Mirror of Apache Spark
Scala Java Python HiveQL R Shell Other
maropu and gatorsmile [SPARK-24206][SQL] Improve FilterPushdownBenchmark benchmark code
## What changes were proposed in this pull request?
This pr added benchmark code `FilterPushdownBenchmark` for string pushdown and updated performance results on the AWS `r3.xlarge`.

## How was this patch tested?
N/A

Author: Takeshi Yamamuro <yamamuro@apache.org>

Closes #21288 from maropu/UpdateParquetBenchmark.
Latest commit 98f363b Jun 24, 2018
Permalink
Failed to load latest commit information.
.github [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site Nov 23, 2016
R [SPARK-24187][R][SQL] Add array_join function to SparkR Jun 6, 2018
assembly [SPARK-23807][BUILD] Add Hadoop 3.1 profile with relevant POM fix ups Apr 24, 2018
bin [SPARK-24547][K8S] Allow for building spark on k8s docker images with… Jun 21, 2018
build [SPARK-24526][BUILD][TEST-MAVEN] Spaces in the build dir causes failu… Jun 18, 2018
common [SPARK-24578][CORE] Cap sub-region's size of returned nio buffer Jun 20, 2018
conf [SPARK-22466][SPARK SUBMIT] export SPARK_CONF_DIR while conf is default Nov 9, 2017
core [SPARK-24518][CORE] Using Hadoop credential provider API to store pas… Jun 22, 2018
data [SPARK-23205][ML] Update ImageSchema.readImages to correctly set alph… Jan 26, 2018
dev [SPARK-24372][BUILD] Add scripts to help with preparing releases. Jun 22, 2018
docs [SPARK-24518][CORE] Using Hadoop credential provider API to store pas… Jun 22, 2018
examples [SPARK-23984][K8S] Initial Python Bindings for PySpark on K8s Jun 8, 2018
external [SPARK-24332][SS][MESOS] Fix places reading 'spark.network.timeout' a… May 24, 2018
graphx [SPARK-23028] Bump master branch version to 2.4.0-SNAPSHOT Jan 12, 2018
hadoop-cloud [SPARK-23807][BUILD] Add Hadoop 3.1 profile with relevant POM fix ups Apr 24, 2018
launcher [SPARK-24319][SPARK SUBMIT] Fix spark-submit execution where no main … Jun 14, 2018
licenses [SPARK-24248][K8S] Use level triggering and state reconciliation in s… Jun 14, 2018
mllib-local [SPARK-23085][ML] API parity for mllib.linalg.Vectors.sparse Jan 19, 2018
mllib [SPARK-24216][SQL] Spark TypedAggregateExpression uses getSimpleName … Jun 12, 2018
project [SPARK-23010][BUILD][FOLLOWUP] Fix java checkstyle failure of kuberne… Jun 12, 2018
python [SPARK-23934][SQL] Adding map_from_entries function Jun 22, 2018
repl [SPARK-16451][REPL] Fail shell if SparkSession fails to start. Jun 5, 2018
resource-managers [SPARK-16630][YARN] Blacklist a node if executors won't launch on it Jun 21, 2018
sbin [PYSPARK] Update py4j to version 0.10.7. May 9, 2018
sql [SPARK-24206][SQL] Improve FilterPushdownBenchmark benchmark code Jun 24, 2018
streaming [SPARK-24452][SQL][CORE] Avoid possible overflow in int add or multiple Jun 15, 2018
tools [SPARK-23028] Bump master branch version to 2.4.0-SNAPSHOT Jan 12, 2018
.gitattributes [SPARK-3870] EOL character enforcement Oct 31, 2014
.gitignore [SPARK-23572][DOCS] Bring "security.md" up to date. Mar 26, 2018
.travis.yml [SPARK-18278][SCHEDULER] Spark on Kubernetes - Basic Scheduler Backend Nov 29, 2017
CONTRIBUTING.md [SPARK-18073][DOCS][WIP] Migrate wiki to spark.apache.org web site Nov 23, 2016
LICENSE [SPARK-24248][K8S] Use level triggering and state reconciliation in s… Jun 14, 2018
NOTICE [SPARK-18278][SCHEDULER] Spark on Kubernetes - Basic Scheduler Backend Nov 29, 2017
README.md [SPARK-23010][K8S] Initial checkin of k8s integration tests. Jun 8, 2018
appveyor.yml [SPARK-22817][R] Use fixed testthat version for SparkR tests in AppVeyor Dec 17, 2017
pom.xml [SPARK-24248][K8S] Use level triggering and state reconciliation in s… Jun 14, 2018
scalastyle-config.xml [SPARK-23550][CORE] Cleanup `Utils`. Mar 7, 2018

README.md

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.

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" 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.