Distributed Systems
Distributed computing is a field of computer science that studies distributed systems. A distributed system is a system whose components are located on different networked computers, which then communicate and coordinate their actions by passing messages to each other. The components interact with each other in order to achieve a common goal. Three significant characteristics of distributed systems are: concurrency of components, lack of a global clock, and independent failure of components. Examples of distributed systems vary from SOA-based systems to massively multiplayer online games to peer-to-peer applications.
A computer program that runs within a distributed system is called a distributed program (and distributed programming is the process of writing such programs). There are many different types of implementations for the message passing mechanism, including pure HTTP, RPC-like connectors and message queues.
A goal or challenge pursued by some computer scientists and practitioners in distributed systems is location transparency; however, this goal has fallen out of favor in industry. As distributed systems are a different concept from conventional non-distributed systems, the differences, such as network partitions, partial system failures, and partial upgrades, cannot simply be "papered over" by attempts at "transparency" (see CAP theorem).
Source: https://en.wikipedia.org/wiki/Distributed_computing
Position on the Adoption Curve
Presentations about Distributed Systems
CockroachDB: Architecture of a Geo-Distributed SQL Database
High Performance Cooperative Distributed Systems in Adtech
AMA w/ Bryan Cantril
Interviews
CockroachDB: Architecture of a Geo-Distributed SQL Database
Could you tell me what the focus of your work today is?
I am VP of Engineering and CTO of Cockroach Labs. I am keeping the lights on for the engineering department at Cockroach Labs and making sure product development stays on track for CockroachDB. I've been involved in every aspect of CockroachDB and today engineering work is much more limited, focusing on specifics like the performance of our low level key-value storage, but that probably gets about 20% of my time, 80% is training the rest of the teams to functioning and working smoothly.
What's the motivation for your talk?
To give an architectural overview of the components that go into building this distributed SQL database. I want to talk about this from the base level, how we're doing replication, how our data is spread across the cluster and then step it up through the levels, how we do distributed transactions, some of the optimizations involved there, stepping up past the distributed transactional store up in the SQL, how the SQL execution works, how we map SQL data down onto key-value data and then that we have a cost-based SQL optimizer, how the SQL optimizer plays into a distributed SQL database.
