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https://issues.apache.org/jira/browse/BEAM-7925?focusedWorklogId=480926&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-480926
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ASF GitHub Bot logged work on BEAM-7925:
----------------------------------------
Author: ASF GitHub Bot
Created on: 09/Sep/20 17:03
Start Date: 09/Sep/20 17:03
Worklog Time Spent: 10m
Work Description: danielxjd commented on a change in pull request #12786:
URL: https://github.com/apache/beam/pull/12786#discussion_r485779725
##########
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 improvement is not as significant, since the processing time saved
is only the time to read the unwanted columns, the reader will still go over
the entire data set since data for each column in a row is stored interleaved.
So the test showed that there is only a slight reduction in the reading time.
For the memory, it is hard for me to track with the Dataflow server.
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Issue Time Tracking
-------------------
Worklog Id: (was: 480926)
Time Spent: 2h 20m (was: 2h 10m)
> 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 20m
> 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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