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Posted to issues@spark.apache.org by "Devin Boyer (JIRA)" <ji...@apache.org> on 2019/07/16 17:57:00 UTC
[jira] [Commented] (SPARK-23443) Spark with Glue as external
catalog
[ https://issues.apache.org/jira/browse/SPARK-23443?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16886352#comment-16886352 ]
Devin Boyer commented on SPARK-23443:
-------------------------------------
FWIW, a little while back AWS released their implementation of the Glue Data Catalog for Hive and Spark as an open source repository. It includes instructions for how to integrate this library into Spark builds, which unfortunately currently requires hand-patching Hive.
https://github.com/awslabs/aws-glue-data-catalog-client-for-apache-hive-metastore#building-the-spark-client
> Spark with Glue as external catalog
> -----------------------------------
>
> Key: SPARK-23443
> URL: https://issues.apache.org/jira/browse/SPARK-23443
> Project: Spark
> Issue Type: New Feature
> Components: Spark Core
> Affects Versions: 3.0.0
> Reporter: Ameen Tayyebi
> Priority: Major
>
> AWS Glue Catalog is an external Hive metastore backed by a web service. It allows permanent storage of catalog data for BigData use cases.
> To find out more information about AWS Glue, please consult:
> * AWS Glue - [https://aws.amazon.com/glue/]
> * Using Glue as a Metastore catalog for Spark - [https://docs.aws.amazon.com/emr/latest/ReleaseGuide/emr-spark-glue.html]
> Today, the integration of Glue and Spark is through the Hive layer. Glue implements the IMetaStore interface of Hive and for installations of Spark that contain Hive, Glue can be used as the metastore.
> The feature set that Glue supports does not align 1-1 with the set of features that the latest version of Spark supports. For example, Glue interface supports more advanced partition pruning that the latest version of Hive embedded in Spark.
> To enable a more natural integration with Spark and to allow leveraging latest features of Glue, without being coupled to Hive, a direct integration through Spark's own Catalog API is proposed. This Jira tracks this work.
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