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On completion, yoüll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. Yoüll also become familiar with machine learning algorithms with real-time usage.
Understand the completearchitecture of Spark and its components
Integrate Apache Spark with Hive and Kafka
Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries
Work with different machine learning concepts and libraries using Spark's MLlib packages
On completion, yoüll have knowledge of the functional programming aspects of Scala, and hands-on expertise in various Spark components. Yoüll also become familiar with machine learning algorithms with real-time usage.
Understand the completearchitecture of Spark and its components
Integrate Apache Spark with Hive and Kafka
Use Spark SQL, DataFrames, and Datasets to process data using traditional SQL queries
Work with different machine learning concepts and libraries using Spark's MLlib packages
Subhashini Chellappan is a technology enthusiast with expertise in the big data and cloud space. She has rich experience in both academia and the software industry. Her areas of interest and expertise are centered on business intelligence, big data analytics and cloud computing.
Dharanitharan Ganesan is a senior analyst with five years of experience in IT. He has a high level of exposure and experience in big data - Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, statistical modelling and predictive analysis.
Contains extensive coverage of machine-learning algorithms with real-time code implementation using Spark MLib
Explains the SparkR real-time module with code implementation
Covers Spark Streaming and Spark Integration examples with other big data components such as Kafka
1. Scala - Functional Programming Aspects. - 2. Single & Multi-node cluster setup. - 3. Introduction to Apache Spark and Spark Core. - 4. Spark SQL, Dataframes & Datasets. - 5. Introduction to Spark Streaming. - 6. Spark Structured Streaming. - 7. Spark Streaming with Kafka. - 8. Spark Machine Learning Library. - 9. Working with SparkR. - 10. Spark - Real time use case.
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Datenkommunikation, Netze & Mailboxen |
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xvi
280 S. 303 s/w Illustr. 280 p. 303 illus. |
| ISBN-13: | 9781484236512 |
| ISBN-10: | 1484236513 |
| Sprache: | Englisch |
| Herstellernummer: | 978-1-4842-3651-2 |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Ganesan, Dharanitharan
Chellappan, Subhashini |
| Auflage: | First Edition |
| Hersteller: | APRESS |
| Verantwortliche Person für die EU: | APress in Springer Science + Business Media, Heidelberger Platz 3, D-14197 Berlin, juergen.hartmann@springer.com |
| Maße: | 254 x 178 x 17 mm |
| Von/Mit: | Dharanitharan Ganesan (u. a.) |
| Erscheinungsdatum: | 13.12.2018 |
| Gewicht: | 0,561 kg |
Subhashini Chellappan is a technology enthusiast with expertise in the big data and cloud space. She has rich experience in both academia and the software industry. Her areas of interest and expertise are centered on business intelligence, big data analytics and cloud computing.
Dharanitharan Ganesan is a senior analyst with five years of experience in IT. He has a high level of exposure and experience in big data - Apache Hadoop, Apache Spark and various Hadoop ecosystem components. He has a proven track record of improving efficiency and productivity through the automation of various routine and administrative functions in business intelligence and big data technologies. His areas of interest and expertise are centered on machine learning algorithms, statistical modelling and predictive analysis.
Contains extensive coverage of machine-learning algorithms with real-time code implementation using Spark MLib
Explains the SparkR real-time module with code implementation
Covers Spark Streaming and Spark Integration examples with other big data components such as Kafka
1. Scala - Functional Programming Aspects. - 2. Single & Multi-node cluster setup. - 3. Introduction to Apache Spark and Spark Core. - 4. Spark SQL, Dataframes & Datasets. - 5. Introduction to Spark Streaming. - 6. Spark Structured Streaming. - 7. Spark Streaming with Kafka. - 8. Spark Machine Learning Library. - 9. Working with SparkR. - 10. Spark - Real time use case.
| Erscheinungsjahr: | 2018 |
|---|---|
| Fachbereich: | Datenkommunikation, Netze & Mailboxen |
| Genre: | Importe, Informatik |
| Rubrik: | Naturwissenschaften & Technik |
| Medium: | Taschenbuch |
| Inhalt: |
xvi
280 S. 303 s/w Illustr. 280 p. 303 illus. |
| ISBN-13: | 9781484236512 |
| ISBN-10: | 1484236513 |
| Sprache: | Englisch |
| Herstellernummer: | 978-1-4842-3651-2 |
| Einband: | Kartoniert / Broschiert |
| Autor: |
Ganesan, Dharanitharan
Chellappan, Subhashini |
| Auflage: | First Edition |
| Hersteller: | APRESS |
| Verantwortliche Person für die EU: | APress in Springer Science + Business Media, Heidelberger Platz 3, D-14197 Berlin, juergen.hartmann@springer.com |
| Maße: | 254 x 178 x 17 mm |
| Von/Mit: | Dharanitharan Ganesan (u. a.) |
| Erscheinungsdatum: | 13.12.2018 |
| Gewicht: | 0,561 kg |
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