Gian Merlino 97765fdfef Simplify LikeFilter implementation of getBitmapIndex, estimateSelectivity. (#3910)
* Simplify LikeFilter implementation of getBitmapIndex, estimateSelectivity.

LikeFilter:
- Reduce code duplication, and simplify methods, at the cost of incurring an extra box
  of ImmutableBitmap into a SingletonImmutableList. I think this is fine, since this
  should be cheap and the code path is not hot (just once per filter).

Filters:
- Make estimateSelectivity public since it seems intended that they be used by Filter
  implementations, and Filters from extensions may want to use them too. Removed
  @VisibleForTesting for the same reason.
- Rename one of the estimatePredicateSelectivity overloads to estimateSelectivity, since
  predicates aren't involved.

* Address PR comments.

* Remove unused import

* Change List to Collection
2017-02-08 13:46:01 -06:00
2017-02-06 15:52:17 +05:30
2016-12-14 21:05:56 -08:00
2015-02-18 23:09:28 -08:00
2016-04-13 11:33:31 -07:00

Build Status Coverage Status

Druid

Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments.

Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.

Druid can load both streaming and batch data and integrates with Samza, Kafka, Storm, Spark, and Hadoop.

License

Apache License, Version 2.0

More Information

More information about Druid can be found on http://www.druid.io.

Documentation

You can find the documentation for the latest Druid release on the project website.

If you would like to contribute documentation, please do so under /docs/content in this repository and submit a pull request.

Getting Started

You can get started with Druid with our quickstart.

Reporting Issues

If you find any bugs, please file a GitHub issue.

Community

Community support is available on the druid-user mailing list(druid-user@googlegroups.com).

Development discussions occur on the druid-development list(druid-development@googlegroups.com).

We also have a couple people hanging out on IRC in #druid-dev on irc.freenode.net.

Contributing

Please follow the guidelines listed here.

Description
Apache Druid: a high performance real-time analytics database.
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