[jira] [Commented] (ARROW-13034) [Python][Docs] Update outdated examples for hdfs/azure on the Parquet doc page

["Joris Van den Bossche (Jira)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/ARROW-13034?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17360837#comment-17360837 ] 

Joris Van den Bossche commented on ARROW-13034:
-----------------------------------------------

And additionally, for the part about reading from the cloud, we should more clearly refer to fsspec based systems as a workaround for now for filesystems that are not supported natively by Arrow.

> [Python][Docs] Update outdated examples for hdfs/azure on the Parquet doc page
> ------------------------------------------------------------------------------
>
>                 Key: ARROW-13034
>                 URL: https://issues.apache.org/jira/browse/ARROW-13034
>             Project: Apache Arrow
>          Issue Type: Improvement
>          Components: Python
>            Reporter: Joris Van den Bossche
>            Priority: Major
>
> From https://github.com/apache/arrow/issues/10492
> - The chapter "Writing to Partitioned Datasets" still presents a "solution" with "hdfs.connect" but since it's mentioned as deprecated no more a good idea to mention it.
> - The chapter "Reading a Parquet File from Azure Blob storage" is based on the package "azure.storage.blob" ... but an old one and the actual "azure-sdk-for-python" doesn't have any-more methods like get_blob_to_stream(). Possible to update this part with new blob storage possibilities, and also another mentioning the same concept with Delta Lake (similar principle but since there are differences ...)



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