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Grokking streaming systems, josh fischer, ning wang

680 грн -5% 650 грн

Описание

A friendly, framework-agnostic tutorial that will help you grok how streaming
systems work—and how to build your own! \n \nIn Grokking Streaming Systems you
will learn how to: \n \nImplement and troubleshoot streaming systems \nDesign
streaming systems for complex functionalities \nAssess parallelization
requirements \nSpot networking bottlenecks and resolve back pressure \nGroup
data for high-performance systems \nHandle delayed events in real-time systems
\n \nGrokking Streaming Systems is a simple guide to the complex concepts
behind streaming systems. This friendly and framework-agnostic tutorial
teaches you how to handle real-time events, and even design and build your own
streaming job that’s a perfect fit for your needs. Each new idea is carefully
explained with diagrams, clear examples, and fun dialogue between perplexed
personalities! \n \nAbout the technology \nStreaming systems minimize the time
between receiving and processing event data, so they can deliver responses in
real time. For applications in finance, security, and IoT where milliseconds
matter, streaming systems are a requirement. And streaming is hot! Skills on
platforms like Spark, Heron, and Kafka are in high demand. \n \nAbout the book
\nGrokking Streaming Systems introduces real-time event streaming applications
in clear, reader-friendly language. This engaging book illuminates core
concepts like data parallelization, event windows, and backpressure without
getting bogged down in framework-specific details. As you go, you’ll build
your own simple streaming tool from the ground up to make sure all the ideas
and techniques stick. The helpful and entertaining illustrations make
streaming systems come alive as you tackle relevant examples like real-time
credit card fraud detection and monitoring IoT services. \n \nWhat's inside \n
\nImplement and troubleshoot streaming systems \nDesign streaming systems for
complex functionalities \nSpot networking bottlenecks and resolve backpressure
\nGroup data for high-performance systems \n \nAbout the reader \nNo prior
experience with streaming systems is assumed. Examples in Java. \n \nAbout the
author \nJosh Fischer and Ning Wang are Apache Committers, and part of the
committee for the Apache Heron distributed stream processing engine.

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