Repair is one of several anti-entropy mechanisms in Scylla. It is used to synchronize data across replicas. In this post, we introduce a new repair algorithm coming with Scylla Open Source 3.1 that improves performance by operating at the row-level, rather than across entire partitions.
“Now, here, you see, it takes all the running you can do, to keep in the same place. If you want to get somewhere else, you must run at least twice as fast as that!” — The Red Queen to Alice, Alice Through the Looking Glass In the world of Big Data, if you are not constantly evolving you are already falling behind. This is at the heart of the Red Queen syndrome, which was first applied to the evolution of natural systems. It applies just as much to the evolution of technology. ‘Now! Now!’ cried the Queen. ‘Faster! Faster!’ […]
This blog post is based on a talk I gave last month at the third annual Scylla Summit in San Francisco. It explains how Scylla ensures that ingestion of data proceeds as quickly as possible, but not quicker. It looks into the existing flow-control mechanism for tables without materialized views, and into the new mechanism for tables with materialized views, which is introduced in Scylla Open Source 3.0. Introduction In this post we look into ingestion of data into a Scylla cluster. What happens when we make a large volume of update (write) requests? We would like the ingestion to […]