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Uncover the power of MySQL 8 for Big Data About This Book Combine the powers of MySQL and Hadoop to build a solid Big Data solution for your organization Integrate MySQL with different NoSQL APIs and Big Data tools such as Apache Sqoop A comprehensive guide with practical examples on building a high performance Big Data pipeline with MySQL Who This Book Is For This book is intended for MySQL database administrators and Big Data professionals looking to integrate MySQL 8 and Hadoop to implement a high performance Big Data solution. Some previous experience with MySQL will be helpful, although the book will highlight the newer features introduced in MySQL 8. What You Will Learn Explore the features of MySQL 8 and how they can be leveraged to handle Big Data Unlock the new features of MySQL 8 for managing structured and unstructured Big Data Integrate MySQL 8 and Hadoop for efficient data processing Perform aggregation using MySQL 8 for optimum data utilization Explore different kinds of join and union in MySQL 8 to process Big Data efficiently Accelerate Big Data processing with Memcached Integrate MySQL with the NoSQL API Implement replication to build highly available solutions for Big Data In Detail With organizations handling large amounts of data on a regular basis, MySQL has become a popular solution to handle this structured Big Data. In this book, you will see how DBAs can use MySQL 8 to handle billions of records, and load and retrieve data with performance comparable or superior to commercial DB solutions with higher costs. Many organizations today depend on MySQL for their websites and a Big Data solution for their data archiving, storage, and analysis needs. However, integrating them can be challenging. This book will show you how to implement a successful Big Data strategy with Apache Hadoop and MySQL 8. It will cover real-time use case scenario to explain integration and achieve Big Data solutions using technologies such as Apache Hadoop, Apache Sqoop, and MySQL Applier. Also, the book includes case studies on Apache Sqoop and real-time event processing. By the end of this book, you will know how to efficiently use MySQL 8 to manage data for your Big Data applications. Style and approach Step by Step guide filled with real-world practical examples.
Design cost-efficient database solutions, scale enterprise operations and reduce overhead business costs with MySQL Key FeaturesExplore the new and advanced features of MySQL 8.0Use advanced techniques to optimize MySQL performanceCreate MySQL-based applications for your enterprise with the help of practical examplesBook Description Advanced MySQL 8 teaches you to enhance your existing database infrastructure and build various tools to improve your enterprise applications and overall website performance. The book starts with the new and exciting MySQL 8.0 features and how to utilize them for maximum efficiency. As you make your way through the chapters, you will learn to optimize MySQL performance using indexes and advanced data query techniques for large queries. You will also discover MySQL Server 8.0 settings and work with the MySQL data dictionary to boost the performance of your database. In the concluding chapters, you will cover MySQL 8.0 Group Replication, which will enable you to create elastic, highly available, and fault-tolerant replication topologies. You will also explore backup and recovery techniques for your databases and understand important tips and tricks to help your critical data reach its full potential. By the end of this book, you’ll have learned about new MySQL 8.0 security features that allow a database administrator (DBA) to simplify user management and increase the security of their multi-user environments. What you will learnExplore new and exciting features of MySQL 8.0Analyze and optimize large MySQL queriesUnderstand MySQL Server 8.0 settingsMaster the deployment of Group Replication and use it in an InnoDB clusterMonitor large distributed databasesDiscover different types of backups and recovery methods for your databasesExplore tips to help your critical data reach its full potentialWho this book is for Advanced MySQL 8 is for database administrators, data architects, and database developers who want to dive deeper into building advanced database applications in the MySQL environment.
Step by step guide to monitor, manage, and secure your database engine Key Features Your companion to master all the administration-related tasks in MySQL 8 Ensure high performance and high availability of your MySQL solution using effective replication and backup techniques A comprehensive guide to performing query optimization, security and a whole host of other administrative tasks in MySQL 8 Book Description 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 learn Understanding different MySQL 8 data types based on type of contents and storage requirements Best practices for optimal use of features in MySQL 8 Explore globalization configuration and caching techniques to improve performance Create custom storage engine as per system requirements Learn various ways of index implementation for flash memory storages Configure and implement replication along with approaches to use replication as solution Understand how to make your MySQL 8 solution highly available Troubleshoot common issues and identify error codes while using MySQL 8 Who 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.
Build next-generation Artificial Intelligence systems with Java Key Features Implement AI techniques to build smart applications using Deeplearning4j Perform big data analytics to derive quality insights using Spark MLlib Create self-learning systems using neural networks, NLP, and reinforcement learning Book Description In this age of big data, companies have larger amount of consumer data than ever before, far more than what the current technologies can ever hope to keep up with. However, Artificial Intelligence closes the gap by moving past human limitations in order to analyze data. With the help of Artificial Intelligence for big data, you will learn to use Machine Learning algorithms such as k-means, SVM, RBF, and regression to perform advanced data analysis. You will understand the current status of Machine and Deep Learning techniques to work on Genetic and Neuro-Fuzzy algorithms. In addition, you will explore how to develop Artificial Intelligence algorithms to learn from data, why they are necessary, and how they can help solve real-world problems. By the end of this book, you'll have learned how to implement various Artificial Intelligence algorithms for your big data systems and integrate them into your product offerings such as reinforcement learning, natural language processing, image recognition, genetic algorithms, and fuzzy logic systems. What you will learn Manage Artificial Intelligence techniques for big data with Java Build smart systems to analyze data for enhanced customer experience Learn to use Artificial Intelligence frameworks for big data Understand complex problems with algorithms and Neuro-Fuzzy systems Design stratagems to leverage data using Machine Learning process Apply Deep Learning techniques to prepare data for modeling Construct models that learn from data using open source tools Analyze big data problems using scalable Machine Learning algorithms Who this book is for This book is for you if you are a data scientist, big data professional, or novice who has basic knowledge of big data and wish to get proficiency in Artificial Intelligence techniques for big data. Some competence in mathematics is an added advantage in the field of elementary linear algebra and calculus.
This book constitutes the workshop proceedings of the 22nd International Conference on Database Systems for Advanced Applications, DASFAA 2017, held in Suzhou, China, in March 2017. The 32 full papers and 5 short papers presented were carefully selected and reviewed from 43 submissions to the four following workshops: the 4th International Workshop on Big Data Management and Service, BDMS 2017; the Second International Workshop on Big Data Quality Management, BDQM 2017; the 4th International Workshop on Semantic Computing and Personalization, SeCoP 2017; and the First International Workshop on Data Management and Mining on MOOCs, DMMOOC 2017.
How can you realize MySQL's full power? With High Performance MySQL, you'll learn advanced techniques for everything from setting service-level objectives to designing schemas, indexes, and queries to tuning your server, operating system, and hardware to achieve your platform's full potential. This guide also teaches database administrators safe and practical ways to scale applications through replication, load balancing, high availability, and failover. Updated to reflect recent advances in cloud- and self-hosted MySQL, InnoDB performance, and new features and tools, this revised edition helps you design a relational data platform that will scale with your business. You'll learn best practices for database security along with hard-earned lessons in both performance and database stability. Dive into MySQL's architecture, including key facts about its storage engines Learn how server configuration works with your hardware and deployment choices Make query performance part of your software delivery process Examine enhancements to MySQL's replication and high availability Compare different MySQL offerings in managed cloud environments Explore MySQL's full stack optimization from application-side configuration to server tuning Turn traditional database management tasks into automated processes
Uncover the power of MySQL 8 for Big DataAbout This Book* Combine the powers of MySQL and Hadoop to build a solid Big Data solution for your organization* Integrate MySQL with different NoSQL APIs and Big Data tools such as Apache Sqoop* A comprehensive guide with practical examples on building a high performance Big Data pipeline with MySQLWho This Book Is ForThis book is intended for MySQL database administrators and Big Data professionals looking to integrate MySQL 8 and Hadoop to implement a high performance Big Data solution. Some previous experience with MySQL will be helpful, although the book will highlight the newer features introduced in MySQL 8.What You Will Learn* Explore the features of MySQL 8 and how they can be leveraged to handle Big Data* Unlock the new features of MySQL 8 for managing structured and unstructured Big Data* Integrate MySQL 8 and Hadoop for efficient data processing* Perform aggregation using MySQL 8 for optimum data utilization* Explore different kinds of join and union in MySQL 8 to process Big Data efficiently* Accelerate Big Data processing with Memcached* Integrate MySQL with the NoSQL API* Implement replication to build highly available solutions for Big DataIn DetailWith organizations handling large amounts of data on a regular basis, MySQL has become a popular solution to handle this structured Big Data. In this book, you will see how DBAs can use MySQL 8 to handle billions of records, and load and retrieve data with performance comparable or superior to commercial DB solutions with higher costs.Many organizations today depend on MySQL for their websites and a Big Data solution for their data archiving, storage, and analysis needs. However, integrating them can be challenging. This book will show you how to implement a successful Big Data strategy with Apache Hadoop and MySQL 8. It will cover real-time use case scenario to explain integration and achieve Big Data solutions using technologies such as Apache Hadoop, Apache Sqoop, and MySQL Applier. Also, the book includes case studies on Apache Sqoop and real-time event processing.By the end of this book, you will know how to efficiently use MySQL 8 to manage data for your Big Data applications.Style and approachStep by Step guide filled with real-world practical examples.
Become a proficient NLP data scientist by developing deep learning models for NLP and extract valuable insights from structured and unstructured data Key FeaturesGet to grips with word embeddings, semantics, labeling, and high-level word representations using practical examplesLearn modern approaches to NLP and explore state-of-the-art NLP models using PyTorchImprove your NLP applications with innovative neural networks such as RNNs, LSTMs, and CNNsBook Description In the internet age, where an increasing volume of text data is generated daily from social media and other platforms, being able to make sense of that data is a crucial skill. With this book, you’ll learn how to extract valuable insights from text by building deep learning models for natural language processing (NLP) tasks. Starting by understanding how to install PyTorch and using CUDA to accelerate the processing speed, you’ll explore how the NLP architecture works with the help of practical examples. This PyTorch NLP book will guide you through core concepts such as word embeddings, CBOW, and tokenization in PyTorch. You’ll then learn techniques for processing textual data and see how deep learning can be used for NLP tasks. The book demonstrates how to implement deep learning and neural network architectures to build models that will allow you to classify and translate text and perform sentiment analysis. Finally, you’ll learn how to build advanced NLP models, such as conversational chatbots. By the end of this book, you’ll not only have understood the different NLP problems that can be solved using deep learning with PyTorch, but also be able to build models to solve them. What you will learnUse NLP techniques for understanding, processing, and generating textUnderstand PyTorch, its applications and how it can be used to build deep linguistic modelsExplore the wide variety of deep learning architectures for NLPDevelop the skills you need to process and represent both structured and unstructured NLP dataBecome well-versed with state-of-the-art technologies and exciting new developments in the NLP domainCreate chatbots using attention-based neural networksWho this book is for This PyTorch book is for NLP developers, machine learning and deep learning developers, and anyone interested in building intelligent language applications using both traditional NLP approaches and deep learning architectures. If you’re looking to adopt modern NLP techniques and models for your development projects, this book is for you. Working knowledge of Python programming, along with basic working knowledge of NLP tasks, is required.
Overview of biomedical data science -- Spreadsheet tools and tips -- Biostatistics primer -- Data visualization -- Introduction to databases -- Big data -- Bioinformatics and precision medicine -- Programming languages for data analysis -- Machine learning -- Artificial intelligence -- Biomedical data science resources -- Appendix A: Glossary -- Appendix B: Using data.world -- Appendix C: Chapter exercises.
This book provides an overview of the resources and research projects that are bringing Big Data and High Performance Computing (HPC) on converging tracks. It demystifies Big Data and HPC for the reader by covering the primary resources, middleware, applications, and tools that enable the usage of HPC platforms for Big Data management and processing.Through interesting use-cases from traditional and non-traditional HPC domains, the book highlights the most critical challenges related to Big Data processing and management, and shows ways to mitigate them using HPC resources. Unlike most books on Big Data, it covers a variety of alternatives to Hadoop, and explains the differences between HPC platforms and Hadoop.Written by professionals and researchers in a range of departments and fields, this book is designed for anyone studying Big Data and its future directions. Those studying HPC will also find the content valuable.