The Future of Presto’s Query Optimizer – Bill McKenna, Ahana

The Future of Presto’s Query Optimizer – Bill McKenna, Ahana

In this talk, you will hear from the query optimizer OG himself, Bill McKenna (Principal software engineer at Ahana, Architect for the query optimizer that became the code base of the Amazon Redshift query optimizer, and co-author of The Volcano Optimizer Generator: Extensibility and Efficient Search) go into detail about the state of modern query optimizers, and how Presto stacks up against them and where it will go in the near future. If database theory is your jam, you won’t want to miss this deeply technical presentation from one of the pioneers in the field.

Query Execution Optimization for Broadcast Join using Replicated-Reads Strategy – George Wang, Ahana

Query Execution Optimization for Broadcast Join using Replicated-Reads Strategy – George Wang, Ahana

Today presto supports broadcast join by having a worker to fetch data from a small data source to build a hash table and then sending the entire data over the network to all other workers for hash lookup probed by large data source. This can be optimized by a new query execution strategy as source data from small tables is pulled directly by all workers which is known as replicated reads from dimension tables. This feature comes with a nice caching property given that all worker nodes N are now participating in scanning the data from remote sources. The table scan operation for dimension tables is cacheable per all worker nodes. In addition, there will be better resource utilization because the presto scheduler can now reduce the number plan fragment to execute as the same workers run tasks in parallel within a single stage to reduce data shuffles.