Spinning Fast Iterative Dataflows

Spinning Fast Iterative Dataflows - Ewen et al. 2012 Last week we saw how Naiad combines low-latency stream processing with iterative computation, and yesterday we looked in more detail at the Differential Dataflow model for incremental processing (needed for low-latency). The Apache Flink project also combines low-latency stream processing with support for incremental, iterative computation. ... Continue Reading

Differential Dataflow

Differential Dataflow - McSherry et al. 2013 The ability to perform complex analyses on [datasets that are constantly being updated] is very valuable; for example, each tweet published on the Twitter social network may supply new information about the community structure of the service’s users, which could be immediately exploited for real-time recommendation services or ... Continue Reading

Heracles: Improving Resource Efficiency at Scale

Heracles: Improving Resource Efficiency at Scale - Lo et al. 2015 Until recently, scaling from Moore’s law provided higher compute per dollar with every server generation, allowing datacenters to scale without raising the cost. However, with several imminent challenges in technology scaling, alternate approaches are needed. Those approaches involve increasing server utilization, which is still ... Continue Reading

Naiad: A Timely Dataflow System

Naiad: A Timely Dataflow System - Murray et al. 2013 Many data processing tasks require low-latency interactive access to results, iterative sub-computations, and consistent intermediate outputs so that sub-computations can be nested and composed. (For example, an) application that performs iterative processing on a real-time data stream, and supports interactive queries on a fresh, consistent ... Continue Reading

Detecting Termination of Distributed Computations Using Markers

Detecting Termination of Distributed Computations Using Markers - Misra 1983 There's an intriguing line in the Distributed GraphLab paper that caught my eye: "Termination is evaluated using distributed consensus algorithm described in [Ref]." Today's choice is the paper by Misra in 1983 that describes this distributed termination detection algorithm. The solution is similar in spirit ... Continue Reading

Scalability! But at what COST?

Scalability! But at what COST? - McSherry et al. 2015 With thanks to Felix Cuadrado, @felixcuadrado, for pointing this paper out to me via twitter. Scalability is highly prized, yet it can be a misleading metric when studied in isolation. McSherry et al. study the COST of distributed systems: the Configuration that Outperforms a Single ... Continue Reading