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https://issues.apache.org/jira/browse/BEAM-6133?focusedWorklogId=170359&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-170359
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ASF GitHub Bot logged work on BEAM-6133:
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Author: ASF GitHub Bot
Created on: 28/Nov/18 18:39
Start Date: 28/Nov/18 18:39
Worklog Time Spent: 10m
Work Description: kanterov commented on issue #7141: [BEAM-6133] [SQL]
Add support for TableMacro UDF
URL: https://github.com/apache/beam/pull/7141#issuecomment-442557557
@amaliujia table macros get expanded to relations during query planning, so
it shouldn't query services a lot. It's possible to implement caching if
needed, but, in my opinion, it's something that should be done by users,
instead of being built-in.
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Issue Time Tracking
-------------------
Worklog Id: (was: 170359)
Time Spent: 1h 20m (was: 1h 10m)
> [SQL] Add support for TableMacro UDF
> ------------------------------------
>
> Key: BEAM-6133
> URL: https://issues.apache.org/jira/browse/BEAM-6133
> Project: Beam
> Issue Type: New Feature
> Components: dsl-sql
> Reporter: Gleb Kanterov
> Assignee: Gleb Kanterov
> Priority: Major
> Time Spent: 1h 20m
> Remaining Estimate: 0h
>
> Now we support only ScalarFunction UDFs. In Calcite, there are other kinds of
> UDFs. With TableMacro UDFs users can connect external data sources in a
> similar way as in TableProvider, but without specifying a schema, or
> enumerating a list of existing tables in advance.
> An example use case is connecting external metadata service and querying
> range of partitions.
> {code}
> SELECT COUNT(*) FROM table(my_udf('dataset', start = '2017-01-01', end =
> '2018-01-01'))
> {code}
> Where the implementation of `my_udf` will connect to this service, get file
> locations for a range of partitions, and translate to PTransform reading it.
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