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https://issues.apache.org/jira/browse/PARQUET-1370?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16568403#comment-16568403
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Uwe L. Korn commented on PARQUET-1370:
--------------------------------------
I'm doing the same, my code looks as follows:
{code:java}
reader = …some file handle…
reader = io.BufferedReader(reader, 512 * 1024)
parquet_file = ParquetFile(reader){code}
This was so simple that I thought it might not be relevant for now. Having a
general C++ implementation of {{io.BufferedReader}} in Arrow C++ might be a
simpler approach to our problem. The usage of `io.BufferedReader` involves
probably some additional memory copies and overhead as we have to switch
between Python and C++ often.
(In my case, the file handle is coming from [https://github.com/mbr/simplekv] /
[https://github.com/blue-yonder/storefact] )
> Read consecutive column chunks in a single scan
> -----------------------------------------------
>
> Key: PARQUET-1370
> URL: https://issues.apache.org/jira/browse/PARQUET-1370
> Project: Parquet
> Issue Type: Improvement
> Components: parquet-cpp
> Reporter: Robert Gruener
> Priority: Major
>
> Currently parquet-cpp calls for a filesystem scan with every single data page
> see
> [https://github.com/apache/parquet-cpp/blob/a0d1669cf67b055cd7b724dea04886a0ded53c8f/src/parquet/column_reader.cc#L181]
> For remote filesystems this can be very inefficient when reading many small
> columns. The java implementation already does this and will read consecutive
> column chunks (and the resulting pages) in a single scan see
> [https://github.com/apache/parquet-mr/blob/master/parquet-hadoop/src/main/java/org/apache/parquet/hadoop/ParquetFileReader.java#L786]
>
> This might be a bit difficult to do, as it would require changing a lot of
> the code structure but it would certainly be valuable for workloads concerned
> with optimal read performance.
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