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SQL server big data clusters = data ...

Weissman, Benjamin.

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SQL server big data clusters = data virtualization, data lake, and AI platform /

Record Type:	Electronic resources : Monograph/item
Title/Author:	SQL server big data clusters/ by Benjamin Weissman, Enrico van de Laar.
Reminder of title:	data virtualization, data lake, and AI platform /
Author:	Weissman, Benjamin.
other author:	Laar, Enrico van de.
Published:	Berkeley, CA :Apress : : 2020.,
Description:	xvii, 260 p. :ill., digital ;24 cm.
[NT 15003449]:	1. What Are Big Data Clusters? -- 2. Big Data Cluster Architecture -- 3. Deployment of Big Data Clusters -- 4. Loading Data into Big Data Clusters -- 5. Querying Big Data Clusters through T-SQL -- 6. Working with Spark in Big Data Clusters -- 7. Machine Learning on Big Data Clusters -- 8. Create and Consume Big Data Cluster Apps -- 9. Maintenance of Big Data Clusters.
Contained By:	Springer eBooks
Subject:	Database management. -
Online resource:	https://doi.org/10.1007/978-1-4842-5985-6
ISBN:	9781484259856

SQL server big data clusters = data virtualization, data lake, and AI platform /
Weissman, Benjamin.

SQL server big data clustersdata virtualization, data lake, and AI platform /[electronic resource] :by Benjamin Weissman, Enrico van de Laar. - Second edition. - Berkeley, CA :Apress :2020. - xvii, 260 p. :ill., digital ;24 cm.

1. What Are Big Data Clusters? -- 2. Big Data Cluster Architecture -- 3. Deployment of Big Data Clusters -- 4. Loading Data into Big Data Clusters -- 5. Querying Big Data Clusters through T-SQL -- 6. Working with Spark in Big Data Clusters -- 7. Machine Learning on Big Data Clusters -- 8. Create and Consume Big Data Cluster Apps -- 9. Maintenance of Big Data Clusters.

Use this guide to one of SQL Server 2019's most impactful features-Big Data Clusters. You will learn about data virtualization and data lakes for this complete artificial intelligence (AI) and machine learning (ML) platform within the SQL Server database engine. You will know how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For example, you can stream large volumes of data from Apache Spark in real time while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL-taking advantage of skills you have honed for years-and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. You will: Install, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization.

ISBN: 9781484259856

Standard No.: 10.1007/978-1-4842-5985-6doiSubjects--Uniform Titles:

SQL server.
Subjects--Topical Terms:

527442
Database management.

LC Class. No.: QA76.9.D3 / W457 2020

Dewey Class. No.: 005.74

SQL server big data clusters = data virtualization, data lake, and AI platform /
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505 0 $a 1. What Are Big Data Clusters? -- 2. Big Data Cluster Architecture -- 3. Deployment of Big Data Clusters -- 4. Loading Data into Big Data Clusters -- 5. Querying Big Data Clusters through T-SQL -- 6. Working with Spark in Big Data Clusters -- 7. Machine Learning on Big Data Clusters -- 8. Create and Consume Big Data Cluster Apps -- 9. Maintenance of Big Data Clusters.
520 $a Use this guide to one of SQL Server 2019's most impactful features-Big Data Clusters. You will learn about data virtualization and data lakes for this complete artificial intelligence (AI) and machine learning (ML) platform within the SQL Server database engine. You will know how to use Big Data Clusters to combine large volumes of streaming data for analysis along with data stored in a traditional database. For example, you can stream large volumes of data from Apache Spark in real time while executing Transact-SQL queries to bring in relevant additional data from your corporate, SQL Server database. Filled with clear examples and use cases, this book provides everything necessary to get started working with Big Data Clusters in SQL Server 2019. You will learn about the architectural foundations that are made up from Kubernetes, Spark, HDFS, and SQL Server on Linux. You then are shown how to configure and deploy Big Data Clusters in on-premises environments or in the cloud. Next, you are taught about querying. You will learn to write queries in Transact-SQL-taking advantage of skills you have honed for years-and with those queries you will be able to examine and analyze data from a wide variety of sources such as Apache Spark. Through the theoretical foundation provided in this book and easy-to-follow example scripts and notebooks, you will be ready to use and unveil the full potential of SQL Server 2019: combining different types of data spread across widely disparate sources into a single view that is useful for business intelligence and machine learning analysis. You will: Install, manage, and troubleshoot Big Data Clusters in cloud or on-premise environments Analyze large volumes of data directly from SQL Server and/or Apache Spark Manage data stored in HDFS from SQL Server as if it were relational data Implement advanced analytics solutions through machine learning and AI Expose different data sources as a single logical source using data virtualization.
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