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Spark : Big Data Processing Made Simple.

Author: Bill Chambers; Matei Zaharia
Publisher: Sebastopol : O'Reilly Media, Incorporated, 2018.
Edition/Format:   eBook : Document : English
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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Genre/Form: Electronic books
Additional Physical Format: Print version:
Chambers, Bill.
Spark: the Definitive Guide.
Sebastopol : O'Reilly Media, Incorporated, ©2018
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Bill Chambers; Matei Zaharia
ISBN: 9781491912300 1491912308
OCLC Number: 1023550875
Notes: Right Outer Joins.
Description: 1 online resource (603 pages)
Contents: Cover; Copyright; Table of Contents; Preface; About the Authors; Who This Book Is For; Conventions Used in This Book; Using Code Examples; Oâ#x80;#x99;Reilly Safari; How to Contact Us; Acknowledgments; Part I. Gentle Overview of Big Data and Spark; Chapter 1. What Is Apache Spark?; Apache Sparkâ#x80;#x99;s Philosophy; Context: The Big Data Problem; History of Spark; The Present and Future of Spark; Running Spark; Downloading Spark Locally; Launching Sparkâ#x80;#x99;s Interactive Consoles; Running Spark in the Cloud; Data Used in This Book; Chapter 2. A Gentle Introduction to Spark; Sparkâ#x80;#x99;s Basic Architecture. Spark ApplicationsSparkâ#x80;#x99;s Language APIs; Sparkâ#x80;#x99;s APIs; Starting Spark; The SparkSession; DataFrames; Partitions; Transformations; Lazy Evaluation; Actions; Spark UI; An End-to-End Example; DataFrames and SQL; Conclusion; Chapter 3. A Tour of Sparkâ#x80;#x99;s Toolset; Running Production Applications; Datasets: Type-Safe Structured APIs; Structured Streaming; Machine Learning and Advanced Analytics; Lower-Level APIs; SparkR; Sparkâ#x80;#x99;s Ecosystem and Packages; Conclusion; Part II. Structured APIsâ#x80;#x94;DataFrames, SQL, and Datasets; Chapter 4. Structured API Overview; DataFrames and Datasets; Schemas. Overview of Structured Spark TypesDataFrames Versus Datasets; Columns; Rows; Spark Types; Overview of Structured API Execution; Logical Planning; Physical Planning; Execution; Conclusion; Chapter 5. Basic Structured Operations; Schemas; Columns and Expressions; Columns; Expressions; Records and Rows; Creating Rows; DataFrame Transformations; Creating DataFrames; select and selectExpr; Converting to Spark Types (Literals); Adding Columns; Renaming Columns; Reserved Characters and Keywords; Case Sensitivity; Removing Columns; Changing a Columnâ#x80;#x99;s Type (cast); Filtering Rows. Getting Unique RowsRandom Samples; Random Splits; Concatenating and Appending Rows (Union); Sorting Rows; Limit; Repartition and Coalesce; Collecting Rows to the Driver; Conclusion; Chapter 6. Working with Different Types of Data; Where to Look for APIs; Converting to Spark Types; Working with Booleans; Working with Numbers; Working with Strings; Regular Expressions; Working with Dates and Timestamps; Working with Nulls in Data; Coalesce; ifnull, nullIf, nvl, and nvl2; drop; fill; replace; Ordering; Working with Complex Types; Structs; Arrays; split; Array Length; array_contains; explode. MapsWorking with JSON; User-Defined Functions; Conclusion; Chapter 7. Aggregations; Aggregation Functions; count; countDistinct; approx_count_distinct; first and last; min and max; sum; sumDistinct; avg; Variance and Standard Deviation; skewness and kurtosis; Covariance and Correlation; Aggregating to Complex Types; Grouping; Grouping with Expressions; Grouping with Maps; Window Functions; Grouping Sets; Rollups; Cube; Grouping Metadata; Pivot; User-Defined Aggregation Functions; Conclusion; Chapter 8. Joins; Join Expressions; Join Types; Inner Joins; Outer Joins; Left Outer Joins.

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