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https://issues.apache.org/jira/browse/NIFI-5130?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16464365#comment-16464365
]
ASF GitHub Bot commented on NIFI-5130:
--------------------------------------
Github user MikeThomsen commented on a diff in the pull request:
https://github.com/apache/nifi/pull/2666#discussion_r186213122
--- Diff:
nifi-nar-bundles/nifi-influxdb-bundle/nifi-influxdb-processors/src/main/java/org/apache/nifi/processors/influxdb/ExecuteInfluxDBQuery.java
---
@@ -86,6 +93,18 @@
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
.build();
+ public static final PropertyDescriptor INFLUX_DB_QUERY_CHUNK_SIZE =
new PropertyDescriptor.Builder()
+ .name("influxdb-query-chunk-size")
+ .displayName("Results chunk size")
+ .description("Chunking can be used to return results in a
stream of smaller batches "
+ + "(each has a partial results up to a chunk size) rather
than as a single response. "
+ + "Chunking queries can return an unlimited number of
rows. Note: Chunking is enable when result chunk size is greater than 0")
+
.defaultValue(String.valueOf(DEFAULT_INFLUX_RESPONSE_CHUNK_SIZE))
+
.expressionLanguageSupported(ExpressionLanguageScope.FLOWFILE_ATTRIBUTES)
+ .addValidator(StandardValidators.createLongValidator(0,
Integer.MAX_VALUE, true))
--- End diff --
Ok, go with the default @michalmisiewicz
> ExecuteInfluxDBQuery processor chunking support
> -----------------------------------------------
>
> Key: NIFI-5130
> URL: https://issues.apache.org/jira/browse/NIFI-5130
> Project: Apache NiFi
> Issue Type: Improvement
> Components: Extensions
> Reporter: Michał Misiewicz
> Priority: Minor
>
> Many production InfluxDB installation has limited number of rows returned in
> a single query (by default 10k). In case of huge collections, 10k rows can
> correspond to less than 1 minute of events, which make usage of
> ExecuteInfluxDBQuery processor inconvenient. I suggest adding support for
> chunking queries. Chunking can be used to return results in a stream of
> smaller batches (each has a partial results up to a chunk size) rather than
> as a single response. Chunking query can return an unlimited number of rows.
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