sryza/spark-timeseries
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license: Apache-2.0
Language: Scala .
A library for time series analysis on Apache Spark
Time Series for Spark (The spark-ts
Package)
A Scala / Java / Python library for interacting with time series data on Apache Spark.
Post questions and comments to the Google group, or email them directly to mailto:spark-ts@googlegroups.com.
Note: The spark-ts library is no longer under active development by me (Sandy). I unfortunately no longer have bandwidth to develop features, answer all questions on the mailing list, or fix all bugs that are filed.
That said, I remain happy to review pull requests and do whatever I can to aid others in advancing the library.
Docs are available at http://sryza.github.io/spark-timeseries.
Or check out the Scaladoc, Javadoc, or Python doc.
The aim here is to provide
- A set of abstractions for manipulating large time series data sets, similar to what's provided for smaller data sets in Pandas, Matlab, and R's zoo and xts packages.
- Models, tests, and functions that enable dealing with time series from a statistical perspective, similar to what's provided in StatsModels and a variety of Matlab and R packages.
The library sits on a few other excellent Java and Scala libraries.
- Breeze for NumPy-like, BLAS-able linear algebra.
- java.time for dates and times.
- Apache Commons Math for general math and statistics functionality.
- Apache Spark for distributed computation with in-memory capabilities.
Using this Repo
Building
We use Maven for building Java / Scala. To compile, run tests, and build jars:
mvn package
To run Python tests (requires nose):
cd python
export SPARK_HOME=<location of local Spark installation>
nosetests
Running
To run a spark-shell with spark-ts and its dependencies on the classpath:
spark-shell --jars target/sparkts-$VERSION-SNAPSHOT-jar-with-dependencies.jar
Releasing
To publish docs, easiest is to clone a separate version of this repo in some location we'll refer to as DOCS_REPO. Then:
# Build main doc
mvn site -Ddependency.locations.enabled=false
# Build scaladoc
mvn scala:doc
# Build javadoc
mvn javadoc:javadoc
# Build Python doc
cd python
export SPARK_HOME=<location of local Spark installation>
export PYTHONPATH=$PYTHONPATH::$SPARK_HOME/python:$SPARK_HOME/python/lib/*
make html
cd ..
cp -r target/site/* $DOCS_REPO
cp -r python/build/html/ $DOCS_REPO/pydoc
cd $DOCS_REPO
git checkout gh-pages
git add -A
git commit -m "Some message that includes the hash of the relevant commit in master"
git push origin gh-pages
To build a Python source distribution, first build with Maven, then:
cp target/sparkts-$VERSION-SNAPSHOT-jar-with-dependencies.jar python/sparkts/
cd python
python setup.py sdist
To release Java/Scala packages (based on http://oryxproject.github.io/oryx/docs/how-to-release.html):
mvn -Darguments="-DskipTests" -DreleaseVersion=$VERSION \
-DdevelopmentVersion=$VERSION-SNAPSHOT release:prepare
mvn -s private-settings.xml -Darguments="-DskipTests" release:perform
To release Python packages (based on http://peterdowns.com/posts/first-time-with-pypi.html):
python setup.py register -r pypi
python setup.py sdist upload -r pypi
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