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Apache MRQL 0.9.6-incubating
Apache MRQL (pronounced miracle) is a query processing and optimization
system for large-scale, distributed data analysis. MRQL (the MapReduce
Query Language) is an SQL-like query language for large-scale data
analysis on a cluster of computers. The MRQL query processing system
can evaluate MRQL queries in four modes:
* in Map-Reduce mode using Apache Hadoop,
* in BSP mode (Bulk Synchronous Parallel mode) using Apache Hama,
* in Spark mode using Apache Spark,
* in Flink mode using Apache Flink.
The MRQL query language is powerful enough to express most common data
analysis tasks over many forms of raw in-situ data, such as XML and
JSON documents, binary files, and CSV documents. MRQL is more powerful
than other current high-level MapReduce languages, such as Hive and
PigLatin, since it can operate on more complex data and supports more
powerful query constructs, thus eliminating the need for using
explicit MapReduce code. With MRQL, users are able to express complex
data analysis tasks, such as PageRank, k-means clustering, matrix
factorization, etc, using SQL-like queries exclusively, while the MRQL
query processing system is able to compile these queries to efficient
Java code.
General Info
For the latest information about MRQL, please visit our website at:
and our wiki, at:
Getting Started
Installation instructions and a quick tutorial:
To build MRQL using maven, use 'mvn clean install'. To validate the
installation use 'mvn -DskipTests=false clean install', which runs the
queries in 'tests/queries' in memory, local Hadoop mode, local Hama
mode, local Spark mode, and local Flink mode.
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