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Posted to issues@beam.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/11/27 15:27:00 UTC
[jira] [Work logged] (BEAM-6133) [SQL] Add support for TableMacro
UDF
[ https://issues.apache.org/jira/browse/BEAM-6133?focusedWorklogId=169825&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-169825 ]
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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