automatic management of partitioned, replicated search services
Low-latency, high-throughput web services are typically achieved through partitioning, replication, and caching. Although these strategies and the general design of large-scale distributed search systems are well known, the academic literature provides surprisingly few details on deployment and operational considerations in production environments. In this paper, we address this gap by sharing the distributed search architecture that underlies Twitter user search, a service for discovering relevant accounts on the popular microblogging service. Our design makes use of the principle that eliminates the distinction between failure and other anticipated service disruptions: as a result, most operational scenarios share exactly the same code path. This simplicity leads to greater robustness and fault-tolerance. Another salient feature of our architecture is its exclusive reliance on open-source software components, which makes it easier for the community to learn from our experiences and replicate our findings.
robustness information retrieval failover distributed retrieval architectures configuration management