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…
Earlier this month we hosted PrestoCon, a fantastic in-person event that showcased the innovation around the Presto project. In this blog we’ll detail Twilio’s presentation on their Presto use case, including their architecture, key optimizations, and lessons learned. You can also check out their full presentation here. In their session, Twilio engineers Aakash Pradeep and…
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…
Presto is known to be a high-performance, distributed SQL query engine for Big Data. It offers large-scale data analytics with multiple connectors for accessing various data sources. This capability enables the Presto users to further extend some features to build a large-scale data federation service on cloud. Alibaba Data Lake Analytics embraces Presto’s federated query…