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Mastering Apache Spark 2.x - Second Edition

You're reading from  Mastering Apache Spark 2.x - Second Edition

Product type Book
Published in Jul 2017
Publisher Packt
ISBN-13 9781786462749
Pages 354 pages
Edition 2nd Edition
Languages
Concepts

Table of Contents (21) Chapters

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
1. A First Taste and What’s New in Apache Spark V2 2. Apache Spark SQL 3. The Catalyst Optimizer 4. Project Tungsten 5. Apache Spark Streaming 6. Structured Streaming 7. Apache Spark MLlib 8. Apache SparkML 9. Apache SystemML 10. Deep Learning on Apache Spark with DeepLearning4j and H2O 11. Apache Spark GraphX 12. Apache Spark GraphFrames 13. Apache Spark with Jupyter Notebooks on IBM DataScience Experience 14. Apache Spark on Kubernetes

How to go from Unresolved Logical Execution Plan to Resolved Logical Execution Plan

The ULEP basically reflects the structure of an AST. So again, the AST is generated from the user's code implemented either on top of the relational API of DataFrames and Datasets or using SQL, or all three. This AST can be easily transformed into a ULEP. But, of course, a ULEP can't be executed. The first thing that is checked is if the referred relations exist in the catalog. This means all table names and fields expressed in the SQL statement or relational API have to exist. If the table (or relation) exists, the column names are verified. In addition, the column names that are referred to multiple times are given an alias in order to read them only once. This is already a first stage optimization taking place here. Finally, the data types of the columns are determined in order to check if the operations expressed on top of the columns are valid. So for example taking the sum of a string doesn't work and...

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