Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing - Image 1

£41.80

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

Name: Streaming Systems: The What, Where, When, and How of Large-Scale Data Processing
Brand: O'Reilly
Price: 41.8 GBP
Availability: InStock

Data Storage & Management

This is the usual price. Wait for it to drop, or tell us your number.

£42 today · usual range £0–£0 · best ever £38

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 579 days • 579 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 579 days • 7 price levels

Days at Price

Current Price

Price Analysis

Most common price: £41 (229 days, 39.6%)

Price range: £38 - £46

Price levels: 7 different prices over 579 days

Description

Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to work with streaming data in a conceptual and platform-agnostic way. Expanded from Tyler Akidau's popular blog posts "Streaming 101" and "Streaming 102", this book takes you from an introductory level to a nuanced understanding of the what, where, when, and how of processing real-time data streams. You'll also dive deep into watermarks and exactly-once processing with co-authors Slava Chernyak and Reuven Lax. You'll explore: How streaming and batch data processing patterns compare The core principles and concepts behind robust out-of-order data processing How watermarks track progress and completeness in infinite datasets How exactly-once data processing techniques ensure correctness How the concepts of streams and tables form the foundations of both batch and streaming data processing The practical motivations behind a powerful persistent state mechanism, driven by a real-world example How time-varying relations provide a link between stream processing and the world of SQL and relational algebra

Product Specifications

Brand: O'Reilly
Format: paperback
ASIN: 1491983876
Category: Books > Subjects > Computing & Internet > Databases > Data Storage & Management
Domain: Amazon UK
Release Date: 27 July 2018
Listed Since: 27 February 2017

Barcode

No barcode data available

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

This is the usual price. Wait for it to drop, or tell us your number.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

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

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

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

Data Engineering Design Patterns: Recipes for Solving the Most Common Data Engineering Problems

Delta Lake: Up and Running: Modern Data Lakehouse Architectures with Delta Lake

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

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

Beginning Azure Synapse Analytics: Transition from Data Warehouse to Data Lakehouse

Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Stream Clustering: Unsupervised Machine Learning

Big Data Science & Analytics: A Hands-On Approach

Data Engineering for Beginners (Tech Today)

Azure Data Factory by Example: Practical Implementation for Data Engineers

Trino: The Definitive Guide: SQL at Any Scale, on Any Storage, in Any Environment

Data Engineering for AI/ML Pipelines: A Comprehensive Guide to Building Scalable, Intelligent Data Workflows

Modern Data Architecture on Azure: Design Data-centric Solutions on Microsoft Azure

Learning and Operating Presto: Fast, Reliable SQL for Data Analytics and Lakehouses

Pro Oracle GoldenGate 23ai for the DBA: Powering the Foundation of Data Integration and AI

Knowledge Discovery from Data Streams (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Database Development and Management (Foundations of Database Design)

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

Data Management at Scale: Best Practices for Enterprise Architecture

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