Apache Spark - A unified analytics engine for large-scale data processing
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Adam Budde e4065376d2 [SPARK-19405][STREAMING] Support for cross-account Kinesis reads via STS
- Add dependency on aws-java-sdk-sts
- Replace SerializableAWSCredentials with new SerializableCredentialsProvider interface
- Make KinesisReceiver take SerializableCredentialsProvider as argument and
  pass credential provider to KCL
- Add new implementations of KinesisUtils.createStream() that take STS
  arguments
- Make JavaKinesisStreamSuite test the entire KinesisUtils Java API
- Update KCL/AWS SDK dependencies to 1.7.x/1.11.x

## What changes were proposed in this pull request?

[JIRA link with detailed description.](https://issues.apache.org/jira/browse/SPARK-19405)

* Replace SerializableAWSCredentials with new SerializableKCLAuthProvider class that takes 5 optional config params for configuring AWS auth and returns the appropriate credential provider object
* Add new public createStream() APIs for specifying these parameters in KinesisUtils

## How was this patch tested?

* Manually tested using explicit keypair and instance profile to read data from Kinesis stream in separate account (difficult to write a test orchestrating creation and assumption of IAM roles across separate accounts)
* Expanded JavaKinesisStreamSuite to test the entire Java API in KinesisUtils

## License acknowledgement
This contribution is my original work and that I license the work to the project under the project’s open source license.

Author: Budde <budde@amazon.com>

Closes #16744 from budde/master.
2017-02-22 11:32:36 -05:00
.github [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site 2016-11-23 11:25:47 +00:00
assembly [SPARK-19550][BUILD][CORE][WIP] Remove Java 7 support 2017-02-16 12:32:45 +00:00
bin [SPARK-1267][SPARK-18129] Allow PySpark to be pip installed 2016-11-16 14:22:15 -08:00
build [SPARK-19550][BUILD][CORE][WIP] Remove Java 7 support 2017-02-16 12:32:45 +00:00
common [SPARK-19534][TESTS] Convert Java tests to use lambdas, Java 8 features 2017-02-19 09:42:50 -08:00
conf [SPARK-11653][DEPLOY] Allow spark-daemon.sh to run in the foreground 2016-10-20 09:49:58 +01:00
core [SPARK-19652][UI] Do auth checks for REST API access. 2017-02-21 16:14:34 -08:00
data [SPARK-16421][EXAMPLES][ML] Improve ML Example Outputs 2016-08-05 20:57:46 +01:00
dev [SPARK-19550] Follow-up: fixed a typo that fails the dev/make-distribution.sh script. 2017-02-18 14:08:59 +00:00
docs [SPARK-19337][ML][DOC] Documentation and examples for LinearSVC 2017-02-21 09:38:14 -08:00
examples [SPARK-19337][ML][DOC] Documentation and examples for LinearSVC 2017-02-21 09:38:14 -08:00
external [SPARK-19405][STREAMING] Support for cross-account Kinesis reads via STS 2017-02-22 11:32:36 -05:00
graphx [SPARK-14804][SPARK][GRAPHX] Fix checkpointing of VertexRDD/EdgeRDD 2017-01-25 17:17:34 -08:00
launcher [SPARK-19534][TESTS] Convert Java tests to use lambdas, Java 8 features 2017-02-19 09:42:50 -08:00
licenses [MINOR][BUILD] Add modernizr MIT license; specify "2014 and onwards" in license copyright 2016-06-04 21:41:27 +01:00
mllib [SPARK-19679][ML] Destroy broadcasted object without blocking 2017-02-22 16:36:03 +02:00
mllib-local [SPARK-19402][DOCS] Support LaTex inline formula correctly and fix warnings in Scala/Java APIs generation 2017-02-01 13:26:16 +00:00
project [SPARK-19652][UI] Do auth checks for REST API access. 2017-02-21 16:14:34 -08:00
python [SPARK-19405][STREAMING] Support for cross-account Kinesis reads via STS 2017-02-22 11:32:36 -05:00
R [SPARK-19639][SPARKR][EXAMPLE] Add spark.svmLinear example and update vignettes 2017-02-17 21:21:10 -08:00
repl [SPARK-19481] [REPL] [MAVEN] Avoid to leak SparkContext in Signaling.cancelOnInterrupt 2017-02-09 11:16:51 -08:00
resource-managers [SPARK-19626][YARN] Using the correct config to set credentials update time 2017-02-21 09:57:40 -08:00
sbin [SPARK-19083] sbin/start-history-server.sh script use of $@ without quotes 2017-01-06 09:57:49 -08:00
sql [SPARK-13721][SQL] Make GeneratorOuter unresolved. 2017-02-22 15:42:40 +01:00
streaming [SPARK-19652][UI] Do auth checks for REST API access. 2017-02-21 16:14:34 -08:00
tools [SPARK-18695] Bump master branch version to 2.2.0-SNAPSHOT 2016-12-02 21:09:37 -08:00
.gitattributes [SPARK-3870] EOL character enforcement 2014-10-31 12:39:52 -07:00
.gitignore [SPARK-19562][BUILD] Added exclude for dev/pr-deps to gitignore 2017-02-13 11:22:31 +00:00
.travis.yml [SPARK-19464][CORE][YARN][TEST-HADOOP2.6] Remove support for Hadoop 2.5 and earlier 2017-02-08 12:20:07 +00:00
appveyor.yml [SPARK-19464][CORE][YARN][TEST-HADOOP2.6] Remove support for Hadoop 2.5 and earlier 2017-02-08 12:20:07 +00:00
CONTRIBUTING.md [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site 2016-11-23 11:25:47 +00:00
LICENSE [SPARK-17960][PYSPARK][UPGRADE TO PY4J 0.10.4] 2016-10-21 09:48:24 +01:00
NOTICE [SPARK-18262][BUILD][SQL] JSON.org license is now CatX 2016-11-10 10:20:03 -08:00
pom.xml [SPARK-19405][STREAMING] Support for cross-account Kinesis reads via STS 2017-02-22 11:32:36 -05:00
README.md [MINOR][DOCS] Remove Apache Spark Wiki address 2016-12-10 16:40:10 +00:00
scalastyle-config.xml [SPARK-13747][CORE] Fix potential ThreadLocal leaks in RPC when using ForkJoinPool 2016-12-13 09:53:22 -08:00

Apache Spark

Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.

http://spark.apache.org/

Online Documentation

You can find the latest Spark documentation, including a programming guide, on the project web page. This README file only contains basic setup instructions.

Building Spark

Spark is built using Apache Maven. To build Spark and its example programs, run:

build/mvn -DskipTests clean package

(You do not need to do this if you downloaded a pre-built package.)

You can build Spark using more than one thread by using the -T option with Maven, see "Parallel builds in Maven 3". More detailed documentation is available from the project site, at "Building Spark".

For general development tips, including info on developing Spark using an IDE, see "Useful Developer Tools".

Interactive Scala Shell

The easiest way to start using Spark is through the Scala shell:

./bin/spark-shell

Try the following command, which should return 1000:

scala> sc.parallelize(1 to 1000).count()

Interactive Python Shell

Alternatively, if you prefer Python, you can use the Python shell:

./bin/pyspark

And run the following command, which should also return 1000:

>>> sc.parallelize(range(1000)).count()

Example Programs

Spark also comes with several sample programs in the examples directory. To run one of them, use ./bin/run-example <class> [params]. For example:

./bin/run-example SparkPi

will run the Pi example locally.

You can set the MASTER environment variable when running examples to submit examples to a cluster. This can be a mesos:// or spark:// URL, "yarn" to run on YARN, and "local" to run locally with one thread, or "local[N]" to run locally with N threads. You can also use an abbreviated class name if the class is in the examples package. For instance:

MASTER=spark://host:7077 ./bin/run-example SparkPi

Many of the example programs print usage help if no params are given.

Running Tests

Testing first requires building Spark. Once Spark is built, tests can be run using:

./dev/run-tests

Please see the guidance on how to run tests for a module, or individual tests.

A Note About Hadoop Versions

Spark uses the Hadoop core library to talk to HDFS and other Hadoop-supported storage systems. Because the protocols have changed in different versions of Hadoop, you must build Spark against the same version that your cluster runs.

Please refer to the build documentation at "Specifying the Hadoop Version" for detailed guidance on building for a particular distribution of Hadoop, including building for particular Hive and Hive Thriftserver distributions.

Configuration

Please refer to the Configuration Guide in the online documentation for an overview on how to configure Spark.

## Contributing

Please review the Contribution to Spark guide for information on how to get started contributing to the project.