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https://issues.apache.org/jira/browse/BEAM-6772?focusedWorklogId=212760&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-212760
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ASF GitHub Bot logged work on BEAM-6772:
----------------------------------------
Author: ASF GitHub Bot
Created on: 13/Mar/19 23:17
Start Date: 13/Mar/19 23:17
Worklog Time Spent: 10m
Work Description: reuvenlax commented on issue #8006: [BEAM-6772] Change
Select semantics to match what a user expects
URL: https://github.com/apache/beam/pull/8006#issuecomment-472643320
Always adding one extra row around whatever is selected makes sense in
Spark and BQ, because it makes selection consistent between primitive and
nested types. Select must always return a row, so if you select userId, it
returns a Row with a single string field (not a scalar string field). Spark
and BQ have therefore decided to treat nested rows the exact same way: even
though the nested row could be returned directly, it is treated
consistently like primitive types and boxed inside a result row.
On Wed, Mar 13, 2019 at 4:09 PM Gleb Kanterov <[email protected]>
wrote:
> Makes sense. I tried and both BigQuery and Spark have consistent behavior
> for selecting rows nested in rows:
>
> df.printSchema()
> root
> |-- userId: string (nullable = true)
> |-- position: struct (nullable = true)
> | |-- location: struct (nullable = true)
> | | |-- longtitude: double (nullable = true)
> | | |-- latitude: double (nullable = true)
>
> df.select("position.location").printSchema()
> root
> |-- location: struct (nullable = true)
> | |-- longtitude: double (nullable = true)
> | |-- latitude: double (nullable = true)
>
>
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Issue Time Tracking
-------------------
Worklog Id: (was: 212760)
Time Spent: 4h 40m (was: 4.5h)
> Select transform has non-intuitive semantics
> --------------------------------------------
>
> Key: BEAM-6772
> URL: https://issues.apache.org/jira/browse/BEAM-6772
> Project: Beam
> Issue Type: Sub-task
> Components: sdk-java-core
> Reporter: Reuven Lax
> Assignee: Reuven Lax
> Priority: Major
> Time Spent: 4h 40m
> Remaining Estimate: 0h
>
> Consider the following schema:
> User:
> name: STRING
> location: Location
>
> Location:
> latitude: DOUBLE
> longitude: DOUBLE
>
> If you apply Select.fieldNames("location"), most users expect to get back a
> row matching the Location schema. Instead you get back an outer schema with a
> single location field in it. Select should instead unnest the output up to
> the point where multiple fields are selected.
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