55153f5c14
Starting work on this, but need to find a way to ensure that, after doing a checkout from `apache/master`, we can successfully return to the current checkout. I believe that `git rev-parse HEAD` will get me what I want, but pushing this PR up to test what the Jenkins boxes are seeing.
Author: Brennon York <brennon.york@capitalone.com>
Closes #5093 from brennonyork/SPARK-4123 and squashes the following commits:
42e243e [Brennon York] moved starting test output to before pr tests, fixed indentation, changed mvn call to build/mvn
dadd941 [Brennon York] reverted assembly pom, put the regular test suite back in play
7aa1dee [Brennon York] set new dendencies into a <code> block, removed the bash debugging flag
0074566 [Brennon York] fixed minor echo issue with quotes
e229802 [Brennon York] updated to print the new dependency found
27bb9b5 [Brennon York] changed the assembly pom to test whether the pr test will pick up new deps
5375ad8 [Brennon York] git output to dev null
9bce980 [Brennon York] ensure both gate files exist
8f3c4b4 [Brennon York] updated to reflect the correct pushed in HEAD variable
2bc7b27 [Brennon York] added a pom gate check
a18db71 [Brennon York] full test of new deps script
ea170de [Brennon York] dont let mvn execute tests
f70d8cd [Brennon York] testing mvn with package
62ffd65 [Brennon York] updated dependency output message and changed compile to package given the jenkins failure output
04747e4 [Brennon York] adding simple mvn statement to see if command executes and prints compile output
87f9bea [Brennon York] added -x flag with bash to get insight into what is executing and what isnt
9e87208 [Brennon York] added set blocks to catch any non-zero exit codes and updated output
6b3042b [Brennon York] removed excess git checkout print statements
4077d46 [Brennon York] Merge remote-tracking branch 'upstream/master' into SPARK-4123
2bb5527 [Brennon York] added echo statement so jenkins logs which pr tests are running
d027f8f [Brennon York] proper piping of unnecessary stderr and stdout
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assembly | ||
bagel | ||
bin | ||
build | ||
conf | ||
core | ||
data/mllib | ||
dev | ||
docker | ||
docs | ||
ec2 | ||
examples | ||
external | ||
extras | ||
graphx | ||
launcher | ||
mllib | ||
network | ||
project | ||
python | ||
repl | ||
sbin | ||
sbt | ||
sql | ||
streaming | ||
tools | ||
yarn | ||
.gitattributes | ||
.gitignore | ||
.rat-excludes | ||
CONTRIBUTING.md | ||
LICENSE | ||
make-distribution.sh | ||
NOTICE | ||
pom.xml | ||
README.md | ||
scalastyle-config.xml | ||
tox.ini |
Apache Spark
Spark is a fast and general cluster computing system for Big Data. It provides high-level APIs in Scala, Java, and Python, 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 structured data processing, MLlib for machine learning, GraphX for graph processing, and Spark Streaming for stream processing.
Online Documentation
You can find the latest Spark documentation, including a programming guide, on the project web page and project wiki. This README file only contains basic setup instructions.
Building Spark
Spark is built using Apache Maven. To build Spark and its example programs, run:
mvn -DskipTests clean package
(You do not need to do this if you downloaded a pre-built package.) More detailed documentation is available from the project site, at "Building Spark".
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-cluster" or "yarn-client" 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 all automated 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. See also "Third Party Hadoop Distributions" for guidance on building a Spark application that works with a particular distribution.
Configuration
Please refer to the Configuration guide in the online documentation for an overview on how to configure Spark.