June 06, 2024
June 05, 2024
Tinybird has joined the AWS ISV Accelerate Program
Simple, Efficient, and Robust Hash Tables for Join Processing
Simple, Efficient, and Robust Hash Tables for Join Processing
Hash tables are probably the most versatile data structures for data processing. For that reason, CedarDB depends on hash table to perform some of the most crucial parts of its query execution engine. Most prominently, CedarDB implements relational joins as hash joins. This blog post assumes you know what a hash join is. If not, the Wikipedia article has a short introduction into the topic for you. During the development of Umbra and now CedarDB, we rewrote our join hash table implementation several times. To share our latest design, TUM and CedarDB published a peer-reviewed scientific paper, which Altan will present at DaMoN'24 in Santiago de Chile next week.
SIGMOD Programming Contest Archive: Join Processing (2018)
Building BerkeleyDB: Introduction
Tinybird has joined the AWS ISV Accelerate Program
June 04, 2024
SELECT DISTINCT without SQL
SIGMOD Programming Contest Archive: Streaming N-Gram Filter (2017)
June 03, 2024
JWTs for API Endpoints now in public beta!
SIGMOD Programming Contest Archive: Social Network Graph Processing (2014)
SIGMOD Programming Contest Archive: Transaction Processing (2015)
SIGMOD Programming Contest Archive: Shortest Path (2016)
May 31, 2024
Why MySQL Replication Is Fast
Replication being slow—replication lag—is a common complaint, but MySQL replication is actually really fast. Let’s run a controlled experiment and peek inside the Performance Schema and binary logs to see why.