Grab uses Presto to support operational reporting (batch and near real-time), ad hoc analyses, and its data pipeline. Currently, Grab has 5+ clusters with 100+ instances in production on AWS and serves up to 30K queries per day while supporting more than 200 internal data users. Feng Cheng and Yanyu Qu explain how Grab operationalizes Presto in the cloud and share lessons learned along the way.
Cheng Feng is a data engineer at Grab, where he works on the big data platform, distributed computing, stream processing, and data science. Previously, he was a data scientist at the Lazada Group, working on Lazada’s tracker, customer segmentation and recommendation systems, and fraud detection.
Yanyu Qu is a data engineer on Grab’s data engineering team, where he works on Spark and Presto’s data gateway. Previously, he worked at FunPlus, App Annie, IBM, and Teradata.
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