With the growing popularity of the lakehouse approach, it has become increasingly important for query engines to support these new formats such as Hudi. A previous blog discusses the evolution of presto-hudi integration via hive connector at a high level. With the latest community developments, a separate presto-hudi connector has come up but it is…
Overview Presto’s architecture originally only supported a single coordinator and a pool of workers. This has worked well for many years but created some challenges. To overcome these challenges, we came up with a new design with a disaggregated coordinator that allows the coordinator to be horizontally scaled out across a single pool of workers….
Apache Hudi is a fast growing data lake storage system that helps organizations build and manage petabyte-scale data lakes. Hudi brings stream style processing to batch-like big data by introducing primitives such as upserts, deletes and incremental queries. These features help surface faster, fresher data on a unified serving layer. Hudi tables can be stored…
Migrating SQL workloads from a fully on-premise environment to cloud infrastructure has numerous benefits, including alleviating resource contention and reducing costs by paying for computation resources on an on-demand basis. In the case of Presto running on data stored in HDFS, the separation of compute in the cloud and storage on-premises is apparent since Presto’s…
In a multi-tenant system like Presto careful memory management is required to keep the system stable and prevent individual queries from taking over all the resources. However, tracking the memory usage of data structures in an application (Presto) running on the Java Virtual Machine (JVM) requires a significant amount of work. In addition, Presto is…