[
https://issues.apache.org/jira/browse/ORC-508?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17004348#comment-17004348
]
Michael Luckey commented on ORC-508:
------------------------------------
[~omalley] Could you elaborate a bit on your suggestion? While investigating
into reading/writing orc files without relying on Hadoop fs/path as [required
for apache
beam|https://github.com/apache/beam/blob/master/sdks/java/io/parquet/src/main/java/org/apache/beam/sdk/io/parquet/ParquetIO.java#L222-L223]
I found this issue and unfortunately do not quite understand the suggested
solution.
IIRC beam had the same issue with ParquetIO which was solved be introducing
[some intermediate level of
abstraction|https://github.com/apache/parquet-mr/commit/8bfd9b4d8f4fb0a2b522c9328f67eb642066306b]
and after a short look it seems possible, that a similar approach could work
for an OrcIO as well.
We might prepare a corresponding PR if that seems like a viable solution.
> Add a reader/writer that does not depend on Hadoop FileSystem
> -------------------------------------------------------------
>
> Key: ORC-508
> URL: https://issues.apache.org/jira/browse/ORC-508
> Project: ORC
> Issue Type: Improvement
> Components: Java
> Reporter: Ismaël Mejía
> Priority: Major
>
> It seems that the default implementation classes of Orc today depend on
> Hadoop FS objects to write. This is not ideal for APIs that do not rely on
> Hadoop. For some context I was taking a look at adding support for Apache
> Beam, but Beam's API supports multiple filesystems with a more generic
> abstraction that relies on Java's Channels and Streams APIs and delegate
> directly to Distributed FS e.g. Google Cloud Storage, Amazon S3, etc. It
> would be really nice to have such support in the core implementation and to
> maybe split the Hadoop dependencies implementation into its own module in the
> future.
--
This message was sent by Atlassian Jira
(v8.3.4#803005)
