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srowen [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0
## What changes were proposed in this pull request?

Remove Scala 2.11 support in build files and docs, and in various parts of code that accommodated 2.11. See some targeted comments below.

## How was this patch tested?

Existing tests.

Closes #23098 from srowen/SPARK-26132.

Authored-by: Sean Owen <sean.owen@databricks.com>
Signed-off-by: Sean Owen <sean.owen@databricks.com>
Latest commit 8bc304f Mar 25, 2019
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.github [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site Nov 23, 2016
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assembly [SPARK-26134][CORE] Upgrading Hadoop to 2.7.4 to fix java.version pro… Nov 22, 2018
bin
build [SPARK-26144][BUILD] `build/mvn` should detect `scala.version` based … Nov 22, 2018
common [SPARK-27219][CORE] Treat timeouts as fatal in SASL fallback path. Mar 25, 2019
conf [SPARK-26890][DOC] Add list of available Dropwizard metrics in Spark … Feb 27, 2019
core [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
data [SPARK-22666][ML][SQL] Spark datasource for image format Sep 5, 2018
dev [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
docs [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
examples [MINOR][EXAMPLES] Add missing return keyword streaming word count exa… Mar 20, 2019
external [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
graphx [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
hadoop-cloud [SPARK-27175][BUILD] Upgrade hadoop-3 to 3.2.0 Mar 17, 2019
launcher [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
licenses-binary [SPARK-26986][ML][FOLLOWUP] Add JAXB reference impl to build for Java 9+ Mar 1, 2019
licenses
mllib-local [SPARK-19591][ML][MLLIB] Add sample weights to decision trees Jan 25, 2019
mllib
project
python [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
repl
resource-managers [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
sbin [SPARK-27056][MESOS] Remove start-shuffle-service.sh Mar 9, 2019
sql [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
streaming [SPARK-26941][YARN] Fix incorrect computation of maxNumExecutorFailur… Mar 17, 2019
tools [SPARK-25956] Make Scala 2.12 as default Scala version in Spark 3.0 Nov 15, 2018
.gitattributes [SPARK-3870] EOL character enforcement Oct 31, 2014
.gitignore [MINOR][DOC] Documentation on JVM options for SBT Jan 23, 2019
CONTRIBUTING.md [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site Nov 23, 2016
LICENSE [SPARK-24654][BUILD] Update, fix LICENSE and NOTICE, and specialize f… Jul 1, 2018
LICENSE-binary [SPARK-27054][BUILD][SQL] Remove the Calcite dependency Mar 10, 2019
NOTICE [SPARK-23654][BUILD] remove jets3t as a dependency of spark Aug 16, 2018
NOTICE-binary [SPARK-27054][BUILD][SQL] Remove the Calcite dependency Mar 10, 2019
README.md [SPARK-7721][INFRA] Run and generate test coverage report from Python… Feb 1, 2019
appveyor.yml [MINOR][BUILD] Remove -Phive-thriftserver profile within appveyor.yml Jul 30, 2018
pom.xml [SPARK-26132][BUILD][CORE] Remove support for Scala 2.11 in Spark 3.0.0 Mar 25, 2019
scalastyle-config.xml [SPARK-25986][BUILD] Add rules to ban throw Errors in application code Nov 14, 2018

README.md

Apache Spark

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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.

There is also a Kubernetes integration test, see resource-managers/kubernetes/integration-tests/README.md

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 and Enabling YARN" 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.

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