داده‌های کلان نسل بعد: راهنمای عملی برای آپاچی کادو، ایمپالا و اسپارک

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 Front Matter ....Pages i-xxiii Next-Generation Big Data (Butch Quinto)....Pages 1-5 Introduction to Kudu (Butch Quinto)....Pages 7-56 Introduction to Impala (Butch Quinto)....Pages 57-99 High Performance Data Analysis with Impala and Kudu (Butch Quinto)....Pages 101-111 Introduction to Spark (Butch Quinto)....Pages 113-158 High Performance Data Processing with Spark and Kudu (Butch Quinto)....Pages 159-229 Batch and Real-Time Data Ingestion and Processing (Butch Quinto)....Pages 231-374 Big Data Warehousing (Butch Quinto)....Pages 375-406 Big Data Visualization and Data Wrangling (Butch Quinto)....Pages 407-476 Distributed In-Memory Big Data Computing (Butch Quinto)....Pages 477-493 Big Data Governance and Management (Butch Quinto)....Pages 495-506 Big Data in the Cloud (Butch Quinto)....Pages 507-536 Big Data Case Studies (Butch Quinto)....Pages 537-548 Back Matter ....Pages 549-557 Apache Spark is amazing when everything clicks. But if you haven't seen the performance improvements you expected, or still don't feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources