Hyperledger Fabric empowers enterprises to scale out in an unprecedented way, allowing organizations to build and manage blockchain business networks. This quick start guide systematically takes you through distributed ledger technology, blockchain, and Hyperledger Fabric while also helping you understand the significance of Blockchain-as-a-Service (BaaS).
The book starts by explaining the blockchain and Hyperledger Fabric architectures. You'll then get to grips with the comprehensive five-step design strategy - explore, engage, experiment, experience, and influence. Next, you'll cover permissioned distributed autonomous organizations (pDAOs), along with the equation to quantify a blockchain solution for a given use case. As you progress, you'll learn how to model your blockchain business network by defining its assets, participants, transactions, and permissions with the help of examples. In the concluding chapters, you'll build on your knowledge as you explore Oracle Blockchain Platform (OBP) in depth and learn how to translate network topology on OBP.
By the end of this book, you will be well-versed with OBP and have developed the skills required for infrastructure setup, access control, adding chaincode to a business network, and exposing chaincode to a DApp using REST configuration.What you will learn
If you are a blockchain developer, blockchain architect or just a cloud developer looking to get hands-on with Oracle Blockchain Cloud Service, then this book is for you. Some familiarity with the basic concepts of blockchain will be helpful to get the most out of this book
MySQL is one of the most popular and widely used relational databases in the world today. The recently released version 8.0 brings along some major advancements in the way your MySQL solution can be administered. This handbook will be your companion to understand the newly introduced features in MySQL and how you can leverage them to design a high-performance MySQL solution for your organization.
This book starts with a brief introduction to the newly introduced features in MySQL 8, followed by quickly jumping onto the crucial administration topics that you will find useful in your day to day work. Topics such as migrating to MySQL 8, MySQL benchmarking, achieving high performance by implementing the indexing techniques, and optimizing your queries are covered in this book. You will also learn how to perform replication, scale your MySQL solution and implement effective security techniques. A special section on the common and not so common troubleshooting techniques for effective MySQL administration is also covered in this book.
By the end of this highly practical book, you will have all the knowledge you need to tackle any problem you might encounter while administering your MySQL solution.What you will learnUnderstanding different MySQL 8 data types based on type of contents and storage requirementsBest practices for optimal use of features in MySQL 8Explore globalization configuration and caching techniques to improve performanceCreate custom storage engine as per system requirementsLearn various ways of index implementation for flash memory storagesConfigure and implement replication along with approaches to use replication as solutionUnderstand how to make your MySQL 8 solution highly availableTroubleshoot common issues and identify error codes while using MySQL 8Who this book is for
This book is intended for MySQL administrators who are looking for a handy guide covering all the MySQL administration-related tasks. If you are a DBA looking to get started with MySQL administration, this book will also help you. Knowledge of the basic database concepts is required to get started with this book.
Apache Superset is a modern, open source, enterprise-ready business intelligence (BI) web application. With the help of this book, you will see how Superset integrates with popular databases like Postgres, Google BigQuery, Snowflake, and MySQL. You will learn to create real time data visualizations and dashboards on modern web browsers for your organization using Superset.
First, we look at the fundamentals of Superset, and then get it up and running. You'll go through the requisite installation, configuration, and deployment. Then, we will discuss different columnar data types, analytics, and the visualizations available. You'll also see the security tools available to the administrator to keep your data safe.
You will learn how to visualize relationships as graphs instead of coordinates on plain orthogonal axes. This will help you when you upload your own entity relationship dataset and analyze the dataset in new, different ways. You will also see how to analyze geographical regions by working with location data.
Finally, we cover a set of tutorials on dashboard designs frequently used by analysts, business intelligence professionals, and developers.What you will learnGet to grips with the fundamentals of data exploration using SupersetSet up a working instance of Superset on cloud services like Google Compute EngineIntegrate Superset with SQL databasesBuild dashboards with SupersetCalculate statistics in Superset for numerical, categorical, or text dataUnderstand visualization techniques, filtering, and grouping by aggregationManage user roles and permissions in SupersetWork with SQL LabWho this book is for
This book is for data analysts, BI professionals, and developers who want to learn Apache Superset. If you want to create interactive dashboards from SQL databases, this book is what you need. Working knowledge of Python will be an advantage but not necessary to understand this book.
This is the golden age of open source NoSQL databases. With enterprises having to work with large amounts of unstructured data and moving away from expensive monolithic architecture, the adoption of NoSQL databases is rapidly increasing. Being familiar with the popular NoSQL databases and knowing how to use them is a must for budding DBAs and developers.
This book introduces you to the different types of NoSQL databases and gets you started with seven of the most popular NoSQL databases used by enterprises today. We start off with a brief overview of what NoSQL databases are, followed by an explanation of why and when to use them. The book then covers the seven most popular databases in each of these categories: MongoDB, Amazon DynamoDB, Redis, HBase, Cassandra, InfluxDB, and Neo4j. The book doesn't go into too much detail about each database but teaches
you enough to get started with them.
By the end of this book, you will have a thorough understanding of the different NoSQL databases and their functionalities, empowering you to select and use the right
database according to your needs.What you will learnUnderstand how MongoDB provides high-performance, high-availability, and automatic scalingInteract with your Neo4j instances via database queries, Python scripts, and Java application codeGet familiar with common querying and programming methods to interact with RedisStudy the different types of problems Cassandra can solveWork with HBase components to support common operations such as creating tables and reading/writing dataDiscover data models and work with CRUD operations using DynamoDBDiscover what makes InfluxDB a great choice for working withtime-series dataWho this book is for
If you are a budding DBA or a developer who wants to get started with the fundamentals of NoSQL databases, this book is for you. Relational DBAs who want to get insights into the various offerings of popular NoSQL databases will also find this book to be very useful.
The Handbook of Research on Innovative Database Query Processing Techniques focuses on the growing topic of database query processing methods, technologies, and applications. Aimed at providing an all-inclusive reference source of technologies and practices in advanced database query systems, this book investigates various techniques, including database and XML queries, spatiotemporal data queries, big data queries, metadata queries, and applications of database query systems. This comprehensive handbook is a necessary resource for students, IT professionals, data analysts, and academicians interested in uncovering the latest methods for using queries as a means to extract information from databases.
This all-inclusive handbook includes the latest research on topics pertaining to information retrieval, data extraction, data management, design and development of database queries, and database and XM queries.
Transact-SQL (T-SQL) is Microsoft's proprietary extension to the SQL language that is used with Microsoft SQL Server and Azure SQL Database. This book will be a useful guide to learning the art of writing efficient T-SQL code in modern SQL Server versions, as well as the Azure SQL Database.
The book will get you started with query processing fundamentals to help you write powerful, performant T-SQL queries. You will then focus on query execution plans and learn how to leverage them for troubleshooting. In the later chapters, you will learn how to identify various T-SQL patterns and anti-patterns. This will help you analyze execution plans to gain insights into current performance, and determine whether or not a query is scalable. You will also learn to build diagnostic queries using dynamic management views (DMVs) and dynamic management functions (DMFs) to address various challenges in T-SQL execution. Next, you will study how to leverage the built-in tools of SQL Server to shorten the time taken to address query performance and scalability issues. In the concluding chapters, the book will guide you through implementing various features, such as Extended Events, Query Store, and Query Tuning Assistant using hands-on examples.
By the end of this book, you will have the skills to determine query performance bottlenecks, avoid pitfalls, and discover the anti-patterns in use.
Foreword by Conor Cunningham, Partner Architect – SQL Server and Azure SQL – MicrosoftWhat you will learnUse Query Store to understand and easily change query performanceRecognize and eliminate bottlenecks that lead to slow performanceDeploy quick fixes and long-term solutions to improve query performanceImplement best practices to minimize performance risk using T-SQLAchieve optimal performance by ensuring careful query and index designUse the latest performance optimization features in SQL Server 2017 and SQL Server 2019Protect query performance during upgrades to newer versions of SQL ServerWho this book is for
This book is for database administrators, database developers, data analysts, data scientists, and T-SQL practitioners who want to get started with writing T-SQL code and troubleshooting query performance issues, through the help of practical examples. Previous knowledge of T-SQL querying is not required to get started on this book.
In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications.Peer under the hood of the systems you already use, and learn how to use and operate them more effectivelyMake informed decisions by identifying the strengths and weaknesses of different toolsNavigate the trade-offs around consistency, scalability, fault tolerance, and complexityUnderstand the distributed systems research upon which modern databases are builtPeek behind the scenes of major online services, and learn from their architectures
Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the IPython shell and Jupyter notebook for exploratory computingLearn basic and advanced features in NumPy (Numerical Python)Get started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples