8 Commonly Used Scalable System Design Patterns

Ricky Ho in Scalable System Design Patterns has created a great list of scalability patterns along with very well done explanatory graphics. A summary of the patterns are:

1. Load Balancer - a dispatcher determines which worker instance will handle a request based on different policies.
2. Scatter and Gather - a dispatcher multicasts requests to all workers in a pool. Each worker will compute a local result and send it back to the dispatcher, who will consolidate them into a single response and then send back to the client.
3. Result Cache - a dispatcher will first lookup if the request has been made before and try to find the previous result to return, in order to save the actual execution.
4. Shared Space - all workers monitors information from the shared space and contributes partial knowledge back to the blackboard. The information is continuously enriched until a solution is reached.
5. Pipe and Filter - all workers connected by pipes across which data flows.
6. MapReduce -  targets batch jobs where disk I/O is the major bottleneck. It use a distributed file system so that disk I/O can be done in parallel.
7. Bulk Synchronous Parallel - a  lock-step execution across all workers, coordinated by a master.
8. Execution Orchestrator - an intelligent scheduler / orchestrator schedules ready-to-run tasks (based on a dependency graph) across a clusters of dumb workers.

Comments

[allan]

Good summary. I think there should be some examples for each pattern. MapReduce is the one for Point 2. Browser cache is the one for Point 3. I don't think MapReduce could be one pattern. Any other examples for these?