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author | Chris Fregly <chris@fregly.com> | 2014-08-02 13:35:35 -0700 |
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committer | Tathagata Das <tathagata.das1565@gmail.com> | 2014-08-02 13:35:35 -0700 |
commit | 91f9504e6086fac05b40545099f9818949c24bca (patch) | |
tree | c79c63f0b3f82c4c9b632072f384b85bc7f646f1 /docs/streaming-programming-guide.md | |
parent | 67bd8e3c217a80c3117a6e3853aa60fe13d08c91 (diff) | |
download | spark-91f9504e6086fac05b40545099f9818949c24bca.tar.gz spark-91f9504e6086fac05b40545099f9818949c24bca.tar.bz2 spark-91f9504e6086fac05b40545099f9818949c24bca.zip |
[SPARK-1981] Add AWS Kinesis streaming support
Author: Chris Fregly <chris@fregly.com>
Closes #1434 from cfregly/master and squashes the following commits:
4774581 [Chris Fregly] updated docs, renamed retry to retryRandom to be more clear, removed retries around store() method
0393795 [Chris Fregly] moved Kinesis examples out of examples/ and back into extras/kinesis-asl
691a6be [Chris Fregly] fixed tests and formatting, fixed a bug with JavaKinesisWordCount during union of streams
0e1c67b [Chris Fregly] Merge remote-tracking branch 'upstream/master'
74e5c7c [Chris Fregly] updated per TD's feedback. simplified examples, updated docs
e33cbeb [Chris Fregly] Merge remote-tracking branch 'upstream/master'
bf614e9 [Chris Fregly] per matei's feedback: moved the kinesis examples into the examples/ dir
d17ca6d [Chris Fregly] per TD's feedback: updated docs, simplified the KinesisUtils api
912640c [Chris Fregly] changed the foundKinesis class to be a publically-avail class
db3eefd [Chris Fregly] Merge remote-tracking branch 'upstream/master'
21de67f [Chris Fregly] Merge remote-tracking branch 'upstream/master'
6c39561 [Chris Fregly] parameterized the versions of the aws java sdk and kinesis client
338997e [Chris Fregly] improve build docs for kinesis
828f8ae [Chris Fregly] more cleanup
e7c8978 [Chris Fregly] Merge remote-tracking branch 'upstream/master'
cd68c0d [Chris Fregly] fixed typos and backward compatibility
d18e680 [Chris Fregly] Merge remote-tracking branch 'upstream/master'
b3b0ff1 [Chris Fregly] [SPARK-1981] Add AWS Kinesis streaming support
Diffstat (limited to 'docs/streaming-programming-guide.md')
-rw-r--r-- | docs/streaming-programming-guide.md | 12 |
1 files changed, 8 insertions, 4 deletions
diff --git a/docs/streaming-programming-guide.md b/docs/streaming-programming-guide.md index 7b8b793343..9f331ed50d 100644 --- a/docs/streaming-programming-guide.md +++ b/docs/streaming-programming-guide.md @@ -9,7 +9,7 @@ title: Spark Streaming Programming Guide # Overview Spark Streaming is an extension of the core Spark API that allows enables high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources -like Kafka, Flume, Twitter, ZeroMQ or plain old TCP sockets and be processed using complex +like Kafka, Flume, Twitter, ZeroMQ, Kinesis or plain old TCP sockets and be processed using complex algorithms expressed with high-level functions like `map`, `reduce`, `join` and `window`. Finally, processed data can be pushed out to filesystems, databases, and live dashboards. In fact, you can apply Spark's in-built @@ -38,7 +38,7 @@ stream of results in batches. Spark Streaming provides a high-level abstraction called *discretized stream* or *DStream*, which represents a continuous stream of data. DStreams can be created either from input data -stream from sources such as Kafka and Flume, or by applying high-level +stream from sources such as Kafka, Flume, and Kinesis, or by applying high-level operations on other DStreams. Internally, a DStream is represented as a sequence of [RDDs](api/scala/index.html#org.apache.spark.rdd.RDD). @@ -313,7 +313,7 @@ To write your own Spark Streaming program, you will have to add the following de artifactId = spark-streaming_{{site.SCALA_BINARY_VERSION}} version = {{site.SPARK_VERSION}} -For ingesting data from sources like Kafka and Flume that are not present in the Spark +For ingesting data from sources like Kafka, Flume, and Kinesis that are not present in the Spark Streaming core API, you will have to add the corresponding artifact `spark-streaming-xyz_{{site.SCALA_BINARY_VERSION}}` to the dependencies. For example, @@ -327,6 +327,7 @@ some of the common ones are as follows. <tr><td> Twitter </td><td> spark-streaming-twitter_{{site.SCALA_BINARY_VERSION}} </td></tr> <tr><td> ZeroMQ </td><td> spark-streaming-zeromq_{{site.SCALA_BINARY_VERSION}} </td></tr> <tr><td> MQTT </td><td> spark-streaming-mqtt_{{site.SCALA_BINARY_VERSION}} </td></tr> +<tr><td> Kinesis<br/>(built separately)</td><td> kinesis-asl_{{site.SCALA_BINARY_VERSION}} </td></tr> <tr><td> </td><td></td></tr> </table> @@ -442,7 +443,7 @@ see the API documentations of the relevant functions in Scala and [JavaStreamingContext](api/scala/index.html#org.apache.spark.streaming.api.java.JavaStreamingContext) for Java. -Additional functionality for creating DStreams from sources such as Kafka, Flume, and Twitter +Additional functionality for creating DStreams from sources such as Kafka, Flume, Kinesis, and Twitter can be imported by adding the right dependencies as explained in an [earlier](#linking) section. To take the case of Kafka, after adding the artifact `spark-streaming-kafka_{{site.SCALA_BINARY_VERSION}}` to the @@ -467,6 +468,9 @@ For more details on these additional sources, see the corresponding [API documen Furthermore, you can also implement your own custom receiver for your sources. See the [Custom Receiver Guide](streaming-custom-receivers.html). +### Kinesis +[Kinesis](streaming-kinesis.html) + ## Operations There are two kinds of DStream operations - _transformations_ and _output operations_. Similar to RDD transformations, DStream transformations operate on one or more DStreams to create new DStreams |