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https://issues.apache.org/jira/browse/BEAM-3157?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16274669#comment-16274669
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Anton Kedin commented on BEAM-3157:
-----------------------------------
This will align with schema-aware pcollections:
https://docs.google.com/document/d/1tnG2DPHZYbsomvihIpXruUmQ12pHGK0QIvXS1FOTgRc
I also need something like this for Nexmark, so I am working on a code
generation solution to infer the schema from pojo, so that you can do things
like:
{code:java}
BeamRecordSqlTypeProxy recordType =
BeamRecordSqlTypeProxy.forClass(PojoClass.class);
BeamRecord record = recordType.newRecordCopyOf(pojoInstance);
{code}
Current draft commit:
https://github.com/akedin/beam/commit/6483880250ea2b04d28594475ab728bcd0aa8d3e
I expect to have a PR out today or tomorrow for this piece.
> 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
>
> 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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