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.

Presto Connector for DataCTRL – Mario Ceste, Jr., SAP NS2

Presto Connector for DataCTRL – Mario Ceste, Jr., SAP NS2

DataCTRL is a data management platform for ingesting large quantities of disparate data sets. We’ve written a connector for Presto which allows our users to leverage the data they’ve ingested using SQL. Integrating Presto with our platform has given our customers a quick and effective way to query their data while also building additional data products.