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https://issues.apache.org/jira/browse/BEAM-7925?focusedWorklogId=480637&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-480637
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ASF GitHub Bot logged work on BEAM-7925:
----------------------------------------
Author: ASF GitHub Bot
Created on: 09/Sep/20 07:04
Start Date: 09/Sep/20 07:04
Worklog Time Spent: 10m
Work Description: ihji commented on a change in pull request #12786:
URL: https://github.com/apache/beam/pull/12786#discussion_r485383858
##########
File path:
sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java
##########
@@ -135,6 +135,16 @@
* ...
* }</pre>
*
+ * <p>Reading with projection can be enabled with the projection schema as
following. The
+ * projection_schema contains only the column that we would like to read and
encoder_schema contains
+ * all field but with the unwanted columns changed to nullable.
+ *
Review comment:
The description is still a bit vague. Can you please elaborate more on
how much improvement users could expect from the column projection? For
example, if the transform with the column projection only reads a half of the
columns, does it also use only half of the memory and finish two times faster
than the transform without the column projection? (If not, why is that?)
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Issue Time Tracking
-------------------
Worklog Id: (was: 480637)
Time Spent: 2h 10m (was: 2h)
> ParquetIO supports neither column projection nor filter predicate
> -----------------------------------------------------------------
>
> Key: BEAM-7925
> URL: https://issues.apache.org/jira/browse/BEAM-7925
> Project: Beam
> Issue Type: Improvement
> Components: io-java-parquet
> Affects Versions: 2.14.0
> Reporter: Neville Li
> Priority: P2
> Time Spent: 2h 10m
> Remaining Estimate: 0h
>
> Current {{ParquetIO}} supports neither column projection nor filter predicate
> which defeats the performance motivation of using Parquet in the first place.
> That's why we have our own implementation of
> [ParquetIO|https://github.com/spotify/scio/tree/master/scio-parquet/src] in
> Scio.
> Reading Parquet as Avro with column projection has some complications,
> namely, the resulting Avro records may be incomplete and will not survive
> ser/de. A workaround maybe provide a {{TypedRead}} interface that takes a
> {{Function<A, B>}} that maps invalid Avro {{A}} into user defined type {{B}}.
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