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Pro SQL Server Wait Statistics is a practical guide for analyzing and troubleshooting SQL Server performance using wait statistics. Whether you are new to wait statistics, or already familiar with them, this book will help you gain a deeper understanding on how wait statistics are generated and what they can mean for your SQL Server’s performance. Besides the most common wait types, Pro SQL Server Wait Statistics goes further into the more complex and performance threatening wait types. The different wait types are categorized by their area of impact, and include CPU, IO, Lock, and many more different wait type categories. Filled with clear examples, Pro SQL Server Wait Statistics helps you gain practical knowledge of why and how specific wait times increase or decrease, and how they impact your SQL Server’s performance.

Computer Science. --- Database Management. --- Computer science. --- Database management. --- Informatique --- Bases de données --- Gestion --- Computer Science --- Engineering & Applied Sciences --- SQL server. --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Microsoft SQL server --- Electronic data processing --- Informatics --- Science

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Pro SQL Server Wait Statistics is a practical guide for analyzing and troubleshooting SQL Server performance using wait statistics. Whether you are new to wait statistics, or already familiar with them, this book will help you gain a deeper understanding on how wait statistics are generated and what they can mean for your SQL Server’s performance. Besides the most common wait types, Pro SQL Server Wait Statistics goes further into the more complex and performance threatening wait types. The different wait types are categorized by their area of impact, and include CPU, IO, Lock, and many more different wait type categories. Filled with clear examples, Pro SQL Server Wait Statistics helps you gain practical knowledge of why and how specific wait times increase or decrease, and how they impact your SQL Server’s performance.

Information systems --- database management

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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.

SQL server. --- Microsoft SQL server --- Database management. --- Microsoft software. --- Microsoft .NET Framework. --- Big data. --- Database Management. --- Microsoft and .NET. --- Big Data. --- Data sets, Large --- Large data sets --- Data sets --- Computer software --- Data base management --- Data services (Database management) --- Database management services --- DBMS (Computer science) --- Generalized data management systems --- Services, Database management --- Systems, Database management --- Systems, Generalized database management --- Electronic data processing --- Microsoft.

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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.

Programming --- Computer architecture. Operating systems --- Information systems --- computerprogramma's --- database management --- programmeertalen --- gegevensanalyse

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