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From "bluejoe (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (SPARK-22936) providing HttpStreamSource and HttpStreamSink
Date Tue, 02 Jan 2018 06:01:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-22936?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

bluejoe updated SPARK-22936:
----------------------------
    Description: 
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:

{quote}val lines = spark.readStream.format(classOf[HttpStreamSourceProvider].getName)
	.option("httpServletUrl", "http://localhost:8080/xxxx")
	.option("topic", "topic-1");
	.option("includesTimestamp", "true")
	.load();{quote}

  was:
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();}}


> 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:
> {quote}val lines = spark.readStream.format(classOf[HttpStreamSourceProvider].getName)
> 	.option("httpServletUrl", "http://localhost:8080/xxxx")
> 	.option("topic", "topic-1");
> 	.option("includesTimestamp", "true")
> 	.load();{quote}



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