Fast Data Architectures for Streaming Applications

Fast Data Architectures for Streaming Applications

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Why have stream-oriented data systems become so popular, when batch-oriented systems have served big data needs for many years? In this report, author Dean Wampler examines the rise of streaming systems for handling time-sensitive problems—such as detecting fraudulent financial activity as it happens. You’ll explore the characteristics of fast data architectures, along with several open source tools for implementing them.

Batch-mode processing isn’t going away, but exclusive use of these systems is now a competitive disadvantage. You’ll learn that, while fast data architectures are much harder to build, they represent the state of the art for dealing with mountains of data that require immediate attention.

  • Learn step-by-step how a basic fast data architecture works
  • Understand why event logs are the core abstraction for streaming architectures, while message queues are the core integration tool
  • Use methods for analyzing infinite data sets, where you don’t have all the data and never will
  • Take a tour of open source streaming engines, and discover which ones work best for different use cases
  • Get recommendations for making real-world streaming systems responsive, resilient, elastic, and message driven
  • Explore an example streaming application for the IoT: telemetry ingestion and anomaly detection for home automation systems

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Dean Wampler

Dean Wampler

Dean Wampler, Ph.D. is the Architect for Big Data Products and Services and a member of the office of the CTO at Lightbend (formerly Typesafe). He leads Lightbend's technical architecture for Fast Data using Spark, Kafka, Mesos, Akka and other tools. Dean has written books on Scala, Functional Programming, and Hive for O'Reilly. He is a Strata speaker and he speaks at and co-organizes many other industry conferences. He also organizes several Chicago-area user groups and he contributes to many open-source projects, including Apache Spark. Dean has a Ph.D. in Physics from the University of Washington.