International Business Machines Corporation

Mara Matias

Austin Clifford

Ilker Ender

Aspects of the present invention disclose a method, computer program product, and system for auto-scaling a query engine. The method includes one or more processors monitoring query traffic at the query engine. The method further includes one or more processors classifying queries by a plurality of service classes based on a level of complexity of a query. The method further includes one or more processors comparing query traffic for each service class with a concurrency threshold of a maximum number of queries of the service class allowed to be concurrently processed. The method further includes one or more processors instructing auto-scaling of a cluster of worker nodes to change a number of worker nodes available in the cluster based on the comparison, over a defined period of time, of the query traffic relative to a defined upscaling threshold and a defined downscaling threshold.

Auto-scaling a query engine for enterprise-level big data workloads

Proposed are concepts for providing resilience (i.e., fault tolerance) for the temporary data needs of a distributed file system. Such concepts may, for instance, provide a virtual storage layer in a data node of a distributed file system. The virtual storage layer may provide resilience for the temporary data needs of a Massively Parallel Processing (MPP) SQL on Hadoop engine.

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Dublin, Ireland

Mara Matias