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How can you get your data from frontend servers to Hadoop in near real time? With this complete reference guide, you’ll learn Flume’s rich set of features for collecting, aggregating, and writing large amounts of streaming data to the Hadoop Distributed File System (HDFS), Apache HBase, SolrCloud, Elastic Search, and other systems. Using Flume shows operations engineers how to configure, deploy, and monitor a Flume cluster, and teaches developers how to write Flume plugins and custom components for their specific use-cases. You’ll learn about Flume’s design and implementation, as well as various features that make it highly scalable, flexible, and reliable. Code examples and exercises are available on GitHub. Learn how Flume provides a steady rate of flow by acting as a buffer between data producers and consumers Dive into key Flume components, including sources that accept data and sinks that write and deliver it Write custom plugins to customize the way Flume receives, modifies, formats, and writes data Explore APIs for sending data to Flume agents from your own applications Plan and deploy Flume in a scalable and flexible way—and monitor your cluster once it’s running
Don't tell anyone -- the only safety is in secrecy. During the summer of 1894 the giant sequoia trees -- the oldest living things on earth -- are being felled for lumber in northern California. When fifteen-year-old Francie finds a note hidden in the stump of an old sequoia, she immediately recognizes her sister's handwriting. But Carrie died in an accident six years ago. Could Carrie's secret still be important? Francie's search for the truth turns dangerous, and she needs to get to St. Joseph fast. She's faced with the choice of either giving up, or riding the flume, a rickety track that carries lumber from the mills in the mountains to the lumberyard in St. Joseph. Should Francie risk her life for the secret her sister fought to keep?
Bobby Pendragon is a seemingly normal and somewhat reluctant 14- year-old boy who is swept into an amazing five-year quest.
The fresh water supplies of the Earth are finite and as the world's population continues to grow humanity's thirst for this water seems unquenchable. Intense pressure is being exerted upon freshwater resources and a lack of adequate clean water is seen as one of the most serious global problems for the 21st century. Indeed it has been said that the next war will be fought over water, not oil. Human health and the health of supporting ecosystems increasingly depends upon our ability to find, control, manage and understand water. In a single volume, The Encyclopedia of Hydrology and Water Resources provides the reader with a comprehensive overview and understanding of the diverse field of hydrology. The intimate inclusion of material on water resources emphasizes the practical applications of this field, applications which are indispensable in any modern approach to the subject. This volume is a vital reference for all hydrologists, hydrogeologists and water engineers worldwide, whether they are concerned with the exploitation of new sources of water, the protection and management of existing reserves, or the science of surface water and groundwater flow. 114 eminent scientists from 17 countries worldwide have contributed to this authoritative volume. Superbly illustrated throughout, it includes almost 300 entries on a range of key topics, including arid and semi-arid zones, climates and climate change, floods and droughts, desertification, entropy, flow measurement, groundwater, hydrological cycle, hydrological models, infiltration, karst hydrology, paleohydrology, precipitation, remote sensing, river pollution prevention, rivers, lakes and seas, satellite hydrology, soil erosion, water treatment, water use, weather radar, and world water balance.
A practical guide to implementing your enterprise data lake using Lambda Architecture as the base About This Book Build a full-fledged data lake for your organization with popular big data technologies using the Lambda architecture as the base Delve into the big data technologies required to meet modern day business strategies A highly practical guide to implementing enterprise data lakes with lots of examples and real-world use-cases Who This Book Is For Java developers and architects who would like to implement a data lake for their enterprise will find this book useful. If you want to get hands-on experience with the Lambda Architecture and big data technologies by implementing a practical solution using these technologies, this book will also help you. What You Will Learn Build an enterprise-level data lake using the relevant big data technologies Understand the core of the Lambda architecture and how to apply it in an enterprise Learn the technical details around Sqoop and its functionalities Integrate Kafka with Hadoop components to acquire enterprise data Use flume with streaming technologies for stream-based processing Understand stream- based processing with reference to Apache Spark Streaming Incorporate Hadoop components and know the advantages they provide for enterprise data lakes Build fast, streaming, and high-performance applications using ElasticSearch Make your data ingestion process consistent across various data formats with configurability Process your data to derive intelligence using machine learning algorithms In Detail The term "Data Lake" has recently emerged as a prominent term in the big data industry. Data scientists can make use of it in deriving meaningful insights that can be used by businesses to redefine or transform the way they operate. Lambda architecture is also emerging as one of the very eminent patterns in the big data landscape, as it not only helps to derive useful information from historical data but also correlates real-time data to enable business to take critical decisions. This book tries to bring these two important aspects — data lake and lambda architecture—together. This book is divided into three main sections. The first introduces you to the concept of data lakes, the importance of data lakes in enterprises, and getting you up-to-speed with the Lambda architecture. The second section delves into the principal components of building a data lake using the Lambda architecture. It introduces you to popular big data technologies such as Apache Hadoop, Spark, Sqoop, Flume, and ElasticSearch. The third section is a highly practical demonstration of putting it all together, and shows you how an enterprise data lake can be implemented, along with several real-world use-cases. It also shows you how other peripheral components can be added to the lake to make it more efficient. By the end of this book, you will be able to choose the right big data technologies using the lambda architectural patterns to build your enterprise data lake. Style and approach The book takes a pragmatic approach, showing ways to leverage big data technologies and lambda architecture to build an enterprise-level data lake.