Algebraix Query Accelerator for Apache Spark
By applying AQA to the Spark framework, developers and data scientists can use less expensive resources, fewer nodes, and shorten processing times to save total cost of ownership.
Whereas most SQL optimization techniques are focused on establishing adjacent data stores, AQA optimizes the actual query execution plans from Spark’s catalyst. Our software uses Data Algebra to cache a variety of equivalent opportunities and subsequently removes work from Spark’s SQL jobs while maintaining the correct end computations.
AQA is a simple to install software package that works in conjunction with Amazon Web Services, Elastic Map Reduce, and Amazon’s S3 filesystem. The application of our product requires no change to your current Spark scripts or queries.
The initial version of AQA runs alongside Apache Spark to improve SQL performance and user concurrency in that environment; however AQA is being developed for other databases and big data cloud environments to include Microsoft Azure and IBM Bluemix.