Hands-on Data Virtualization with Polybase

Length: 496 pages
Edition: 1
Language: English
Publisher: BPB Publications
Publication Date: 2021-04-05
ISBN-10: 9390684412
ISBN-13: 9789390684410
Sales Rank: #0 (See Top 100 Books)

Run queries and analysis on big data clusters across relational and non relational databases

Key Features
● Connect to Hadoop, Azure, Spark, Oracle, Teradata, Cassandra, MongoDB, CosmosDB, MySQL, PostgreSQL, MariaDB, and SAP HANA.
● Numerous techniques on how to query data and troubleshoot Polybase for better data analytics.
● Exclusive coverage on Azure Synapse Analytics and building Big Data clusters.

Description
This book brings exciting coverage on establishing and managing data virtualization using polybase. This book teaches how to configure polybase on almost all relational and nonrelational databases. You will learn to set up the test environment for any tool or software instantly without hassle. You will practice how to design and build some of the high performing data warehousing solutions and that too in a few minutes of time.

You will almost become an expert in connecting to all databases including hadoop, cassandra, MySQL, PostgreSQL, MariaDB and Oracle database. This book also brings exclusive coverage on how to build data clusters on Azure and using Azure Synapse Analytics. By the end of this book, you just don’t administer the polybase for managing big data clusters but rather you learn to optimize and boost the performance for enabling data analytics and ease of data accessibility.

What you will learn
● Learn to configure Polybase and process Transact SQL queries with ease.
● Create a Docker container with SQL Server 2019 on Windows and Polybase.
● Establish SQL Server instance with any other software or tool using Polybase.
● Connect with Cassandra, MongoDB, MySQL, PostgreSQL, MariaDB, and IBM DB2.

Who this book is for
This book is for database developers and administrators familiar with the SQL language and command prompt. Managers and decision-makers will also find this book useful. No prior knowledge of any other technology or language is required.

Table of Contents
1. What is Data Virtualization (Polybase)
2. History of Polybase
3. Polybase current state
4. Differences with other technologies
5. Usage
6. Future
7. SQL Server
8. Hadoop Cloudera and Hortonworks
9. Windows Azure Storage Blob
10. Spark
11. From Azure Synapse Analytics
12. From Big Data Clusters
13. Oracle
14. Teradata
15. Cassandra
16. MongoDB
17. CosmosDB
18. MySQL
19. PostgreSQL
20. MariaDB
21. SAP HANA
22. IBM DB2
23. Excel

About the Authors
Pablo Echeverria is a talented database and software developer. He tuned long-running queries in Oracle and SQL achieving an execution time of under one-second, reducing resource usage up to 10%, and streamlined client processes, reducing work time by 50%. He is a critical thinker who focuses on implementation and testing. He loves learning and connecting new technologies.

LinkedIn profile: https://www.linkedin.com/in/pablo-echeverria/
Blog Link: https://www.sqlservercentral.com/author/pabechevb

Cover Page
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Errata
Table of Contents
1. Data Virtualization
    Structure
    Objectives
    Filtering the information
    Link relational data with storage/file system data
    What you would have to do without data virtualization
    How data virtualization simplifies querying external data
    How learning PolyBase can help you irrespective of your role
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
2. History of PolyBase
    Structure
    Objectives
    The data warehousing market
    November 2010, the basis: Parallel Data Warehouse (PDW)
    November 2012: PolyBase official announcement at the SQL PASS session
    July 12, 2013: PDW 2012 (v2) release
    May 1, 2014: PDW v2 AU1 also known as Analytics Platform System (APS)
    Other APS AU releases (2, 3, 4, and 5)
    SQL Server 2016
    SQL Server 2017
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
3. PolyBase Current State
    Structure
    Objectives
    Analytics Platform System and Azure Data Warehouse
    Azure Synapse Analytics
    Data Warehouse Fast Track deployment
    SQL Server 2019 Enterprise
    Big Data Clusters
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
4. Difference between PolyBase and Other Technologies
    Structure
    Objectives
    Reasoning
    OPENROWSET
    OPENDATASOURCE
    Linked servers
    Oracle EXTERNAL TABLE
    Oracle DATABASE LINK
    Oracle Data Service Integrator (ODSI)
    Teradata
    Other relational database management systems
    Any programming language/environment: Java, Scala, Python, R, .Net C#, PowerShell, etc.
    Azure Data Lake Storage (ADLS) U-SQL
    Power BI
    SQL Server Analysis Services/Azure Analysis Services
    Tibco Data Virtualization (TDV)
    Other data virtualization tools
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
5. Usage
    Structure
    Objectives
    Aging out or archiving tables
    Logging tables
    Programming language and environment
    Data Warehouse (DW) applications
    Data consuming programs: ETL, analysis, and reporting
    Other relational database management systems
    Places where you manifest your preferences, directly or indirectly
    Machine learning (ML) and artificial intelligence (AI)
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
6. Future of PolyBase
    Structure
    Objectives
    Support other file formats
    Query multiple Hadoop types at once
    Additional external sources
    Native support replacing Open DataBase Connectivity (ODBC)
    Execute commands directly on the external source
    Add an entire database instead of individual tables
    Query/write in parallel different external sources at the same time
    Independence from Java
    Other security protocols
    Large rows and large objects
    Tight control over results
    Table partitions to an external table
    Dashboard reports
    Get notified when the underlying data has changed
    Reuse data sets within the same plan and across nodes
    Index the external data
    Allow CRUD operations unsupported on the external source
    Automatically aggregate statistics about the external data
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
7. SQL Server
    Structure
    Objectives
    Download required media
    Installation considerations
    Installation process
    Configuration
    Test using a loopback source
    Read SQL Server data from a remote server
    Read SQL Server data using an intermediate server
    Serial vs. parallel loading
    Monitoring and troubleshooting
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
8. Hadoop Cloudera and Hortonworks
    Structure
    Objectives
    Prerequisites
    Hadoop
    SQL Server
    SequenceIQ Hadoop
    Hortonworks Data Platform (HDP) Sandbox
    Cloudbreak for Hortonworks Data Platform (HDP)
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
9. Azure Storage
    Structure
    Objectives
    Azure Storage
    SQL Server
    WASB
    Cloudbreak for Hortonworks Data Platform with Cloud Storage
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
10. Spark
    Structure
    Objectives
    Prerequisites
    Spark
    SQL Server
    HDInsight
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
11. Azure Synapse Analytics
    Structure
    Objectives
    Azure Data Lake Store (ADLS) Gen1
    Azure Data Lake Store (ADLS) Gen2
    Azure Synapse Analytics (formerly SQL DW)
    Azure Synapse Analytics (workspaces)
    Cloudbreak for Hortonworks Data Platform (HDP)
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
12. Big Data Clusters
    Structure
    Objectives
    Prerequisites for creation of Big Data Clusters
    Manual creation of Big Data Clusters
    Creation of Big Data Clusters using Azure Data Studio
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
13. Oracle
    Structure
    Objectives
    SQL Server
    Oracle
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
14. Teradata
    Structure
    Objectives
    SQL Server
    Acronyms and definitions
    Teradata in Azure
    Teradata in Amazon Web Services (AWS)
    Teradata in a Virtual Machine
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
15. Cassandra
    Structure
    Objectives
    SQL Server
    Cassandra
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
16. MongoDB
    Structure
    Objectives
    SQL Server
    MongoDB
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
17. Cosmos DB
    Structure
    Objectives
    Introduction to Cosmos DB
    SQL Server
    Cosmos DB Emulator in a Docker container on Windows
    Azure Cosmos DB
    Conclusion
    Points to remember
    Multiple choice questions
        Answer 
    Questions 
18. MySQL
    Structure
    Objectives
    SQL Server
    MySQL
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
19. PostgreSQL
    Structure
    Objectives
    SQL Server
    PostgreSQL
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
20. MariaDB
    Structure
    Objectives
    SQL Server
    MariaDB
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
21. SAP HANA
    Structure
    Objectives
    SQL Server
    SAP HANA
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
22. IBM Db2
    Structure
    Objectives
    SQL Server
    IBM Db2
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
23. Excel
    Structure
    Objectives
    SQL Server
    Excel
    Conclusion
    Points to remember
    Multiple choice questions
        Answer
    Questions
Index