Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications - Image 1

£44.14

O'Reilly Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications

Name: Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications
Brand: O'Reilly
Price: 41.8 GBP
Availability: InStock

Data Storage & Management

Price History & Forecast

Last 84 days • 84 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 84 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £42 (52 days, 61.9%)

Price range: £42 - £44

Price levels: 2 different prices over 84 days

Description

Get started with Apache Flink, the open source framework that powers some of the world's largest stream processing applications. With this practical book, you'll explore the fundamental concepts of parallel stream processing and discover how this technology differs from traditional batch data processing. Longtime Apache Flink committers Fabian Hueske and Vasia Kalavri show you how to implement scalable streaming applications with Flink's DataStream API and continuously run and maintain these applications in operational environments. Stream processing is ideal for many use cases, including low-latency ETL, streaming analytics, and real-time dashboards as well as fraud detection, anomaly detection, and alerting. You can process continuous data of any kind, including user interactions, financial transactions, and IoT data, as soon as you generate them. Learn concepts and challenges of distributed stateful stream processing Explore Flink's system architecture, including its event-time processing mode and fault-tolerance model Understand the fundamentals and building blocks of the DataStream API, including its time-based and statefuloperators Read data from and write data to external systems with exactly-once consistency Deploy and configure Flink clusters Operate continuously running streaming applications

Key Features

New Store Stock

Product Specifications

Brand: O'Reilly
Format: paperback
ASIN: 149197429X
Category: Books > Subjects > Computing & Internet > Databases > Data Storage & Management
Domain: Amazon UK
Release Date: 23 April 2019
Listed Since: 27 February 2017

Barcode

No barcode data available

O'Reilly Stream Processing with Apache Flink: Fundamentals, Implementation, and Operation of Streaming Applications

Price History & Forecast

Price Distribution

Price Analysis

Description

Key Features

Product Specifications

Barcode

Similar Products You Might Like

Stream Processing with Apache Spark: Mastering Structured Streaming and Spark Streaming

Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing

Streaming Databases: Building Real-Time, User-Facing Solutions

Mastering Kafka Streams and ksqlDB: Building real-time data systems by example

Hands-on Guide to Apache Spark 3: Build Scalable Computing Engines for Batch and Stream Data Processing

Modern Data Engineering with Apache Spark: A Hands-On Guide for Building Mission-Critical Streaming Applications

Kafka - The Definitive Guide: Real-Time Data and Stream Processing at Scale

Fundamentals of Stream Processing: Application Design, Systems, and Analytics

Kafka Streams in Action: Event-Driven Applications and Microservices

CRC Press Parallel Computing Architectures and APIs Book

Beginning Apache Spark 3: With DataFrame, Spark SQL, Structured Streaming, and Spark Machine Learning Library

Spark – The Definitive Guide: Big data processing made simple

Learning Spark 2e: Lightning-Fast Data Analytics

Kafka Connect: Build Data Pipelines by Integrating Existing Systems

Learning Apache OpenWhisk: Developing Open Serverless Solutions

Apache Kafka in Action: From Basics to Production

Effective Kafka: A Hands-On Guide to Building Robust and Scalable Event-Driven Applications with Code Examples in Java

Delta Lake: The Definitive Guide: Modern Data Lakehouse Architectures with Data Lakes

Mapping Data Flows in Azure Data Factory: Building Scalable ETL Projects in the Microsoft Cloud

Big Data Analytics with Spark: A Practitioner's Guide to Using Spark for Large Scale Data Analysis

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

Stream Clustering: Unsupervised Machine Learning

The Definitive Guide to Azure Data Engineering: Modern ELT, DevOps, and Analytics on the Azure Cloud Platform

In-Memory Analytics with Apache Arrow: Perform fast and efficient data analytics on both flat and hierarchical structured data