Actions and Detail Panel
Tech-Meetup: Espresso: LinkedIn’s Distributed Database.
Sat, April 23, 2016, 1:30 PM – 4:30 PM PDT
Time: 1:30PM ~ 4:00PM, 04/23/2016, Saturday
Location: 97 E Brokaw Rd, Suite 210, San Jose, CA 95112
1:30pm – 2:00pm: Reception and social time
2:00pm – 3:30pm: Talk and QA
3:30pm – 4:00pm: offline networking
Espresso is a document-oriented distributed data serving platform that has been built to address LinkedIn's requirements for a scalable, performant, source-of-truth primary store. It provides a hierarchical document model, transactional support for modications to related documents, real-time secondary indexing, on-the-fly schema evolution and provides a timeline consistent change capture stream.
Espresso has been serving as LinkedIn's online, distributed, fault-tolerant NoSQL database which currently powers approximately 30 LinkedIn applications including Member Profile, InMail (LinkedIn's member-to-member messaging system), portions of the Homepage and mobile applications, etc. Espresso has a large production footprint at LinkedIn with over a dozen clusters in use. It hosts some of the most heavily accessed and valuable datasets at LinkedIn serving millions of records per second at peak. It is the source of truth for hundreds of terabytes (not counting replicas) of data.
In this talk, our speaker will share the motivation and design principles involved in building Espresso, the data model and capabilities exposed to clients, details of the replication and secondary indexing implementation, etc.
Yun Sun is a Staff Engineer and technical lead of Espresso team within LinkedIn's Data Infra team. He has been one of the primary contributors in building and optimizing Espresso for over 5 years.