Spark : the definitive guide : big data processing made simple (eBook, 2018) [WorldCat.org]
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Spark : the definitive guide : big data processing made simple

Author: Bill Chambers; Matei Zaharia
Publisher: Sebastopol, CA : O'Reilly Media, [2018] ©2018
Edition/Format:   eBook : Document : English : First editionView all editions and formats
Summary:

Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new  Read more...

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Details

Genre/Form: Electronic books
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Bill Chambers; Matei Zaharia
ISBN: 9781491912300 1491912308 9781491912294 1491912294 9781491912201 1491912200 1491912219 9781491912218
OCLC Number: 988029368
Notes: Includes index.
Description: 1 online resource (xxvi, 576 pages) : illustrations
Contents: Part 1. Gentle overview of big data and Spark. What is Apache Spark? --
A gentle introduction to Spark --
A tour of Spark's toolset --
Part 2. Structured APIs : DataFrames, SQL, and datasets. Structured API overview --
Basic structured operations --
Working with different types of data --
Aggregations --
Joins --
Data sources --
Spark SQL --
Datasets --
Part 3. Low-level APIs. Resilient distributed datasets (RDDs) --
Advanced RDDs --
Distributed shared variables --
Part 4. Production applications. How Spark runs on a cluster --
Developint Spark applications --
Deploying Spark --
Monitoring and debugging --
Performance tuning --
Part 5. Streaming. Stream processing fundamentals --
Structured streaming basics --
Event-time and stateful processing --
Structured streaming in production --
Part 6. Advanced analytics and machine learning. Advanced analytics and machine learning overview --
Preprocessing and feature engineering --
Classification --
Regression --
Recommendation --
Unsupervised learning --
Graph analytics --
Deep learning --
Part 7. Ecosystem. Language specifics : Python (PySpark) and R (SparkR and sparklyr) --
Ecosystem and community.
Responsibility: Bill Chambers and Matei Zaharia.

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