Apache Spark - A unified analytics engine for large-scale data processing
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Davies Liu 05ac023dc8 [HOTFIX] fix flaky test in PySpark SQL
It may loss precision in microseconds when using float for it.

Author: Davies Liu <davies@databricks.com>

Closes #7344 from davies/fix_date_test and squashes the following commits:

249ec61 [Davies Liu] fix flaky test
2015-07-10 13:05:23 -07:00
assembly [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0 2015-06-03 10:11:27 -07:00
bagel [SPARK-7801] [BUILD] Updating versions to SPARK 1.5.0 2015-06-03 10:11:27 -07:00
bin [SPARK-7733] [CORE] [BUILD] Update build, code to use Java 7 for 1.5.0+ 2015-06-07 20:18:13 +01:00
build [SPARK-8316] Upgrade to Maven 3.3.3 2015-06-15 08:18:01 +01:00
conf [SPARK-3071] Increase default driver memory 2015-07-01 23:11:02 -07:00
core [SPARK-8675] Executors created by LocalBackend won't get the same classpath as other executor backends 2015-07-10 09:52:40 -07:00
data/mllib [SPARK-8758] [MLLIB] Add Python user guide for PowerIterationClustering 2015-07-02 09:59:54 -07:00
dev [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
docker [SPARK-2691] [MESOS] Support for Mesos DockerInfo 2015-05-01 18:41:22 -07:00
docs [SPARK-8958] Dynamic allocation: change cached timeout to infinity 2015-07-10 09:48:17 -07:00
ec2 [SPARK-8863] [EC2] Check aws access key from aws credentials if there is no boto config 2015-07-09 10:23:36 -07:00
examples [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
external [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
extras [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
graphx [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
launcher [SPARK-8776] Increase the default MaxPermSize 2015-07-02 22:09:07 -07:00
mllib [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
network [SPARK-3071] Increase default driver memory 2015-07-01 23:11:02 -07:00
project [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
python [HOTFIX] fix flaky test in PySpark SQL 2015-07-10 13:05:23 -07:00
R [SPARK-8940] [SPARKR] Don't overwrite given schema in createDataFrame 2015-07-09 09:57:12 -07:00
repl [SPARK-7944] [SPARK-8013] Remove most of the Spark REPL fork for Scala 2.11 2015-07-10 16:22:49 +01:00
sbin [SPARK-5412] [DEPLOY] Cannot bind Master to a specific hostname as per the documentation 2015-05-15 11:30:19 -07:00
sbt Adde LICENSE Header to build/mvn, build/sbt and sbt/sbt 2014-12-29 10:48:53 -08:00
sql [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
streaming [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
tools [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
unsafe [SPARK-8247] [SPARK-8249] [SPARK-8252] [SPARK-8254] [SPARK-8257] [SPARK-8258] [SPARK-8259] [SPARK-8261] [SPARK-8262] [SPARK-8253] [SPARK-8260] [SPARK-8267] [SQL] Add String Expressions 2015-07-09 11:11:34 -07:00
yarn [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
.gitattributes [SPARK-3870] EOL character enforcement 2014-10-31 12:39:52 -07:00
.gitignore [SPARK-8495] [SPARKR] Add a .lintr file to validate the SparkR files and the lint-r script 2015-06-20 16:10:14 -07:00
.rat-excludes [SPARK-6123] [SPARK-6775] [SPARK-6776] [SQL] Refactors Parquet read path for interoperability and backwards-compatibility 2015-07-08 15:51:01 -07:00
CONTRIBUTING.md [SPARK-6889] [DOCS] CONTRIBUTING.md updates to accompany contribution doc updates 2015-04-21 22:34:31 -07:00
LICENSE [SPARK-8709] Exclude hadoop-client's mockito-all dependency 2015-06-29 14:07:55 -07:00
make-distribution.sh [SPARK-7733] [CORE] [BUILD] Update build, code to use Java 7 for 1.5.0+ 2015-06-07 20:18:13 +01:00
NOTICE SPARK-1827. LICENSE and NOTICE files need a refresh to contain transitive dependency info 2014-05-14 09:38:33 -07:00
pom.xml [SPARK-7944] [SPARK-8013] Remove most of the Spark REPL fork for Scala 2.11 2015-07-10 16:22:49 +01:00
README.md Update README to include DataFrames and zinc. 2015-05-31 23:55:45 -07:00
scalastyle-config.xml [SPARK-7977] [BUILD] Disallowing println 2015-07-10 11:34:01 +01:00
tox.ini [SPARK-7427] [PYSPARK] Make sharedParams match in Scala, Python 2015-05-10 19:18:32 -07:00

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 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 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:

build/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 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. 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.