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Posted to dev@lucene.apache.org by "Joel Bernstein (JIRA)" <ji...@apache.org> on 2016/07/12 00:21:11 UTC
[jira] [Commented] (SOLR-9240) Support running the topic()
Streaming Expression in parallel mode.
[ https://issues.apache.org/jira/browse/SOLR-9240?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15371958#comment-15371958 ]
Joel Bernstein commented on SOLR-9240:
--------------------------------------
This ticket is looking fairly good. I did a round of manual testing which works as expected.
{code}
parallel(workerCollection,
workers="2",
sort="_version_ desc",
daemon(update(updateCollection,
batchSize=200,
topic(checkpointCollection,
topicCollection,
q=*:*,
id="topic40",
fl="id, to , from",
partitionKeys="id",
initialCheckpoint="0")),
runInterval="1000",
id="test3"))
{code}
> Support running the topic() Streaming Expression in parallel mode.
> ------------------------------------------------------------------
>
> Key: SOLR-9240
> URL: https://issues.apache.org/jira/browse/SOLR-9240
> Project: Solr
> Issue Type: Improvement
> Reporter: Joel Bernstein
> Assignee: Joel Bernstein
> Attachments: SOLR-9240.patch, SOLR-9240.patch
>
>
> Currently the topic() function won't run in parallel mode because each worker needs to maintain a separate set of checkpoints. The proposed solution for this is to append the worker ID to the topic ID, which will cause each worker to have it's own checkpoints.
> It would be useful to support parallelizing the topic function because it will provide a general purpose approach for processing text in parallel across worker nodes.
> For example this would allow a classify() function to be wrapped around a topic() function to classify documents in parallel across worker nodes.
> Sample syntax:
> {code}
> parallel(daemon(update(classify(topic(..., partitionKeys="id")))))
> {code}
> The example above would send a daemon to worker nodes that would classify all documents returned by the topic() function. The update function would send the output of classify() to a SolrCloud collection for indexing.
> The partitionKeys parameter would ensure that each worker would receive a partition of the results returned by the topic() function. This allows the classify() function to be run in parallel.
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