Wide-Scale Data Stream Management

This paper describes Mortar, a distributed stream processing platform for building very large queries across federated systems (enterprises, grids, datacenters, testbeds). Nodes in such systems can be queried for distributed debugging, application control and provisioning, anomaly detection, and measurement. We address the primary challenges of managing continuous queries that have thousands of wide-area sources that may periodically be down, disconnected, or overloaded, e.g., multiple data centers filled with cheap PCs, Internet testbeds such as Planetlab, or country-wide sensor installations. Mortar presents a clean-slate design for best-effort innetwork processing. For each query, it builds multiple, static overlays and leverages the union of overlay paths to provide resilient query installation and data routing. Further, a unique data management scheme mitigates the impact of clock skew on distributed stream processing, reducing result latency by a factor of 8, and allows users to specify custom in-network operators that transparently benefit from multipath routing. When compared to a contemporary distributed snapshot querying substrate, Mortar uses a fifth of the bandwidth while providing increased query resolution, responsiveness, and accuracy during failures.