Publisher: 8
Francesco Pierfederici
CPU-intensive data processing tasks have become crucial considering the complexity of the various big data applications that are used today. Reducing the CPU utilization per process is very important to improve the overall speed of applications.This book will teach you how to perform parallel execution of computations by distributing them across multiple processors in a single machine, thus improving the overall performance of a big data processing task. We will cover synchronous and asynchronous models, shared memory and file systems, communication between various processes, synchronization, and more.
Distributed Data Systems with Azure Databricks. Create, deploy, and manage enterprise data pipelines
Alan Bernardo Palacio
Microsoft Azure Databricks helps you to harness the power of distributed computing and apply it to create robust data pipelines, along with training and deploying machine learning and deep learning models. Databricks' advanced features enable developers to process, transform, and explore data. Distributed Data Systems with Azure Databricks will help you to put your knowledge of Databricks to work to create big data pipelines. The book provides a hands-on approach to implementing Azure Databricks and its associated methodologies that will make you productive in no time. Complete with detailed explanations of essential concepts, practical examples, and self-assessment questions, you’ll begin with a quick introduction to Databricks core functionalities, before performing distributed model training and inference using TensorFlow and Spark MLlib. As you advance, you’ll explore MLflow Model Serving on Azure Databricks and implement distributed training pipelines using HorovodRunner in Databricks. Finally, you’ll discover how to transform, use, and obtain insights from massive amounts of data to train predictive models and create entire fully working data pipelines. By the end of this MS Azure book, you’ll have gained a solid understanding of how to work with Databricks to create and manage an entire big data pipeline.
Guanhua Wang
Reducing time cost in machine learning leads to a shorter waiting time for model training and a faster model updating cycle. Distributed machine learning enables machine learning practitioners to shorten model training and inference time by orders of magnitude. With the help of this practical guide, you'll be able to put your Python development knowledge to work to get up and running with the implementation of distributed machine learning, including multi-node machine learning systems, in no time. You'll begin by exploring how distributed systems work in the machine learning area and how distributed machine learning is applied to state-of-the-art deep learning models. As you advance, you'll see how to use distributed systems to enhance machine learning model training and serving speed. You'll also get to grips with applying data parallel and model parallel approaches before optimizing the in-parallel model training and serving pipeline in local clusters or cloud environments. By the end of this book, you'll have gained the knowledge and skills needed to build and deploy an efficient data processing pipeline for machine learning model training and inference in a distributed manner.
Bhupesh Guptha Muthiyalu, Suneel Kumar Kunani
Building distributed applications in this modern era can be a tedious task as customers expect high availability, high performance, and improved resilience. With the help of this book, you'll discover how you can harness the power of Microsoft Orleans to build impressive distributed applications.Distributed .NET with Microsoft Orleans will demonstrate how to leverage Orleans to build highly scalable distributed applications step by step in the least possible time and with minimum effort. You'll explore some of the key concepts of Microsoft Orleans, including the Orleans programming model, runtime, virtual actors, hosting, and deployment. As you advance, you'll become well-versed with important Orleans assets such as grains, silos, timers, and persistence. Throughout the book, you'll create a distributed application by adding key components to the application as you progress through each chapter and explore them in detail.By the end of this book, you'll have developed the confidence and skills required to build distributed applications using Microsoft Orleans and deploy them in Microsoft Azure.
Diuna. Dziedzic Kaladanu. Trylogia Kaladanu. Tom 1
Brian Herbert, Kevin J. Anderson
Czytając Dziedzica Kaladanu, wszyscy fani Diuny mogą z satysfakcją towarzyszyć narodzinom legendy. Po tym, jak Bene Gesserit odwołały Jessikę z Kaladanu i wysłały jako konkubinę do innego szlachcica, książę Leto postanowił zaangażować się w rozbicie radykalnego ruchu na rzecz Wspólnoty Szlacheckiej. Kaladanem zaś w jego imieniu zarządza ich syn. Ledwie czternastoletni Paul wkracza w świat, którego sobie nawet nie wyobrażał. Podczas gdy sardaukarzy pacyfikują kolejne planety i wskutek knowań Harkonnenów zagrażają też Kaladanowi, Paul wyrasta na przywódcę i wstępuje na krętą ścieżkę swego przeznaczenia jako przyszły MuadDib.
Jacek Lewandowski, Artur Mamcarz
Opracowanie jest połączeniem wiedzy płynącej z badań klinicznych i wieloletniego doświadczenia lekarzy praktyków. Autorzy przedstawiają różne aspekty leczenia diuretykami. Diuretyki odgrywają kluczową rolę w terapii chorób układu sercowo-naczyniowego. Stanowią niezbędny element skojarzonego leczenia nadciśnienia tętniczego, potencjalna zaleta leków moczopędnych polega na przywracaniu fizjologicznego profilu dobowego ciśnienia u chorych bez nocnego obniżenia ciśnienia.
Arthur Morrison
Arthur Morrison, who was English novelist, short story writer and journalist, wrote pioneering realistic narratives about working-class life in Londons East End. He is also celebrated for his exciting mystery stories, featuring the detective Martin Hewitt, who served as a natural successor to Sherlock Holmes. This comprehensive book presents Morrisons collection of short stories. The collection includes: Chance of the Game, Spottos Reclamation, A Dead Un, The Disorder of the Bath, His Talk of Bricks, Teacher and Taught, A Blot on St. Basil, The Torn Heart and others. Each story features a fascinating look at life in the 20th century, and even includes some action along the way.
Katarzyna Kwapisz-Osadnik
Monografia zawiera spójny opis funkcjonowania czterech włoskich przyimków di, da, a oraz in, które zaliczane są do grupy przyimków neutralnych, tj. na tyle polisemicznych, że dotarcie do znaczenia rozpatruje się w oparciu o funkcję relacyjną w kontekście. Przyimki te konkurują ze sobą i z innymi przyimkami w wyrażaniu tych samych relacji między tymi samymi obiektami, np. andare in Francia/a Roma, stare al bar/nel bar/dentro il bar; interessarsi a/di; parlare a/di/con; di più/al più/per lo più. Problematyczne jest również ich funkcjonowanie w formie prostej lub ściągniętej, co związane jest z obecnością rodzajnika, np. andare in/nel Portogallo; saltare di felicità/dalla gioia.