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BlinkDB: Sub-Second Approximate Queries on Very Large Data.

Home Page: http://blinkdb.cs.berkeley.edu/

License: Apache License 2.0

Shell 4.37% Python 0.89% Scala 90.37% Batchfile 0.15% Java 4.10% CSS 0.12%

blinkdb's Introduction

BlinkDB

Queries with Bounded Errors and Bounded Response Times on Very Large Data

BlinkDB is a large-scale data warehouse system built on Shark and Spark and is designed to be compatible with Apache Hive. It can answer HiveQL queries up to 200-300 times faster than Hive by executing them on user-specified samples of data and providing approximate answers that are augmented with meaningful error bars. BlinkDB 0.1.0 is an alpha developer release that supports creating/deleting samples on any input table and/or materialized view and executing approximate HiveQL queries with those aggregates that have statistical closed forms (i.e., AVG, SUM, COUNT, VAR and STDEV).

BlinkDB requires:

  • Scala 2.10.x
  • Spark 0.9.x

For current documentation, see the BlinkDB Wiki.

For more information about the BlinkDB Project, see the BlinkDB Website.

blinkdb's People

Contributors

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