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Diffstat (limited to 'docs/streaming-flume-integration.md')
| -rw-r--r-- | docs/streaming-flume-integration.md | 13 |
1 files changed, 11 insertions, 2 deletions
diff --git a/docs/streaming-flume-integration.md b/docs/streaming-flume-integration.md index 383d954409..e2d589b843 100644 --- a/docs/streaming-flume-integration.md +++ b/docs/streaming-flume-integration.md @@ -71,7 +71,16 @@ configuring Flume agents. cluster (Mesos, YARN or Spark Standalone), so that resource allocation can match the names and launch the receiver in the right machine. -3. **Deploying:** Package `spark-streaming-flume_{{site.SCALA_BINARY_VERSION}}` and its dependencies (except `spark-core_{{site.SCALA_BINARY_VERSION}}` and `spark-streaming_{{site.SCALA_BINARY_VERSION}}` which are provided by `spark-submit`) into the application JAR. Then use `spark-submit` to launch your application (see [Deploying section](streaming-programming-guide.html#deploying-applications) in the main programming guide). +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-flume_{{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). + + For Python applications which lack SBT/Maven project management, `spark-streaming-flume_{{site.SCALA_BINARY_VERSION}}` and its dependencies can be directly added to `spark-submit` using `--packages` (see [Application Submission Guide](submitting-applications.html)). That is, + + ./bin/spark-submit --packages org.apache.spark:spark-streaming-flume_{{site.SCALA_BINARY_VERSION}}:{{site.SPARK_VERSION_SHORT}} ... + + Alternatively, you can also download the JAR of the Maven artifact `spark-streaming-flume-assembly` from the + [Maven repository](http://search.maven.org/#search|ga|1|a%3A%22spark-streaming-flume-assembly_{{site.SCALA_BINARY_VERSION}}%22%20AND%20v%3A%22{{site.SPARK_VERSION_SHORT}}%22) and add it to `spark-submit` with `--jars`. ## Approach 2: Pull-based Approach using a Custom Sink Instead of Flume pushing data directly to Spark Streaming, this approach runs a custom Flume sink that allows the following. @@ -157,7 +166,7 @@ configuring Flume agents. Note that each input DStream can be configured to receive data from multiple sinks. -3. **Deploying:** Package `spark-streaming-flume_{{site.SCALA_BINARY_VERSION}}` and its dependencies (except `spark-core_{{site.SCALA_BINARY_VERSION}}` and `spark-streaming_{{site.SCALA_BINARY_VERSION}}` which are provided by `spark-submit`) into the application JAR. Then use `spark-submit` to launch your application (see [Deploying section](streaming-programming-guide.html#deploying-applications) in the main programming guide). +3. **Deploying:** This is same as the first approach. |