Modern data analytics embrace a disaggregated architecture which decouples storage, cache, and compute into network-connected independent components. With disaggregated cache, a key design decision is whether to push down query predicates to the cache server. Without predicate pushdown, the cache must send all data to compute nodes, creating network bottlenecks. With predicate pushdown, the cache server evaluates predicates on cached... Read More

Apache Spark is one of the most widely-used distributed data analysis frameworks. However, its JVM-based and row-oriented query execution engine limits Spark’s performance and scalability. In this talk, we will introduce DataFusion Comet, an accelerator for Apache Spark designed to improve the efficiency of Spark queries by translating them into native queries that leverage Apache Arrow and Apache DataFusion. We... Read More

Apache DataFusion is a fast, embeddable, and extensible query engine written in Rust that uses Apache Arrow as its memory model. In this talk we explain DataFusion in more detail and describe the types of data centric systems it is used to build. We will also review its high level architecture and feature set, discussing tradeoffs and performance between DataFusion's... Read More