Apache Spark 2: Data Processing and Real-Time Analytics: Master complex big data processing, stream analytics, and machine learning with Apache Spark
bBuild efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework/b h4Key Features/h4 ul liMaster the art of real-time big data processing and machine learning /li liExplore a wide range of use-cases to analyze large data /li liDisc...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Birmingham
Packt Publishing Limited
2018
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| Ausgabe: | 1 |
| Schlagworte: | |
| Zusammenfassung: | bBuild efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework/b h4Key Features/h4 ul liMaster the art of real-time big data processing and machine learning /li liExplore a wide range of use-cases to analyze large data /li liDiscover ways to optimize your work by using many features of Spark 2.x and Scala /li /ul h4Book Description/h4 Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: ul liMastering Apache Spark 2.x by Romeo Kienzler/li liScala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla/li liApache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook/li /ul h4What you will learn/h4 ulliGet to grips with all the features of Apache Spark 2.x /li liPerform highly optimized real-time big data processing /li liUse ML and DL techniques with Spark MLlib and third-party tools /li liAnalyze structured and unstructured data using SparkSQL and GraphX /li liUnderstand tuning, debugging, and monitoring of big data applications /li liBuild scalable and fault-tolerant streaming applications /li liDevelop scalable recommendation engines /li /ul h4Who this book is for/h4 If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. |
| Beschreibung: | 1 Online-Ressource (616 Seiten) |
| ISBN: | 9781789959918 |
Internformat
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| 520 | |a bBuild efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework/b h4Key Features/h4 ul liMaster the art of real-time big data processing and machine learning /li liExplore a wide range of use-cases to analyze large data /li liDiscover ways to optimize your work by using many features of Spark 2.x and Scala /li /ul h4Book Description/h4 Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. | ||
| 520 | |a You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: ul liMastering Apache Spark 2.x by Romeo Kienzler/li liScala and Spark for Big Data Analytics by Md. | ||
| 520 | |a Rezaul Karim, Sridhar Alla/li liApache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook/li /ul h4What you will learn/h4 ulliGet to grips with all the features of Apache Spark 2.x /li liPerform highly optimized real-time big data processing /li liUse ML and DL techniques with Spark MLlib and third-party tools /li liAnalyze structured and unstructured data using SparkSQL and GraphX /li liUnderstand tuning, debugging, and monitoring of big data applications /li liBuild scalable and fault-tolerant streaming applications /li liDevelop scalable recommendation engines /li /ul h4Who this book is for/h4 If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. | ||
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| id | DE-604.BV047070203 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T16:13:34Z |
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| isbn | 9781789959918 |
| language | English |
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| spelling | Kienzler, Romeo Verfasser aut Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark Kienzler, Romeo 1 Birmingham Packt Publishing Limited 2018 1 Online-Ressource (616 Seiten) txt rdacontent c rdamedia cr rdacarrier bBuild efficient data flow and machine learning programs with this flexible, multi-functional open-source cluster-computing framework/b h4Key Features/h4 ul liMaster the art of real-time big data processing and machine learning /li liExplore a wide range of use-cases to analyze large data /li liDiscover ways to optimize your work by using many features of Spark 2.x and Scala /li /ul h4Book Description/h4 Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. This Learning Path includes content from the following Packt products: ul liMastering Apache Spark 2.x by Romeo Kienzler/li liScala and Spark for Big Data Analytics by Md. Rezaul Karim, Sridhar Alla/li liApache Spark 2.x Machine Learning Cookbook by Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen MeiCookbook/li /ul h4What you will learn/h4 ulliGet to grips with all the features of Apache Spark 2.x /li liPerform highly optimized real-time big data processing /li liUse ML and DL techniques with Spark MLlib and third-party tools /li liAnalyze structured and unstructured data using SparkSQL and GraphX /li liUnderstand tuning, debugging, and monitoring of big data applications /li liBuild scalable and fault-tolerant streaming applications /li liDevelop scalable recommendation engines /li /ul h4Who this book is for/h4 If you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. COMPUTERS / Programming Languages / Python COMPUTERS / Data Modeling & Design Karim, Md. Rezaul Sonstige oth Alla, Sridhar Sonstige oth Amirghodsi, Siamak Sonstige oth |
| spellingShingle | Kienzler, Romeo Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark COMPUTERS / Programming Languages / Python COMPUTERS / Data Modeling & Design |
| title | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark |
| title_auth | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark |
| title_exact_search | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark |
| title_exact_search_txtP | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark |
| title_full | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark Kienzler, Romeo |
| title_fullStr | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark Kienzler, Romeo |
| title_full_unstemmed | Apache Spark 2: Data Processing and Real-Time Analytics Master complex big data processing, stream analytics, and machine learning with Apache Spark Kienzler, Romeo |
| title_short | Apache Spark 2: Data Processing and Real-Time Analytics |
| title_sort | apache spark 2 data processing and real time analytics master complex big data processing stream analytics and machine learning with apache spark |
| title_sub | Master complex big data processing, stream analytics, and machine learning with Apache Spark |
| topic | COMPUTERS / Programming Languages / Python COMPUTERS / Data Modeling & Design |
| topic_facet | COMPUTERS / Programming Languages / Python COMPUTERS / Data Modeling & Design |
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