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https://issues.apache.org/jira/browse/CONNECTORS-1162?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14611574#comment-14611574
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Karl Wright commented on CONNECTORS-1162:
-----------------------------------------
Hi [~tugbadogan],
I didn't hear back from you about whether you were ready for code review. I
presume that, other than the unit tests, you were ready.
Based on what has been done so far, I've given you a "pass" for the midterm.
Here are my determinations, and recommendations going forward:
(1) You seem to have developed a good working understanding of Kafka and
ManifoldCF.
(2) You've produced workable code that can be integrated into MCF, with some
minor editing.
Specific recommendations:
- It would suggest taking maximum advantage of me and the MCF community at
large for subsequent development. More frequent and detailed communication
would help a lot. Don't be afraid to ask questions, post code snippets, and
describe what you've tried that isn't working. Modern software development
requires both individual initiative as well as collaboration.
Thanks!
> Apache Kafka Output Connector
> -----------------------------
>
> Key: CONNECTORS-1162
> URL: https://issues.apache.org/jira/browse/CONNECTORS-1162
> Project: ManifoldCF
> Issue Type: Wish
> Affects Versions: ManifoldCF 1.8.1, ManifoldCF 2.0.1
> Reporter: Rafa Haro
> Assignee: Karl Wright
> Labels: gsoc, gsoc2015
> Fix For: ManifoldCF 1.10, ManifoldCF 2.2
>
> Attachments: 1.JPG, 2.JPG
>
>
> Kafka is a distributed, partitioned, replicated commit log service. It
> provides the functionality of a messaging system, but with a unique design. A
> single Kafka broker can handle hundreds of megabytes of reads and writes per
> second from thousands of clients.
> Apache Kafka is being used for a number of uses cases. One of them is to use
> Kafka as a feeding system for streaming BigData processes, both in Apache
> Spark or Hadoop environment. A Kafka output connector could be used for
> streaming or dispatching crawled documents or metadata and put them in a
> BigData processing pipeline
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