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https://issues.apache.org/jira/browse/BEAM-6133?focusedWorklogId=169825&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-169825
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ASF GitHub Bot logged work on BEAM-6133:
----------------------------------------

                Author: ASF GitHub Bot
            Created on: 27/Nov/18 15:26
            Start Date: 27/Nov/18 15:26
    Worklog Time Spent: 10m 
      Work Description: kanterov opened a new pull request #7141: [BEAM-6133] 
[SQL] Add support for TableMacro UDF
URL: https://github.com/apache/beam/pull/7141
 
 
   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.
   
   ```sql
   SELECT COUNT(*) FROM table(my_udf('dataset', start = '2017-01-01', end = 
'2018-01-01'))
   ```
   
   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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Issue Time Tracking
-------------------

            Worklog Id:     (was: 169825)
            Time Spent: 10m
    Remaining Estimate: 0h

> [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: 10m
>  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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