System to generate Logical Design for MPP Clusters using self-learning model

摘要

Haystaxs provides a framework which transforms the cluster into a self-learning database by suggesting a logical design. This is achieved by extracting the schema definition and query logs from the MPP cluster; synthesize this information to build a probabilistic model using the abstract syntax tree. This information is passed through the rule engine and model evaluator to generate recommendations which would improve the cluster performance.