e79284da59
* new interval based cost function Addresses issues with balancing of segments in the existing cost function - `gapPenalty` led to clusters of segments ~30 days apart - `recencyPenalty` caused imbalance among recent segments - size-based cost could be skewed by compression New cost function is purely based on segment intervals: - assumes each time-slice of a partition is a constant cost - cost is additive, i.e. cost(A, B union C) = cost(A, B) + cost(A, C) - cost decays exponentially based on distance between time-slices * comments and formatting * add more comments to explain the calculation |
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| api | ||
| aws-common | ||
| benchmarks | ||
| common | ||
| distribution | ||
| docs | ||
| examples | ||
| extensions-contrib | ||
| extensions-core | ||
| indexing-hadoop | ||
| indexing-service | ||
| integration-tests | ||
| processing | ||
| publications | ||
| server | ||
| services | ||
| .gitignore | ||
| .travis.yml | ||
| CONTRIBUTING.md | ||
| DruidCorporateCLA.pdf | ||
| DruidIndividualCLA.pdf | ||
| LICENSE | ||
| NOTICE | ||
| README.md | ||
| eclipse.importorder | ||
| eclipse_formatting.xml | ||
| intellij_formatting.jar | ||
| pom.xml | ||
| upload.sh | ||
README.md
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
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.