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https://issues.apache.org/jira/browse/NIFI-4473?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16236610#comment-16236610
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ASF GitHub Bot commented on NIFI-4473:
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GitHub user mattyb149 opened a pull request:
https://github.com/apache/nifi/pull/2247
NIFI-4473: Fixed SelectHiveQL flowfile handling during error conditions
So the behavior is inconsistent with other processors like ExecuteSQL, but
it has always been that way, so this fix is just to ensure it isn't any worse :)
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You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mattyb149/nifi NIFI-4473_1
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/nifi/pull/2247.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #2247
----
commit 6dca191ed641659b89f45cf46f8510f7f5530f2b
Author: Matthew Burgess <mattyb...@apache.org>
Date: 2017-11-02T21:13:22Z
NIFI-4473: Fixed SelectHiveQL flowfile handling during error conditions
----
> Add support for large result sets and normalizing Avro names to SelectHiveQL
> ----------------------------------------------------------------------------
>
> Key: NIFI-4473
> URL: https://issues.apache.org/jira/browse/NIFI-4473
> Project: Apache NiFi
> Issue Type: Improvement
> Components: Extensions
> Reporter: Matt Burgess
> Assignee: Matt Burgess
> Priority: Major
> Fix For: 1.5.0
>
>
> A number of enhancements were made to processors like QueryDatabaseTable to
> allow for such things as:
> - Splitting result sets into multiple flow files (i.e. Max Rows Per Flowfile
> property)
> - Max number of splits/rows returned (Max fragments)
> - Normalizing names to be Avro-compatible
> The RDBMS processors also now support Avro logical types, but the version of
> Avro needed by the current version of Hive (1.2.1) is Avro 1.7.7, which does
> not support logical types.
> These enhancements were made to JdbcCommon, but not to HiveJdbcCommon (the
> Hive version of the JDBC utils class). Since Hive queries can return even
> larger result sets than traditional RDBMS, these properties/enhancements are
> at least as valuable to have for SelectHiveQL.
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