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https://issues.apache.org/jira/browse/PARQUET-1698?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17013536#comment-17013536
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David Li commented on PARQUET-1698:
-----------------------------------
[~apitrou] yes, I backported the current Arrow S3File from the datasets
project, if that's what you're talking about - it only achieved ~10 MiB/s for
us, IIRC, precisely because it issues a new network request for every read
operation.
An API like that would likely be what we propose - we're still doing
experiments in C++ before sending something more formal to the mailing list.
(Our current work is in Python, but anything open-source would go into the C++
core.) We'd also propose some sort of I/O concurrency manager, which IIRC there
have been discussions about in the past.
> [C++] Add reader option to pre-buffer entire serialized row group into memory
> -----------------------------------------------------------------------------
>
> Key: PARQUET-1698
> URL: https://issues.apache.org/jira/browse/PARQUET-1698
> Project: Parquet
> Issue Type: Improvement
> Components: parquet-cpp
> Reporter: Wes McKinney
> Assignee: Zherui Cao
> Priority: Major
> Labels: pull-request-available
> Fix For: cpp-1.6.0
>
> Time Spent: 10m
> Remaining Estimate: 0h
>
> In some scenarios (example: reading datasets from Amazon S3), reading columns
> independently and allowing unbridled {{Read}} calls to the underlying file
> handle can yield suboptimal performance. In such cases, it may be preferable
> to first read the entire serialized row group into memory then deserialize
> the constituent columns from this
> Note that such an option would not be appropriate as a default behavior for
> all file handle types since low-selectivity reads (example: reading only 3
> columns out of a file with 100 columns) will be suboptimal in some cases. I
> think it would be better for "high latency" file systems to opt into this
> option
> cc [~fsaintjacques] [~bkietz] [~apitrou]
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