5 Reasons Why AI Is the Future of SQL – Jared Zhao, AskEdith

5 Reasons Why AI Is the Future of SQL – Jared Zhao, AskEdith

SQL remains ubiquitous for data retrieval and analytics, yet can be tedious to write, and is downright unusable for business users. The 2-5 business day turnaround time for data projects is both disruptive and frustrating for business users. Data teams are becoming increasingly overwhelmed, and organizations are pushing to empower their “citizen data analysts.” With the advent of AI English-to-SQL platforms like AskEdith, now anyone can work with and query Presto using plain English questions. AskEdith integrates natively with web interfaces like Ahana for a seamless analytics experience.

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.