Ebook: Spark: the definitive guide: big data processing made simple
Author: Chambers William Andrew, Zaharia Matei
- Tags: Big data, COMPUTERS--Computer Literacy, COMPUTERS--Computer Science, COMPUTERS--Data Processing, COMPUTERS--Hardware--General, COMPUTERS--Information Technology, COMPUTERS--Machine Theory, COMPUTERS--Reference, Data mining, Information retrieval, Electronic books, Spark (Electronic resource : Apache Software Foundation), COMPUTERS -- Computer Literacy, COMPUTERS -- Computer Science, COMPUTERS -- Data Processing, COMPUTERS -- Hardware -- General, COMPUTERS -- Information Technology, COMPUTERS -- Machine Theory, CO
- Year: 2018
- Publisher: O'Reilly Media
- City: Sebastopol;CA
- Edition: First edition
- Language: English
- epub
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.
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