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Getting Started With Big Data Query Using Apache Impala
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Book Synopsis Getting Started with Big Data Query using Apache Impala by : Agus Kurniawan
Download or read book Getting Started with Big Data Query using Apache Impala written by Agus Kurniawan and published by PE Press. This book was released on 2021-02-06 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is designed for anyone who learns how to get started with Apache Impala. The book covers SQL queries and data manipulation for Apache Impala. The following is a list of highlight topics: * Introduction to Apache Impala * Working with Apache Impala Shell * SQL Querying with Apache Hue and Apache Impala * Loading Dataset to Apache Impala * Basic SQL Query for Apache Impala * Joining Query and Subquery on Apache Impala * Partition Data on Apache Impala * Apache Impala Database Programming with Java
Book Synopsis Getting Started with Impala by : John Russell
Download or read book Getting Started with Impala written by John Russell and published by "O'Reilly Media, Inc.". This book was released on 2014-09-25 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to write, tune, and port SQL queries and other statements for a Big Data environment, using Impala—the massively parallel processing SQL query engine for Apache Hadoop. The best practices in this practical guide help you design database schemas that not only interoperate with other Hadoop components, and are convenient for administers to manage and monitor, but also accommodate future expansion in data size and evolution of software capabilities. Written by John Russell, documentation lead for the Cloudera Impala project, this book gets you working with the most recent Impala releases quickly. Ideal for database developers and business analysts, the latest revision covers analytics functions, complex types, incremental statistics, subqueries, and submission to the Apache incubator. Getting Started with Impala includes advice from Cloudera’s development team, as well as insights from its consulting engagements with customers. Learn how Impala integrates with a wide range of Hadoop components Attain high performance and scalability for huge data sets on production clusters Explore common developer tasks, such as porting code to Impala and optimizing performance Use tutorials for working with billion-row tables, date- and time-based values, and other techniques Learn how to transition from rigid schemas to a flexible model that evolves as needs change Take a deep dive into joins and the roles of statistics
Book Synopsis Getting Started with Impala by : John Russell
Download or read book Getting Started with Impala written by John Russell and published by "O'Reilly Media, Inc.". This book was released on 2014-09-25 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to write, tune, and port SQL queries and other statements for a Big Data environment, using Impala—the massively parallel processing SQL query engine for Apache Hadoop. The best practices in this practical guide help you design database schemas that not only interoperate with other Hadoop components, and are convenient for administers to manage and monitor, but also accommodate future expansion in data size and evolution of software capabilities. Written by John Russell, documentation lead for the Cloudera Impala project, this book gets you working with the most recent Impala releases quickly. Ideal for database developers and business analysts, the latest revision covers analytics functions, complex types, incremental statistics, subqueries, and submission to the Apache incubator. Getting Started with Impala includes advice from Cloudera’s development team, as well as insights from its consulting engagements with customers. Learn how Impala integrates with a wide range of Hadoop components Attain high performance and scalability for huge data sets on production clusters Explore common developer tasks, such as porting code to Impala and optimizing performance Use tutorials for working with billion-row tables, date- and time-based values, and other techniques Learn how to transition from rigid schemas to a flexible model that evolves as needs change Take a deep dive into joins and the roles of statistics
Book Synopsis Introducing Data Science by : Davy Cielen
Download or read book Introducing Data Science written by Davy Cielen and published by Simon and Schuster. This book was released on 2016-05-02 with total page 475 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Introducing Data Science teaches you how to accomplish the fundamental tasks that occupy data scientists. Using the Python language and common Python libraries, you'll experience firsthand the challenges of dealing with data at scale and gain a solid foundation in data science. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Many companies need developers with data science skills to work on projects ranging from social media marketing to machine learning. Discovering what you need to learn to begin a career as a data scientist can seem bewildering. This book is designed to help you get started. About the Book Introducing Data ScienceIntroducing Data Science explains vital data science concepts and teaches you how to accomplish the fundamental tasks that occupy data scientists. You’ll explore data visualization, graph databases, the use of NoSQL, and the data science process. You’ll use the Python language and common Python libraries as you experience firsthand the challenges of dealing with data at scale. Discover how Python allows you to gain insights from data sets so big that they need to be stored on multiple machines, or from data moving so quickly that no single machine can handle it. This book gives you hands-on experience with the most popular Python data science libraries, Scikit-learn and StatsModels. After reading this book, you’ll have the solid foundation you need to start a career in data science. What’s Inside Handling large data Introduction to machine learning Using Python to work with data Writing data science algorithms About the Reader This book assumes you're comfortable reading code in Python or a similar language, such as C, Ruby, or JavaScript. No prior experience with data science is required. About the Authors Davy Cielen, Arno D. B. Meysman, and Mohamed Ali are the founders and managing partners of Optimately and Maiton, where they focus on developing data science projects and solutions in various sectors. Table of Contents Data science in a big data world The data science process Machine learning Handling large data on a single computer First steps in big data Join the NoSQL movement The rise of graph databases Text mining and text analytics Data visualization to the end user
Book Synopsis Hadoop Application Architectures by : Mark Grover
Download or read book Hadoop Application Architectures written by Mark Grover and published by "O'Reilly Media, Inc.". This book was released on 2015-06-30 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various components in the Hadoop ecosystem, this practical book takes you through architectural considerations necessary to tie those components together into a complete tailored application, based on your particular use case. To reinforce those lessons, the book’s second section provides detailed examples of architectures used in some of the most commonly found Hadoop applications. Whether you’re designing a new Hadoop application, or planning to integrate Hadoop into your existing data infrastructure, Hadoop Application Architectures will skillfully guide you through the process. This book covers: Factors to consider when using Hadoop to store and model data Best practices for moving data in and out of the system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and using windowing analytics Giraph, GraphX, and other tools for large graph processing on Hadoop Using workflow orchestration and scheduling tools such as Apache Oozie Near-real-time stream processing with Apache Storm, Apache Spark Streaming, and Apache Flume Architecture examples for clickstream analysis, fraud detection, and data warehousing
Download or read book Cloudera Impala written by John Russell and published by "O'Reilly Media, Inc.". This book was released on 2013-11-25 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn about Cloudera Impala--an open source project that's opening up the Apache Hadoop software stack to a wide audience of database analysts, users, and developers. The Impala massively parallel processing (MPP) engine makes SQL queries of Hadoop data simple enough to be accessible to analysts familiar with SQL and to users of business intelligence tools--and it’s fast enough to be used for interactive exploration and experimentation.
Book Synopsis Getting Started with Kudu by : Jean-Marc Spaggiari
Download or read book Getting Started with Kudu written by Jean-Marc Spaggiari and published by "O'Reilly Media, Inc.". This book was released on 2018-07-09 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fast data ingestion, serving, and analytics in the Hadoop ecosystem have forced developers and architects to choose solutions using the least common denominator—either fast analytics at the cost of slow data ingestion or fast data ingestion at the cost of slow analytics. There is an answer to this problem. With the Apache Kudu column-oriented data store, you can easily perform fast analytics on fast data. This practical guide shows you how. Begun as an internal project at Cloudera, Kudu is an open source solution compatible with many data processing frameworks in the Hadoop environment. In this book, current and former solutions professionals from Cloudera provide use cases, examples, best practices, and sample code to help you get up to speed with Kudu. Explore Kudu’s high-level design, including how it spreads data across servers Fully administer a Kudu cluster, enable security, and add or remove nodes Learn Kudu’s client-side APIs, including how to integrate Apache Impala, Spark, and other frameworks for data manipulation Examine Kudu’s schema design, including basic concepts and primitives necessary to make your project successful Explore case studies for using Kudu for real-time IoT analytics, predictive modeling, and in combination with another storage engine
Author :City of London College of Economics Publisher :City of London College of Economics ISBN 13 : Total Pages :2653 pages Book Rating :4./5 ( download)
Book Synopsis Data Scientist Diploma (master's level) - City of London College of Economics - 6 months - 100% online / self-paced by : City of London College of Economics
Download or read book Data Scientist Diploma (master's level) - City of London College of Economics - 6 months - 100% online / self-paced written by City of London College of Economics and published by City of London College of Economics. This book was released on with total page 2653 pages. Available in PDF, EPUB and Kindle. Book excerpt: Overview This diploma course covers all aspects you need to know to become a successful Data Scientist. Content - Getting Started with Data Science - Data Analytic Thinking - Business Problems and Data Science Solutions - Introduction to Predictive Modeling: From Correlation to Supervised Segmentation - Fitting a Model to Data - Overfitting and Its Avoidance - Similarity, Neighbors, and Clusters Decision Analytic Thinking I: What Is a Good Model? - Visualizing Model Performance - Evidence and Probabilities - Representing and Mining Text - Decision Analytic Thinking II: Toward Analytical Engineering - Other Data Science Tasks and Techniques - Data Science and Business Strategy - Machine Learning: Learning from Data with Your Machine. - And much more Duration 6 months Assessment The assessment will take place on the basis of one assignment at the end of the course. Tell us when you feel ready to take the exam and we’ll send you the assignment questions. Study material The study material will be provided in separate files by email / download link.
Book Synopsis Data Science For Dummies by : Lillian Pierson
Download or read book Data Science For Dummies written by Lillian Pierson and published by John Wiley & Sons. This book was released on 2021-09-15 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.
Book Synopsis Next-Generation Big Data by : Butch Quinto
Download or read book Next-Generation Big Data written by Butch Quinto and published by Apress. This book was released on 2018-06-12 with total page 572 pages. Available in PDF, EPUB and Kindle. Book excerpt: Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You’ll Learn Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive modeling Study real-world big data case studies from innovative companies, including Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard Who This Book Is For BI and big data warehouse professionals interested in gaining practical and real-world insight into next-generation big data processing and analytics using Apache Kudu, Impala, and Spark; and those who want to learn more about other advanced enterprise topics
Download or read book Cloudera Impala written by John Russell and published by . This book was released on 2013 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn about Cloudera Impala--an open source project that's opening up the Apache Hadoop software stack to a wide audience of database analysts, users, and developers. The Impala massively parallel processing (MPP) engine makes SQL queries of Hadoop data simple enough to be accessible to analysts familiar with SQL and to users of business intelligence tools--and it's fast enough to be used for interactive exploration and experimentation.
Book Synopsis Hadoop: The Definitive Guide by : Tom White
Download or read book Hadoop: The Definitive Guide written by Tom White and published by "O'Reilly Media, Inc.". This book was released on 2012-05-10 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
Book Synopsis Disruptive Analytics by : Thomas W. Dinsmore
Download or read book Disruptive Analytics written by Thomas W. Dinsmore and published by Apress. This book was released on 2016-08-27 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
Author :Management Association, Information Resources Publisher :IGI Global ISBN 13 :1668436639 Total Pages :1988 pages Book Rating :4.6/5 (684 download)
Book Synopsis Research Anthology on Big Data Analytics, Architectures, and Applications by : Management Association, Information Resources
Download or read book Research Anthology on Big Data Analytics, Architectures, and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2021-09-24 with total page 1988 pages. Available in PDF, EPUB and Kindle. Book excerpt: Society is now completely driven by data with many industries relying on data to conduct business or basic functions within the organization. With the efficiencies that big data bring to all institutions, data is continuously being collected and analyzed. However, data sets may be too complex for traditional data-processing, and therefore, different strategies must evolve to solve the issue. The field of big data works as a valuable tool for many different industries. The Research Anthology on Big Data Analytics, Architectures, and Applications is a complete reference source on big data analytics that offers the latest, innovative architectures and frameworks and explores a variety of applications within various industries. Offering an international perspective, the applications discussed within this anthology feature global representation. Covering topics such as advertising curricula, driven supply chain, and smart cities, this research anthology is ideal for data scientists, data analysts, computer engineers, software engineers, technologists, government officials, managers, CEOs, professors, graduate students, researchers, and academicians.
Book Synopsis Big Data Analytics with Java by : Rajat Mehta
Download or read book Big Data Analytics with Java written by Rajat Mehta and published by Packt Publishing Ltd. This book was released on 2017-07-31 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn the basics of analytics on big data using Java, machine learning and other big data tools About This Book Acquire real-world set of tools for building enterprise level data science applications Surpasses the barrier of other languages in data science and learn create useful object-oriented codes Extensive use of Java compliant big data tools like apache spark, Hadoop, etc. Who This Book Is For This book is for Java developers who are looking to perform data analysis in production environment. Those who wish to implement data analysis in their Big data applications will find this book helpful. What You Will Learn Start from simple analytic tasks on big data Get into more complex tasks with predictive analytics on big data using machine learning Learn real time analytic tasks Understand the concepts with examples and case studies Prepare and refine data for analysis Create charts in order to understand the data See various real-world datasets In Detail This book covers case studies such as sentiment analysis on a tweet dataset, recommendations on a movielens dataset, customer segmentation on an ecommerce dataset, and graph analysis on actual flights dataset. This book is an end-to-end guide to implement analytics on big data with Java. Java is the de facto language for major big data environments, including Hadoop. This book will teach you how to perform analytics on big data with production-friendly Java. This book basically divided into two sections. The first part is an introduction that will help the readers get acquainted with big data environments, whereas the second part will contain a hardcore discussion on all the concepts in analytics on big data. It will take you from data analysis and data visualization to the core concepts and advantages of machine learning, real-life usage of regression and classification using Naive Bayes, a deep discussion on the concepts of clustering,and a review of simple neural networks on big data using deepLearning4j or plain Java Spark code. This book is a must-have book for Java developers who want to start learning big data analytics and want to use it in the real world. Style and approach The approach of book is to deliver practical learning modules in manageable content. Each chapter is a self-contained unit of a concept in big data analytics. Book will step by step builds the competency in the area of big data analytics. Examples using real world case studies to give ideas of real applications and how to use the techniques mentioned. The examples and case studies will be shown using both theory and code.
Book Synopsis Handbook of Research on Big Data Storage and Visualization Techniques by : Segall, Richard S.
Download or read book Handbook of Research on Big Data Storage and Visualization Techniques written by Segall, Richard S. and published by IGI Global. This book was released on 2018-01-05 with total page 1078 pages. Available in PDF, EPUB and Kindle. Book excerpt: The digital age has presented an exponential growth in the amount of data available to individuals looking to draw conclusions based on given or collected information across industries. Challenges associated with the analysis, security, sharing, storage, and visualization of large and complex data sets continue to plague data scientists and analysts alike as traditional data processing applications struggle to adequately manage big data. The Handbook of Research on Big Data Storage and Visualization Techniques is a critical scholarly resource that explores big data analytics and technologies and their role in developing a broad understanding of issues pertaining to the use of big data in multidisciplinary fields. Featuring coverage on a broad range of topics, such as architecture patterns, programing systems, and computational energy, this publication is geared towards professionals, researchers, and students seeking current research and application topics on the subject.
Download or read book Hadoop Security written by Ben Spivey and published by "O'Reilly Media, Inc.". This book was released on 2015-06-29 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: As more corporations turn to Hadoop to store and process their most valuable data, the risk of a potential breach of those systems increases exponentially. This practical book not only shows Hadoop administrators and security architects how to protect Hadoop data from unauthorized access, it also shows how to limit the ability of an attacker to corrupt or modify data in the event of a security breach. Authors Ben Spivey and Joey Echeverria provide in-depth information about the security features available in Hadoop, and organize them according to common computer security concepts. You’ll also get real-world examples that demonstrate how you can apply these concepts to your use cases. Understand the challenges of securing distributed systems, particularly Hadoop Use best practices for preparing Hadoop cluster hardware as securely as possible Get an overview of the Kerberos network authentication protocol Delve into authorization and accounting principles as they apply to Hadoop Learn how to use mechanisms to protect data in a Hadoop cluster, both in transit and at rest Integrate Hadoop data ingest into enterprise-wide security architecture Ensure that security architecture reaches all the way to end-user access
