Mastering PostgreSQL 9.6. A comprehensive guide for PostgreSQL 9.6 developers and administrators

Hans-Jürgen Schönig

PostgreSQL is an open source database used for handling large datasets (Big Data) and as a JSON document database. It also has applications in the software and web domains. This book will enable you to build better PostgreSQL applications and administer databases more efficiently.We begin by explaining the advanced database design concepts in PostgreSQL 9.6, along with indexing and query optimization. You will also see how to work with event triggers and perform concurrent transactions and table partitioning, along with exploring SQL and server tuning. We will walk you through implementing advanced administrative tasks such as server maintenance and monitoring, replication, recovery and high availability, and much more. You will understand the common and not-so-common troubleshooting problems and how you can overcome them.By the end of this book, you will have an expert-level command of the advanced database functionalities and will be able to implement advanced administrative tasks with PostgreSQL.

Learning PySpark. Click here to enter text

Tomasz Drabas, Denny Lee

Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark. You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command. By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.

Learning Docker. Build, ship, and scale faster - Second Edition

Vinod Singh, Pethuru Raj, Jeeva S. Chelladhurai

Docker is an open source containerization engine that offers a simple and faster way for developing and running software. Docker containers wrap software in a complete filesystem that contains everything it needs to run, enabling any application to be run anywhere – this flexibily and portabily means that you can run apps in the cloud, on virtual machines, or on dedicated servers.This book will give you a tour of the new features of Docker and help you get started with Docker by building and deploying a simple application. It will walk you through the commands required to manage Docker images and containers. You’ll be shown how to download new images, run containers, list the containers running on the Docker host, and kill them. You’ll learn how to leverage Docker’s volumes feature to share data between the Docker host and its containers – this data management feature is also useful for persistent data. This book also covers how to orchestrate containers using Docker compose, debug containers, and secure containers using the AppArmor and SELinux security modules.

R Statistics Cookbook. Over 100 recipes for performing complex statistical operations with R 3.5

Francisco Juretig

R is a popular programming language for developing statistical software. This book will be a useful guide to solving common and not-so-common challenges in statistics. With this book, you'll be equipped to confidently perform essential statistical procedures across your organization with the help of cutting-edge statistical tools.You'll start by implementing data modeling, data analysis, and machine learning to solve real-world problems. You'll then understand how to work with nonparametric methods, mixed effects models, and hidden Markov models. This book contains recipes that will guide you in performing univariate and multivariate hypothesis tests, several regression techniques, and using robust techniques to minimize the impact of outliers in data.You'll also learn how to use the caret package for performing machine learning in R. Furthermore, this book will help you understand how to interpret charts and plots to get insights for better decision making.By the end of this book, you will be able to apply your skills to statistical computations using R 3.5. You will also become well-versed with a wide array of statistical techniques in R that are extensively used in the data science industry.

Hands-On Penetration Testing with Kali NetHunter. Spy on and protect vulnerable ecosystems using the power of Kali Linux for pentesting on the go

Glen D. Singh, Sean-Philip Oriyano

Kali NetHunter is a version of the popular and powerful Kali Linux pentesting platform, designed to be installed on mobile devices. Hands-On Penetration Testing with Kali NetHunter will teach you the components of NetHunter and how to install the software. You’ll also learn about the different tools included and how to optimize and use a package, obtain desired results, perform tests, and make your environment more secure. Starting with an introduction to Kali NetHunter, you will delve into different phases of the pentesting process. This book will show you how to build your penetration testing environment and set up your lab. You will gain insight into gathering intellectual data, exploiting vulnerable areas, and gaining control over target systems. As you progress through the book, you will explore the NetHunter tools available for exploiting wired and wireless devices. You will work through new ways to deploy existing tools designed to reduce the chances of detection. In the concluding chapters, you will discover tips and best practices for integrating security hardening into your Android ecosystem. By the end of this book, you will have learned to successfully use a mobile penetration testing device based on Kali NetHunter and Android to accomplish the same tasks you would traditionally, but in a smaller and more mobile form factor.

Machine Learning Algorithms. A reference guide to popular algorithms for data science and machine learning

Giuseppe Bonaccorso

In this book, you will learn all the important machine learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. The algorithms that are covered in this book are linear regression, logistic regression, SVM, naïve Bayes, k-means, random forest, TensorFlow and feature engineering.In this book, you will how to use these algorithms to resolve your problems, and how they work. This book will also introduce you to natural language processing and recommendation systems, which help you to run multiple algorithms simultaneously.On completion of the book, you will know how to pick the right machine learning algorithm for clustering, classification, or regression for your problem

Learning Apache Apex. Real-time streaming applications with Apex

Thomas Weise, Munagala V. Ramanath, David Yan, Kenneth Knowles

Apache Apex is a next-generation stream processing framework designed to operate on data at large scale, with minimum latency, maximum reliability, and strict correctness guarantees.Half of the book consists of Apex applications, showing you key aspects of data processing pipelines such as connectors for sources and sinks, and common data transformations. The other half of the book is evenly split into explaining the Apex framework, and tuning, testing, and scaling Apex applications.Much of our economic world depends on growing streams of data, such as social media feeds, financial records, data from mobile devices, sensors and machines (the Internet of Things - IoT). The projects in the book show how to process such streams to gain valuable, timely, and actionable insights. Traditional use cases, such as ETL, that currently consume a significant chunk of data engineering resources are also covered.The final chapter shows you future possibilities emerging in the streaming space, and how Apache Apex can contribute to it.

Mastering C++ Programming. Modern C++ 17 at your fingertips

Jeganathan Swaminathan

C++ ? ?has ? ?come ? ?a ? ?long ? ?way ? ?and ? ?has ? ?now ? ?been ? ?adopted ? ?in ? ?several ? ?contexts. Its ? ?key ? ?strengths ? ?are ? ?its ? ?software ? ?infrastructure ? ?and ? ?resource-constrained applications. ? ?The ?C++ ? ?17 ? ?release ? ?will ? ?change ? ?the ? ?way ? ?developers ? ?write code, ? ?and ? ?this ? ?book ? ?will ? ?help ?you ? ?master ? ?your ? ?developing ? ?skills ? ?with ? ?C++. With ? ?real-world, ? ?practical ? ?examples ? ?explaining ? ?each ? ?concept, ? ?the ? ?book ? ?will begin ? ?by ? ?introducing ? ?you ? ?to ? ?the ? ?latest ? ?features ? ?in ? ?C++ ? ?17. ? ?It ? ?encourages clean ? ?code ? ?practices ? ?in ? ?C++ ? ?in ? ?general, ? ?and ? ?demonstrates ? ?the ? ?GUI app-development ? ?options ? ?in ? ?C++. ? ?You’ll ? ?get ? ?tips ? ?on ? ?avoiding ? ?memory ? ?leaks using ? ?smart-pointers. ? ?Next, ? ?you’ll ? ?see ? ?how ? ?multi-threaded ?programming can ? ?help ? ?you ? ?achieve ? ?concurrency ? ?in ? ?your ? ?applications. Moving ? ?on, ? ?you’ll ? ?get ? ?an ? ?in-depth ? ?understanding ? ?of ? ?the ? ?C++ ? ?Standard Template ? ?Library. ? ?We ? ?show ? ?you ? ?the ? ?concepts ? ?of ? ?implementing ? ?TDD ? ?and BDD ? ?in ? ?your ? ?C++ ? ?programs, ? ?and ? ?explore ? ?template-based ? ?generic programming, ? ?giving ? ?you ? ?the ? ?expertise ? ?to ? ?build ? ?powerful ? ?applications. Finally, ? ?we’ll ? ?round ? ?up ? ?with ? ?debugging ? ?techniques ? ?and ? ?best ? ?practices.By ? ?the ? ?end ? ?of ? ?the ? ?book, ? ?you’ll ? ?have ? ?an ? ?in-depth ? ?understanding ? ?of ? ?the language ? ?and ? ?its ? ?various ? ?facets.