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Posted to issues@spark.apache.org by "bluejoe (JIRA)" <ji...@apache.org> on 2018/01/03 07:26:00 UTC

[jira] [Comment Edited] (SPARK-22936) providing HttpStreamSource and HttpStreamSink

    [ https://issues.apache.org/jira/browse/SPARK-22936?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16309220#comment-16309220 ] 

bluejoe edited comment on SPARK-22936 at 1/3/18 7:25 AM:
---------------------------------------------------------

The latest spark-http-stream artifact has been released to the central maven repository and is free to use in any java/scala projects.

I would be very appreciated that spark-http-stream is listed as a third-party Source/Sink in Spark documentation.


was (Author: bluejoe):
The latest spark-http-stream artifact has been released to the central maven repository and is free to use in any java/scala projects.

I will be appreciated that spark-http-stream is listed as a third-party Source/Sink in Spark documentation.

> providing HttpStreamSource and HttpStreamSink
> ---------------------------------------------
>
>                 Key: SPARK-22936
>                 URL: https://issues.apache.org/jira/browse/SPARK-22936
>             Project: Spark
>          Issue Type: New Feature
>          Components: Structured Streaming
>    Affects Versions: 2.1.0
>            Reporter: bluejoe
>
> Hi, in my project I completed a spark-http-stream, which is now available on https://github.com/bluejoe2008/spark-http-stream. I am thinking if it is useful to others and is ok to be integrated as a part of Spark.
> spark-http-stream transfers Spark structured stream over HTTP protocol. Unlike tcp streams, Kafka streams and HDFS file streams, http streams often flow across distributed big data centers on the Web. This feature is very helpful to build global data processing pipelines across different data centers (scientific research institutes, for example) who own separated data sets.
> The following code shows how to load messages from a HttpStreamSource:
> ```
> val lines = spark.readStream.format(classOf[HttpStreamSourceProvider].getName)
> 	.option("httpServletUrl", "http://localhost:8080/xxxx")
> 	.option("topic", "topic-1");
> 	.option("includesTimestamp", "true")
> 	.load();
> ```



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