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https://issues.apache.org/jira/browse/HIVE-26307?focusedWorklogId=780857&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-780857
 ]

ASF GitHub Bot logged work on HIVE-26307:
-----------------------------------------

                Author: ASF GitHub Bot
            Created on: 13/Jun/22 15:07
            Start Date: 13/Jun/22 15:07
    Worklog Time Spent: 10m 
      Work Description: pvary commented on code in PR #3354:
URL: https://github.com/apache/hive/pull/3354#discussion_r895836024


##########
iceberg/iceberg-handler/src/main/java/org/apache/iceberg/mr/mapreduce/IcebergInputFormat.java:
##########
@@ -381,100 +400,67 @@ private CloseableIterable<T> newAvroIterable(
       Avro.ReadBuilder avroReadBuilder = Avro.read(inputFile)
           .project(readSchema)
           .split(task.start(), task.length());
+

Review Comment:
   The first check in `openVectorized` is this:
   ```
         
Preconditions.checkArgument(!task.file().format().equals(FileFormat.AVRO),
             "Vectorized execution is not yet supported for Iceberg avro 
tables. " +
                 "Please turn off vectorization and retry the query.");
   ```





Issue Time Tracking
-------------------

    Worklog Id:     (was: 780857)
    Time Spent: 0.5h  (was: 20m)

> Avoid FS init in FileIO::newInputFile in vectorized Iceberg reads
> -----------------------------------------------------------------
>
>                 Key: HIVE-26307
>                 URL: https://issues.apache.org/jira/browse/HIVE-26307
>             Project: Hive
>          Issue Type: Improvement
>            Reporter: Peter Vary
>            Assignee: Peter Vary
>            Priority: Major
>              Labels: pull-request-available
>          Time Spent: 0.5h
>  Remaining Estimate: 0h
>
> With vectorized Iceberg reads we are creating {{HadoopInputFile}} objects 
> just to store the location of the files. If we can avoid this, then we can 
> improve the performance, since the {{path.getFileSystem(conf)}} calls can 
> become costly, especially for S3



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