currently the Beam SQL transform only supports input and output data represented as a
BeamRecord. This seems to me like an usability limitation (even if we can do a ParDo to prepare
objects before and after the transform).
> I suppose this constraint comes from the fact that we need to map name/type/value from
an object field into Calcite so it is convenient to have a specific data type (BeamRecord)
for this. However we can accomplish the same by using a PCollection of JavaBean (where we
know the same information via the field names/types/values) or by using Avro records where
we also have the Schema information. For the output PCollection we can map the object via
a Reference (e.g. a JavaBean to be filled with the names of an Avro object).
> Note: I am assuming for the moment simple mappings since the SQL does not support composite
types for the moment.
> A simple API idea would be something like this:
> A simple filter:
> PCollection<MyPojo> col = BeamSql.query("SELECT * FROM .... WHERE ...").from(MyPojo.class);
> A projection:
> PCollection<MyNewPojo> newCol = BeamSql.query("SELECT id, name").from(MyPojo.class).as(MyNewPojo.class);
> A first approach could be to just add the extra ParDos + transform DoFns however I suppose
that for memory use reasons maybe mapping directly into Calcite would make sense.



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