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https://issues.apache.org/jira/browse/ARROW-7224?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17297661#comment-17297661
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Andy Douglas commented on ARROW-7224:
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[~bkietz]
> directories viewed by datasets are only listed once (on construction)
right but for a dataset containing a large number of parquet files (> 100k) the
construction can take a long time so too can querying the dataset for a
particularly partition. What I was suggesting is the ability to load a cached
copy of the dataset *files* as a dataset i.e. the mapping from partition to
parquet file. Clearly this cache would be invalidated when the dataset is
written to but I have lots of datasets that are read more than they are
written, so for me the caching works well. Both the initial load and subsequent
querying are much faster (seconds not minutes for the initial load and then
tens of seconds for the query)
> [C++][Dataset] Partition level filters should be able to provide filtering to
> file systems
> ------------------------------------------------------------------------------------------
>
> Key: ARROW-7224
> URL: https://issues.apache.org/jira/browse/ARROW-7224
> Project: Apache Arrow
> Issue Type: Improvement
> Components: C++
> Reporter: Micah Kornfield
> Priority: Major
> Labels: dataset
>
> When providing a filter for partitions, it should be possible in some cases
> to use it to optimize file system list calls. This can greatly improve the
> speed for reading data from partitions because fewer number of
> directories/files need to be explored/expanded. I've fallen behind on the
> dataset code, but I want to make sure this issue is tracked someplace. This
> came up in SO question linked below (feel free to correct my analysis if I
> missed the functionality someplace).
> Reference:
> [https://stackoverflow.com/questions/58868584/pyarrow-parquetdataset-read-is-slow-on-a-hive-partitioned-s3-dataset-despite-u/58951477#58951477]
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