MRQL with Spark and Flink SQL announces new release

Apache MRQL is one of those new breed SQL on Hadoop tools which  run a SQL query using Apache Flink engine and conveniently switch over to Apache Spark or Apache Hama or plain old MapReduce as required.

Apache MRQL recently announced the release of new version 0.6 where it has added new features for incremental query processing. Further, it can now run with newer versions of Apache Flink and more importantly in YARN mode. MRQL is created by the same guys who are behind Apache Hama BSP engine and Apache Horn deep learning engine.

...MRQL (pronounced miracle) is claimed to be 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.