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https://issues.apache.org/jira/browse/METRON-1829?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16656887#comment-16656887
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ASF GitHub Bot commented on METRON-1829:
----------------------------------------

Github user nickwallen commented on a diff in the pull request:

    https://github.com/apache/metron/pull/1239#discussion_r226675652
  
    --- Diff: 
metron-platform/metron-writer/src/main/java/org/apache/metron/writer/BulkWriterComponent.java
 ---
    @@ -118,12 +118,15 @@ public void commit(BulkWriterResponse response) {
     
       public void error(String sensorType, Throwable e, Iterable<Tuple> 
tuples, MessageGetStrategy messageGetStrategy) {
         LOG.error(format("Failing %d tuple(s); sensorType=%s", 
Iterables.size(tuples), sensorType), e);
    -    MetronError error = new MetronError()
    -            .withSensorType(Collections.singleton(sensorType))
    -            .withErrorType(Constants.ErrorType.INDEXING_ERROR)
    -            .withThrowable(e);
    -    tuples.forEach(t -> error.addRawMessage(messageGetStrategy.get(t)));
    -    handleError(tuples, error);
    +    tuples.forEach(t -> {
    --- End diff --
    
    Looks great.  I'm just going to spin it up and do some manual testing now.


> Large Error Message Causes Slow Search Performance
> --------------------------------------------------
>
>                 Key: METRON-1829
>                 URL: https://issues.apache.org/jira/browse/METRON-1829
>             Project: Metron
>          Issue Type: Bug
>            Reporter: Ryan Merriman
>            Priority: Major
>
> Errors that occur during batch writes in the index topologies (batch and RA) 
> are written to Elasticsearch as a single, large error message, with a field 
> for each failed message. For example, if the batch size is 5000, a single 
> error message will be created with 5000 fields `raw_message_0`, 
> `raw_message_1`, .., `raw_message_4999`. With such large messages, searching 
> the error index in Elasticsearch is excessively slow.



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