<commit_before>[![Build Status](https://travis-ci.org/sryza/spark-timeseries.svg)](https://travis-ci.org/sryza/spark-timeseries)

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](https://groups.google.com/forum/#!forum/spark-ts),
or email them directly to <mailto:<EMAIL>>.

Docs are available at http://sryza.github.io/spark-timeseries.

Or check out the [Scaladoc](http://sryza.github.io/spark-timeseries/0.3.0/scaladocs/index.html), [Javadoc](http://sryza.github.io/spark-timeseries/0.3.0/apidocs/index.html), or [Python doc](http://sryza.github.io/spark-timeseries/0.3.0/pydoc/py-modindex.html).

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<commit_msg>Update README with notice about support<commit_after>[![Build Status](https://travis-ci.org/sryza/spark-timeseries.svg)](https://travis-ci.org/sryza/spark-timeseries)

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](https://groups.google.com/forum/#!forum/spark-ts),
or email them directly to <mailto:<EMAIL>>.

### 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](http://sryza.github.io/spark-timeseries/0.3.0/scaladocs/index.html), [Javadoc](http://sryza.github.io/spark-timeseries/0.3.0/apidocs/index.html), or [Python doc](http://sryza.github.io/spark-timeseries/0.3.0/pydoc/py-modindex.html).

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
{'fraction_non_alphanumeric': 0.13296903460837886, 'fraction_numerical': 0.00819672131147541, 'mean_word_length': 4.534005037783375, 'pattern_counts': {'":': 0, '<': 7, '<?xml version=': 0, '>': 7, 'https://': 6, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '271192', 'n_tokens_mistral': 730, 'n_tokens_neox': 681, 'n_words': 215}