Github user srowen commented on a diff in the pull request:
https://github.com/apache/spark/pull/14981#discussion_r78702619
--- Diff: docs/streaming-kinesis-integration.md ---
@@ -119,15 +119,14 @@ A Kinesis stream can be set up at one of the valid
Kinesis endpoints with 1 or m
3. **Deploying:** As with any Spark applications, `spark-submit` is used
to launch your application. However, the details are slightly different for
Scala/Java applications and Python applications.
- For Scala and Java applications, if you are using SBT or Maven for
project management, then package
`spark-streaming-kinesis-asl_{{site.SCALA_BINARY_VERSION}}` and its
dependencies into the application JAR. Make sure
`spark-core_{{site.SCALA_BINARY_VERSION}}` and
`spark-streaming_{{site.SCALA_BINARY_VERSION}}` are marked as `provided`
dependencies as those are already present in a Spark installation. Then use
`spark-submit` to launch your application (see [Deploying
section](streaming-programming-guide.html#deploying-applications) in the main
programming guide).
+ You'll first need to perform a custom build of Spark. **Note that by
linking to this library, you will include
[ASL](https://aws.amazon.com/asl/)-licensed code in your application.**
Download Spark source and follow the [instructions](building-spark.html) to
build Spark with profile *-Pkinesis-asl*.
--- End diff --
Is this true? if you build the Kinesis code into your app as in the
following text and next paragraph it should work.
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