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https://issues.apache.org/jira/browse/NIFI-1706?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16195216#comment-16195216
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ASF GitHub Bot commented on NIFI-1706:
--------------------------------------
Github user mattyb149 commented on a diff in the pull request:
https://github.com/apache/nifi/pull/2162#discussion_r143289913
--- Diff:
nifi-nar-bundles/nifi-standard-bundle/nifi-standard-processors/src/main/java/org/apache/nifi/processors/standard/QueryDatabaseTable.java
---
@@ -77,7 +80,8 @@
@InputRequirement(Requirement.INPUT_FORBIDDEN)
@Tags({"sql", "select", "jdbc", "query", "database"})
@SeeAlso({GenerateTableFetch.class, ExecuteSQL.class})
-@CapabilityDescription("Generates and executes a SQL select query to fetch
all rows whose values in the specified Maximum Value column(s) are larger than
the "
+@CapabilityDescription("Generates a SQL select query, or uses a provided
statement, and executes it to fetch all rows whose values in the specified "
--- End diff --
Nitpick, but an extra space between "or uses"
> Extend QueryDatabaseTable to support arbitrary queries
> ------------------------------------------------------
>
> Key: NIFI-1706
> URL: https://issues.apache.org/jira/browse/NIFI-1706
> Project: Apache NiFi
> Issue Type: Improvement
> Components: Core Framework
> Affects Versions: 1.4.0
> Reporter: Paul Bormans
> Assignee: Peter Wicks
> Labels: features
>
> The QueryDatabaseTable is able to observe a configured database table for new
> rows and yield these into the flowfile. The model of an rdbms however is
> often (if not always) normalized so you would need to join various tables in
> order to "flatten" the data into useful events for a processing pipeline as
> can be build with nifi or various tools within the hadoop ecosystem.
> The request is to extend the processor to specify an arbitrary sql query
> instead of specifying the table name + columns.
> In addition (this may be another issue?) it is desired to limit the number of
> rows returned per run. Not just because of bandwidth issue's from the nifi
> pipeline onwards but mainly because huge databases may not be able to return
> so many records within a reasonable time.
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