Your mission, should you decide to accept it, is the following: aggregate temperature values from a CSV file and group them by weather station name. There’s only one caveat: the file has one 1,000,000,000 rows!
This is the task of the “One Billion Row Challenge” which went viral within the Java community earlier this year. Come and join me for this talk where I’ll dive into some of the tricks employed by the fastest solutions for processing the challenge’s 13 GB input file within less than two seconds. Parallelization and efficient memory access, optimized parsing routines using SIMD and SWAR, as well as custom map implementations are just some of the topics which we are going to discuss.
I will also share some of the personal experiences and learnings which I made while running this challenge for and with the community.
Speaker
Gunnar Morling
Senior Staff Software Engineer @Decodableco
Gunnar Morling is a software engineer and open-source enthusiast by heart, currently working at Decodable on stream processing based on Apache Flink. In his prior role as a software engineer at Red Hat, he led the Debezium project, a distributed platform for change data capture. He is a Java Champion and has founded multiple open source projects such as JfrUnit, kcctl, and MapStruct. Gunnar is an avid blogger (morling.dev) and has spoken at a wide range of conferences like QCon, Java One, and Devoxx. He lives in Hamburg, Germany.
