krainaksiazek real time tasks scheduling in cloud computing environment 20123882

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Pthreads Programming - 2827062571

143,84 zł

Pthreads Programming O'Reilly Media, Inc, USA

Książki / Literatura obcojęzyczna

Computers are just as busy as the rest of us nowadays. They have lots of tasks to do at once, and need some cleverness to get them all done at the same time. That's why threads are seen more and more often as a new model for programming. Threads have been available for some time. The Mach operating system, the Distributed Computer Environment (DCE), and Windows NT all feature threads. One advantage of most UNIX implementations, as well as DCE, is that they conform to a recently ratified POSIX standard (originally 1003.4a, now 1003.1c), which allows your programs to be portable between them. POSIX threads are commonly known as pthreads, after the word that starts all the names of the function calls. The standard is supported by Solaris, OSF/1, AIX, and several other UNIX-based operating systems. The idea behind threads programming is to have multiple tasks running concurrently within the same program. They can share a single CPU as processes do, or take advantage of multiple CPUs when available. In either case, they provide a clean way to divide the tasks of a program while sharing data. A window interface can read input on dozens of different buttons, each responsible for a separate task. A network server has to accept simultaneous calls from many clients, providing each with reasonable response time. A multiprocessor runs a number-crunching program on several CPUs at once, combining the results when all are done. All these kinds of applications can benefit from threads. In this book you will learn not only what the pthread calls are, but when it is a good idea to use threads and how to make them efficient (which is the whole reason for using threads in the first place). The authors delves into performance issues, comparing threads to processes, contrasting kernel threads to user threads, and showing how to measure speed. He also describes in a simple, clear manner what all the advanced features are for, and how threads interact with the rest of the UNIX system. Topics include: * Basic design techniques * Mutexes, conditions, and specialized synchronization techniques * Scheduling, priorities, and other real-time issues * Cancellation * UNIX libraries and re-entrant routines * Signals * Debugging tips * Measuring performance * Special considerations for the Distributed Computing Environment (DCE)


Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself - 2826800607

204,96 zł

Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself Sams Publishing

Książki / Literatura obcojęzyczna

With Microsoft HDInsight, business professionals and data analysts can rapidly leverage the power of Hadoop on a flexible, scalable cloud-based platform, using Microsoft's accessible business intelligence, visualization, and productivity tools. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to provision, configure, monitor, troubleshoot, and use HDInsight, even if you're new to big data analytics. Each short, easy lesson builds on all that's come before: you'll learn all of HDInsight's essentials as you solve real data analytics problems. Sams Teach Yourself Big Data Analytics with Microsoft HDInsight in 24 Hours covers all this, and much more: * Introduction of Big Data, NoSQL systems, its Business Value Proposition and use cases examples * Introduction to Hadoop, Architecture, Ecosystem and Microsoft HDInsight * Getting to know Hadoop 2.0 and the innovations it provides like HDFS2 and YARN * Quickly installing, configuring, and monitoring Hadoop (HDInsight) clusters in the cloud and automating cluster provisioning * Customize the HDInsight cluster and install additional Hadoop ecosystem projects using Script Actions * Administering HDInsight from the Hadoop command prompt or Microsoft PowerShell * Using the Microsoft Azure HDInsight Emulator for learning or development * Understanding HDFS, HDFS vs. Azure Blob Storage, MapReduce Job Framework and Job Execution Pipeline * Doing big data analytics with MapReduce, writing your MapReduce programs in your choice of .NET programming language such as C# * Using Hive for big data analytics, demonstrate end to end scenario and how Apache Tez improves the performance several folds * Consuming HDInsight data from Microsoft BI Tools over Hive ODBC Driver - Using HDInsight with Microsoft BI and Power BI to simplify data integration, analysis, and reporting * Using PIG for big data transformation workflows step by step * Apache HBase on HDInsight, its architecture, data model, HBase vs. Hive, programmatically managing HBase data with C# and Apache Phoenix * Using Sqoop or SSIS (SQL Server Integration Services) to move data to/from HDInsight and build data integration workflows for transferring data * Using Oozie for scheduling, co-ordination and managing data processing workflows in HDInsight cluster * Using R programming language with HDInsight for performing statistical computing on Big Data sets * Using Apache Spark's in-memory computation model to run big data analytics up to 100 times faster than Hadoop MapReduce * Perform real-time Stream Analytics on high-velocity big data streams with Storm * Integration of Enterprise Data Warehouse with Hadoop and Microsoft Analytics Platform System (APS), formally known as SQL Server Parallel Data Warehouse (PDW) Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid problems. By the time you're finished, you'll be comfortable going beyond the book to create any HDInsight app you can imagine!


Sklepy zlokalizowane w miastach: Warszawa, Kraków, Łódź, Wrocław, Poznań, Gdańsk, Szczecin, Bydgoszcz, Lublin, Katowice

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