Cloudera Impala – Fast, Interactive Queries with Hadoop by Istvan Szegedi.
From the post:
As discussed in the previous post about Twitter’s Storm, Hadoop is a batch oriented solution that has a lack of support for ad-hoc, real-time queries. Many of the players in Big Data have realised the need for fast, interactive queries besides the traditional Hadooop approach. Cloudera, one the key solution vendors in Big Data/Hadoop domain has just recently launched Cloudera Impala that addresses this gap.
As Cloudera Engineering team descibed in ther blog, their work was inspired by Google Dremel paper which is also the basis for Google BigQuery. Cloudera Impala provides a HiveQL-like query language for wide variety of SELECT statements with WHERE, GROUP BY, HAVING clauses, with ORDER BY – though currently LIMIT is mandatory with ORDER BY -, joins (LEFT, RIGTH, FULL, OUTER, INNER), UNION ALL, external tables, etc. It also supports arithmetic and logical operators and Hive built-in functions such as COUNT, SUM, LIKE, IN or BETWEEN. It can access data stored on HDFS but it does not use mapreduce, instead it is based on its own distributed query engine.
The current Impala release (Impala 1.0beta) does not support DDL statements (CREATE, ALTER, DROP TABLE), all the table creation/modification/deletion functions have to be executed via Hive and then refreshed in Impala shell.
Cloudera Impala is open-source under Apache Licence, the code can be retrieved from Github. Its components are written in C++, Java and Python.
Will get you off to a good start with Impala.