A Cookbook with plenty of practical recipes for different uses of Storm.If you are a Java developer with basic knowledge of real-time processing and would like to learn Storm to process unbounded streams of data in real time, then this book is for you.
Learn to process massive real-time data streams using Storm and Python—no Java required! About This Book Learn to use Apache Storm and the Python Petrel library to build distributed applications that process large streams of data Explore sample applications in real-time and analyze them in the popular NoSQL databases MongoDB and Redis Discover how to apply software development best practices to improve performance, productivity, and quality in your Storm projects Who This Book Is For This book is intended for Python developers who want to benefit from Storm's real-time data processing capabilities. If you are new to Python, you'll benefit from the attention to key supporting tools and techniques such as automated testing, virtual environments, and logging. If you're an experienced Python developer, you'll appreciate the thorough and detailed examples What You Will Learn Install Storm and learn about the prerequisites Get to know the components of a Storm topology and how to control the flow of data between them Ingest Twitter data directly into Storm Use Storm with MongoDB and Redis Build topologies and run them in Storm Use an interactive graphical debugger to debug your topology as it's running in Storm Test your topology components outside of Storm Configure your topology using YAML In Detail Big data is a trending concept that everyone wants to learn about. With its ability to process all kinds of data in real time, Storm is an important addition to your big data “bag of tricks.” At the same time, Python is one of the fastest-growing programming languages today. It has become a top choice for both data science and everyday application development. Together, Storm and Python enable you to build and deploy real-time big data applications quickly and easily. You will begin with some basic command tutorials to set up storm and learn about its configurations in detail. You will then go through the requirement scenarios to create a Storm cluster. Next, you'll be provided with an overview of Petrel, followed by an example of Twitter topology and persistence using Redis and MongoDB. Finally, you will build a production-quality Storm topology using development best practices. Style and approach This book takes an easy-to-follow and a practical approach to help you understand all the concepts related to Storm and Python.
Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It allows developers to concurrently run the likes of Hadoop, Spark, Storm, and other applications on a dynamically shared pool of nodes. With Mesos, you have the power to manage a wide range of resources in a multi-tenant environment. Starting with the basics, this book will give you an insight into all the features that Mesos has to offer. You will first learn how to set up Mesos in various environments from data centers to the cloud. You will then learn how to implement self-managed Platform as a Service environment with Mesos using various service schedulers, such as Chronos, Aurora, and Marathon. You will then delve into the depths of Mesos fundamentals and learn how to build distributed applications using Mesos primitives. Finally, you will round things off by covering the operational aspects of Mesos including logging, monitoring, high availability, and recovery.
This book offers a collection of high-quality, peer-reviewed research papers presented at the International Conference on Intelligent Computing, Communication and Devices (ICCD 2017), discussing all dimensions of intelligent sciences – intelligent computing, intelligent communication, and intelligent devices. Intelligent computing addresses areas such as intelligent and distributed computing, intelligent grid and cloud computing, internet of things, soft computing and engineering applications, data mining and knowledge discovery, semantic and web technology, hybrid systems, agent computing, bioinformatics, and recommendation systems. Intelligent communication is concerned with communication and network technologies, such as mobile broadband and all optical networks that are the key to groundbreaking inventions of intelligent communication technologies. It includes communication hardware, software and networked intelligence, mobile technologies, machine-to-machine communication networks, speech and natural language processing, routing techniques and network analytics, wireless ad hoc and sensor networks, communications and information security, signal, image and video processing, network management, and traffic engineering. Lastly, intelligent devices are any equipment, instruments, or machines that have their own computing capability. As computing technology becomes more advanced and less expensive, it can be incorporated an increasing number of devices of all kinds. This area covers such as embedded systems, radiofrequency identification (RFID), radiofrequency microelectromechanical system (RF MEMS), very-large-scale integration (VLSI) design and electronic devices, analog and mixed-signal integrated circuit (IC) design and testing, microelectromechanical system (MEMS) and microsystems, solar cells and photonics, nanodevices, single electron and spintronics devices, space electronics, and intelligent robotics.
With more than 150 detailed recipes, this cookbook shows experienced Clojure developers how to solve a variety of programming tasks with this JVM language. The solutions cover everything from building dynamic websites and working with databases to network communication, cloud computing, and advanced testing strategies. And more than 60 of the world’s best Clojurians contributed recipes. Each recipe includes code that you can use right away, along with a discussion on how and why the solution works, so you can adapt these patterns, approaches, and techniques to situations not specifically covered in this cookbook. Master built-in primitive and composite data structures Create, develop and publish libraries, using the Leiningen tool Interact with the local computer that’s running your application Manage network communication protocols and libraries Use techniques for connecting to and using a variety of databases Build and maintain dynamic websites, using the Ring HTTP server library Tackle application tasks such as packaging, distributing, profiling, and logging Take on cloud computing and heavyweight distributed data crunching Dive into unit, integration, simulation, and property-based testing Clojure Cookbook is a collaborative project with contributions from some of the world’s best Clojurians, whose backgrounds range from aerospace to social media, banking to robotics, AI research to e-commerce.
If you are a Big Data enthusiast and wish to use Hadoop v2 to solve your problems, then this book is for you. This book is for Java programmers with little to moderate knowledge of Hadoop MapReduce. This is also a one-stop reference for developers and system admins who want to quickly get up to speed with using Hadoop v2. It would be helpful to have a basic knowledge of software development using Java and a basic working knowledge of Linux.
Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book Use Apache Spark for data processing with these hands-on recipes Implement end-to-end, large-scale data analysis better than ever before Work with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your data Who This Book Is For This book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework. Basic experience with data science implementation tasks is expected. Data science professionals looking to skill up and gain an edge in the field will find this book helpful. What You Will Learn Explore the topics of data mining, text mining, Natural Language Processing, information retrieval, and machine learning. Solve real-world analytical problems with large data sets. Address data science challenges with analytical tools on a distributed system like Spark (apt for iterative algorithms), which offers in-memory processing and more flexibility for data analysis at scale. Get hands-on experience with algorithms like Classification, regression, and recommendation on real datasets using Spark MLLib package. Learn about numerical and scientific computing using NumPy and SciPy on Spark. Use Predictive Model Markup Language (PMML) in Spark for statistical data mining models. In Detail Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark's selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark's data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work. Style and approach This book contains a comprehensive range of recipes designed to help you learn the fundamentals and tackle the difficulties of data science. This book outlines practical steps to produce powerful insights into Big Data through a recipe-based approach.
Unlock the power of your data with Hadoop 2.X ecosystem and its data warehousing techniques across large data sets About This Book Conquer the mountain of data using Hadoop 2.X tools The authors succeed in creating a context for Hadoop and its ecosystem Hands-on examples and recipes giving the bigger picture and helping you to master Hadoop 2.X data processing platforms Overcome the challenging data processing problems using this exhaustive course with Hadoop 2.X Who This Book Is For This course is for Java developers, who know scripting, wanting a career shift to Hadoop - Big Data segment of the IT industry. So if you are a novice in Hadoop or an expert, this book will make you reach the most advanced level in Hadoop 2.X. What You Will Learn Best practices for setup and configuration of Hadoop clusters, tailoring the system to the problem at hand Integration with relational databases, using Hive for SQL queries and Sqoop for data transfer Installing and maintaining Hadoop 2.X cluster and its ecosystem Advanced Data Analysis using the Hive, Pig, and Map Reduce programs Machine learning principles with libraries such as Mahout and Batch and Stream data processing using Apache Spark Understand the changes involved in the process in the move from Hadoop 1.0 to Hadoop 2.0 Dive into YARN and Storm and use YARN to integrate Storm with Hadoop Deploy Hadoop on Amazon Elastic MapReduce and Discover HDFS replacements and learn about HDFS Federation In Detail As Marc Andreessen has said “Data is eating the world,” which can be witnessed today being the age of Big Data, businesses are producing data in huge volumes every day and this rise in tide of data need to be organized and analyzed in a more secured way. With proper and effective use of Hadoop, you can build new-improved models, and based on that you will be able to make the right decisions. The first module, Hadoop beginners Guide will walk you through on understanding Hadoop with very detailed instructions and how to go about using it. Commands are explained using sections called “What just happened” for more clarity and understanding. The second module, Hadoop Real World Solutions Cookbook, 2nd edition, is an essential tutorial to effectively implement a big data warehouse in your business, where you get detailed practices on the latest technologies such as YARN and Spark. Big data has become a key basis of competition and the new waves of productivity growth. Hence, once you get familiar with the basics and implement the end-to-end big data use cases, you will start exploring the third module, Mastering Hadoop. So, now the question is if you need to broaden your Hadoop skill set to the next level after you nail the basics and the advance concepts, then this course is indispensable. When you finish this course, you will be able to tackle the real-world scenarios and become a big data expert using the tools and the knowledge based on the various step-by-step tutorials and recipes. Style and approach This course has covered everything right from the basic concepts of Hadoop till you master the advance mechanisms to become a big data expert. The goal here is to help you learn the basic essentials using the step-by-step tutorials and from there moving toward the recipes with various real-world solutions for you. It covers all the important aspects of Hadoop from system designing and configuring Hadoop, machine learning principles with various libraries with chapters illustrated with code fragments and schematic diagrams. This is a compendious course to explore Hadoop from the basics to the most advanced techniques available in Hadoop 2.X.
Over 80 recipes to help you breeze through your data analysis projects using R About This Book Analyse your data using the popular R packages like ggplot2 with ready-to-use and customizable recipes Find meaningful insights from your data and generate dynamic reports A practical guide to help you put your data analysis skills in R to practical use Who This Book Is For This book is for data scientists, analysts and even enthusiasts who want to learn and implement the various data analysis techniques using R in a practical way. Those looking for quick, handy solutions to common tasks and challenges in data analysis will find this book to be very useful. Basic knowledge of statistics and R programming is assumed. What You Will Learn Acquire, format and visualize your data using R Using R to perform an Exploratory data analysis Introduction to machine learning algorithms such as classification and regression Get started with social network analysis Generate dynamic reporting with Shiny Get started with geospatial analysis Handling large data with R using Spark and MongoDB Build Recommendation system- Collaborative Filtering, Content based and Hybrid Learn real world dataset examples- Fraud Detection and Image Recognition In Detail Data analytics with R has emerged as a very important focus for organizations of all kinds. R enables even those with only an intuitive grasp of the underlying concepts, without a deep mathematical background, to unleash powerful and detailed examinations of their data. This book will show you how you can put your data analysis skills in R to practical use, with recipes catering to the basic as well as advanced data analysis tasks. Right from acquiring your data and preparing it for analysis to the more complex data analysis techniques, the book will show you how you can implement each technique in the best possible manner. You will also visualize your data using the popular R packages like ggplot2 and gain hidden insights from it. Starting with implementing the basic data analysis concepts like handling your data to creating basic plots, you will master the more advanced data analysis techniques like performing cluster analysis, and generating effective analysis reports and visualizations. Throughout the book, you will get to know the common problems and obstacles you might encounter while implementing each of the data analysis techniques in R, with ways to overcoming them in the easiest possible way. By the end of this book, you will have all the knowledge you need to become an expert in data analysis with R, and put your skills to test in real-world scenarios. Style and Approach Hands-on recipes to walk through data science challenges using R Your one-stop solution for common and not-so-common pain points while performing real-world problems to execute a series of tasks. Addressing your common and not-so-common pain points, this is a book that you must have on the shelf
New Standards for Teaching and Learning in America's Schools
Author: Steven Zemelman
In this extensively revised and expanded second edition, we find updated descriptions of progressive teaching in six subject areas: reading, writing, mathematics, science, social studies, and the arts.
The Comprehensive Guide to Lose Rapid Weight, Burn Fat, and Transform Your Lifestyle
Author: Jenson Jamsen
Are you tired of the usual diets? Would you like to boost your energy and start living a healthy and productive lifestyle? Do you still think that you do not have perfect genetics, and there is nothing that can help you lose weight in a way that is both effective in the short term and sustainable over time? A new diet has arrived and taken the fitness world by storm - the Sirtfood Diet! The real breakthrough for this diet came when researchers discovered the benefits of fasting that come from the activation of the skinny gene, influencing many beneficial changes in the body. During this process, fat storage is stopped, and all that the body does is to halt its normal body process and then switch into a survival mode. Fat burning is then regulated, cell repair and rejuvenation come into play. "Sirtfood Diet", Will teach you one of the most recent discoveries in the world of health, science, and fitness. A lifestyle that will help you lose weight naturally and achieve your fitness goals effortlessly by activating something we already have inside us. A gene that turns our body into a fat-burning machine without losing energy or muscle in the process. This ultimate guide on the Sirtfood Diet is all you need to start losing weight rapidly and permanently! In this book you will find: How to turn the skinny gene on and off: you will learn why some people are skinny despite the way they eat It presents the Sirtfood Diet in details and explains how to modify it to fit your needs It provides an extensive shopping list, to help you get started It describes the two phases of the diet and helps you prepare for them It offers delicious recipes for every meal of the day It will stop you from making common mistakes that might hinder your weight loss And you get much, much more! Now you have the opportunity to improve your health, and get rid of those extra pounds in a matter of weeks! So don't wait, scroll up, click on "Buy Now" and Start Living a Lifestyle You Truly Want And Need!
Managing the Uncertainty in Restoring Physical Habitat
Author: Stephen Darby
The designers and managers of river restoration projects frequently face high levels of uncertainty due to such problems as having to use different models reflecting different results on the same problem, incomplete or absent data, and climatic/social/cultural changes.