Download or read book Apache Kafka 1 0 Cookbook written by Raúl Estrada and published by . This book was released on 2017-12-21 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 Key Features Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Book Description Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. What you will learn -Install and configure Apache Kafka 1.0 to get optimal performance -Create and configure Kafka Producers and Consumers -Operate your Kafka clusters efficiently by implementing the mirroring technique -Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka -Monitor Kafka using tools such as Graphite and Ganglia -Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more Who this book is for This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful.

Download or read book Apache Kafka 1 0 Cookbook written by Raúl Estrada and published by Packt Publishing Ltd. This book was released on 2017-12-22 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 About This Book Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Who This Book Is For This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful. What You Will Learn Install and configure Apache Kafka 1.0 to get optimal performance Create and configure Kafka Producers and Consumers Operate your Kafka clusters efficiently by implementing the mirroring technique Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka Monitor Kafka using tools such as Graphite and Ganglia Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more In Detail Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. Style and approach Following a cookbook recipe-based approach, we'll teach you how to solve everyday difficulties and struggles you encounter using Kafka through hands-on examples.

Download or read book Apache Kafka 1 0 Cookbook written by Raúl Estrada and published by Packt Publishing Ltd. This book was released on 2017-12-22 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify real-time data processing by leveraging the power of Apache Kafka 1.0 About This Book Use Kafka 1.0 features such as Confluent platforms and Kafka streams to build efficient streaming data applications to handle and process your data Integrate Kafka with other Big Data tools such as Apache Hadoop, Apache Spark, and more Hands-on recipes to help you design, operate, maintain, and secure your Apache Kafka cluster with ease Who This Book Is For This book is for developers and Kafka administrators who are looking for quick, practical solutions to problems encountered while operating, managing or monitoring Apache Kafka. If you are a developer, some knowledge of Scala or Java will help, while for administrators, some working knowledge of Kafka will be useful. What You Will Learn Install and configure Apache Kafka 1.0 to get optimal performance Create and configure Kafka Producers and Consumers Operate your Kafka clusters efficiently by implementing the mirroring technique Work with the new Confluent platform and Kafka streams, and achieve high availability with Kafka Monitor Kafka using tools such as Graphite and Ganglia Integrate Kafka with third-party tools such as Elasticsearch, Logstash, Apache Hadoop, Apache Spark, and more In Detail Apache Kafka provides a unified, high-throughput, low-latency platform to handle real-time data feeds. This book will show you how to use Kafka efficiently, and contains practical solutions to the common problems that developers and administrators usually face while working with it. This practical guide contains easy-to-follow recipes to help you set up, configure, and use Apache Kafka in the best possible manner. You will use Apache Kafka Consumers and Producers to build effective real-time streaming applications. The book covers the recently released Kafka version 1.0, the Confluent Platform and Kafka Streams. The programming aspect covered in the book will teach you how to perform important tasks such as message validation, enrichment and composition.Recipes focusing on optimizing the performance of your Kafka cluster, and integrate Kafka with a variety of third-party tools such as Apache Hadoop, Apache Spark, and Elasticsearch will help ease your day to day collaboration with Kafka greatly. Finally, we cover tasks related to monitoring and securing your Apache Kafka cluster using tools such as Ganglia and Graphite. If you're looking to become the go-to person in your organization when it comes to working with Apache Kafka, this book is the only resource you need to have. Style and approach Following a cookbook recipe-based approach, we'll teach you how to solve everyday difficulties and struggles you encounter using Kafka through hands-on examples.

Download or read book Spark Cookbook written by Posts & Telecom Press and published by Packt Publishing Ltd. This book was released on 2024-05-23 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: 针对常见问题的快速指南,囊括60多种Spark开发技巧 Key Features 针对常见问题的快速指南 囊括60多种Spark开发技巧 Book DescriptionSpark是一个基于内存计算的开源集群计算系统,它非常小巧玲珑,让数据分析更加快速,已逐渐成为新一代大数据处理平台中的佼佼者。 本书内容分为12章,从认识Apache Spark开始讲解,陆续介绍了Spark的使用、外部数据源、Spark SQL、Spark Streaming、机器学习、监督学习中的回归和分类、无监督学习、推荐系统、图像处理、优化及调优等内容。 本书适合大数据领域的技术人员,可以帮助他们更好地洞悉大数据,本书也适合想要学习Spark进行大数据处理的人员,它将是一本绝佳的参考教程。What you will learn Spark的使用 外部数据源 Spark SQL Spark Streaming 机器学习 监督学习中的回归和分类 无监督学习 推荐系统 图像处理 优化及调优 Who this book is for 大数据领域的技术人员、想要学习Spark进行大数据处理的人员。

Download or read book Data Engineering with Databricks Cookbook written by Pulkit Chadha and published by Packt Publishing Ltd. This book was released on 2024-05-31 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work through 70 recipes for implementing reliable data pipelines with Apache Spark, optimally store and process structured and unstructured data in Delta Lake, and use Databricks to orchestrate and govern your data Key Features Learn data ingestion, data transformation, and data management techniques using Apache Spark and Delta Lake Gain practical guidance on using Delta Lake tables and orchestrating data pipelines Implement reliable DataOps and DevOps practices, and enforce data governance policies on Databricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionData Engineering with Databricks Cookbook will guide you through recipes to effectively use Apache Spark, Delta Lake, and Databricks for data engineering, beginning with an introduction to data ingestion and loading with Apache Spark. As you progress, you’ll be introduced to various data manipulation and data transformation solutions that can be applied to data. You'll find out how to manage and optimize Delta tables, as well as how to ingest and process streaming data. The book will also show you how to improve the performance problems of Apache Spark apps and Delta Lake. Later chapters will show you how to use Databricks to implement DataOps and DevOps practices and teach you how to orchestrate and schedule data pipelines using Databricks Workflows. Finally, you’ll understand how to set up and configure Unity Catalog for data governance. By the end of this book, you’ll be well-versed in building reliable and scalable data pipelines using modern data engineering technologies.What you will learn Perform data loading, ingestion, and processing with Apache Spark Discover data transformation techniques and custom user-defined functions (UDFs) in Apache Spark Manage and optimize Delta tables with Apache Spark and Delta Lake APIs Use Spark Structured Streaming for real-time data processing Optimize Apache Spark application and Delta table query performance Implement DataOps and DevOps practices on Databricks Orchestrate data pipelines with Delta Live Tables and Databricks Workflows Implement data governance policies with Unity Catalog Who this book is for This book is for data engineers, data scientists, and data practitioners who want to learn how to build efficient and scalable data pipelines using Apache Spark, Delta Lake, and Databricks. To get the most out of this book, you should have basic knowledge of data architecture, SQL, and Python programming.

Download or read book Spark Cookbook written by Rishi Yadav and published by Packt Publishing Ltd. This book was released on 2015-07-27 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: By introducing in-memory persistent storage, Apache Spark eliminates the need to store intermediate data in filesystems, thereby increasing processing speed by up to 100 times. This book will focus on how to analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting up development environments. You will then cover various recipes to perform interactive queries using Spark SQL and real-time streaming with various sources such as Twitter Stream and Apache Kafka. You will then focus on machine learning, including supervised learning, unsupervised learning, and recommendation engine algorithms. After mastering graph processing using GraphX, you will cover various recipes for cluster optimization and troubleshooting.

Download or read book Knative Cookbook written by Burr Sutter and published by O'Reilly Media. This book was released on 2020-04-09 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enterprise developers face several challenges when it comes to building serverless applications, such as integrating applications and building container images from source. With more than 60 practical recipes, this cookbook helps you solve these issues with Knative—the first serverless platform natively designed for Kubernetes. Each recipe contains detailed examples and exercises, along with a discussion of how and why it works. If you have a good understanding of serverless computing and Kubernetes core resources such as deployment, services, routes, and replicas, the recipes in this cookbook show you how to apply Knative in real enterprise application development. Authors Kamesh Sampath and Burr Sutter include chapters on autoscaling, build and eventing, observability, Knative on OpenShift, and more. With this cookbook, you’ll learn how to: Efficiently build, deploy, and manage modern serverless workloads Apply Knative in real enterprise scenarios, including advanced eventing Monitor your Knative serverless applications effectively Integrate Knative with CI/CD principles, such as using pipelines for faster, more successful production deployments Deploy a rich ecosystem of enterprise integration patterns and connectors in Apache Camel K as Kubernetes and Knative components

Download or read book Cloud Native Microservices Cookbook written by Varun Yadav and published by BPB Publications. This book was released on 2024-04-17 with total page 413 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the secrets of cloud-native success with step-by-step recipes for conquering every stage of microservice deployment KEY FEATURES ● Develop, test, build, and deploy with cloud-native microservices. ● Orchestrate microservices with containerization in the cloud. ● Ensure cloud observability and security in implementation. DESCRIPTION The convergence of microservices and cloud technology represents a significant paradigm shift in software development. To fully leverage the potential of both, integration from the outset of application development is crucial. Cloud-native microservices cookbook serve as a conduit, harmonizing disparate elements of microservice construction by establishing a cohesive framework from inception to deployment. This book meticulously outlines the various stages involved in launching an application utilizing cloud-native microservices. It commences with the foundational aspects of application development, emphasizing microservice architecture principles such as configuration and service discovery, considering cloud infrastructure. Progressing through containerization, continuous integration (CI), and continuous deployment (CD) pipelines, the book explores the intricacies of orchestration, high availability (HA), auto scalability, and cloud security. Subsequently, it elucidates the significance of observability in monitoring microservices post-deployment, concluding with a comprehensive exploration of Infrastructure as Code (IaC) for cloud infrastructure provisioning. Explore cloud-native microservices basics using real-world examples from the finance sector. Follow curated recipes from concept to cloud deployment for a clear understanding and smooth application development. WHAT YOU WILL LEARN ● Learn the fundamental principles of data architecture. ● Practical methodology encompassing the development, testing, building, containerization, and orchestration of microservices. ● Software development, spanning from initial design to cloud hosting. ● Achieve microservice auto scalability and high availability. ● Utilizing cloud services and experimenting with newfound services confidently. ● Meticulously track cloud expenditures, alleviating any apprehension surrounding cost management. WHO THIS BOOK IS FOR The book is ideal for software developers, solution designers, and DevOps engineers with a foundational understanding of programming concepts and professionals seeking to deepen their expertise in system architecture and full-stack development within cloud environments. TABLE OF CONTENTS 1. Microservices and Cloud 2. Developing Microservices and Test Cases 3. Externalize Application Configurations 4. Implementing Dynamic Services 5. Containerization Using Docker 6. Pipeline Automation for CI/CD 7. Microservices Orchestration 8. Auto Scalability, High Availability, and Disaster Recovery 9. Cloud Security 10. Observability 11. Infrastructure Automation with IaC

Download or read book Apache Kafka Cookbook written by Saurabh Minni and published by . This book was released on 2015 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 50 hands-on recipes to efficiently administer, maintain, and use your Apache Kafka installationAbout This Book- Quickly configure and manage your Kafka cluster- Learn how to use the Apache Kafka cluster and connect it with tools for big data processing- A practical guide to monitor your Apache Kafka installationWho This Book Is ForIf you are a programmer or big data engineer using or planning to use Apache Kafka, then this book is for you. This book has several recipes which will teach you how to effectively use Apache Kafka. You need to have some basic knowledge of Java. If you don't know big data tools, this would be your stepping stone for learning how to consume the data in these kind of systems.What You Will Learn- Learn how to configure Kafka brokers for better efficiency- Explore how to configure producers and consumers for optimal performance- Set up tools for maintaining and operating Apache Kafka- Create producers and consumers for Apache Kafka in Java- Understand how Apache Kafka can be used by several third party system for big data processing, such as Apache Storm, Apache Spark, Hadoop, and more- Monitor Apache Kafka using tools like graphite and GangliaIn DetailThis book will give you details about how to manage and administer your Apache Kafka Cluster.We will cover topics like how to configure your broker, producer, and consumer for maximum efficiency for your situation. Also, you will learn how to maintain and administer your cluster for fault tolerance. We will also explore tools provided with Apache Kafka to do regular maintenance operations. We shall also look at how to easily integrate Apache Kafka with big data tools like Hadoop, Apache Spark, Apache Storm, and Elasticsearch.Style and approachEasy-to-follow, step-by-step recipes explaining from start to finish how to accomplish real-world tasks.

Download or read book Apache Spark 2 x Machine Learning Cookbook written by Siamak Amirghodsi and published by Packt Publishing Ltd. This book was released on 2017-09-22 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simplify machine learning model implementations with Spark About This Book Solve the day-to-day problems of data science with Spark This unique cookbook consists of exciting and intuitive numerical recipes Optimize your work by acquiring, cleaning, analyzing, predicting, and visualizing your data Who This Book Is For This book is for Scala developers with a fairly good exposure to and understanding of machine learning techniques, but lack practical implementations with Spark. A solid knowledge of machine learning algorithms is assumed, as well as hands-on experience of implementing ML algorithms with Scala. However, you do not need to be acquainted with the Spark ML libraries and ecosystem. What You Will Learn Get to know how Scala and Spark go hand-in-hand for developers when developing ML systems with Spark Build a recommendation engine that scales with Spark Find out how to build unsupervised clustering systems to classify data in Spark Build machine learning systems with the Decision Tree and Ensemble models in Spark Deal with the curse of high-dimensionality in big data using Spark Implement Text analytics for Search Engines in Spark Streaming Machine Learning System implementation using Spark In Detail Machine learning aims to extract knowledge from data, relying on fundamental concepts in computer science, statistics, probability, and optimization. Learning about algorithms enables a wide range of applications, from everyday tasks such as product recommendations and spam filtering to cutting edge applications such as self-driving cars and personalized medicine. You will gain hands-on experience of applying these principles using Apache Spark, a resilient cluster computing system well suited for large-scale machine learning tasks. This book begins with a quick overview of setting up the necessary IDEs to facilitate the execution of code examples that will be covered in various chapters. It also highlights some key issues developers face while working with machine learning algorithms on the Spark platform. We progress by uncovering the various Spark APIs and the implementation of ML algorithms with developing classification systems, recommendation engines, text analytics, clustering, and learning systems. Toward the final chapters, we'll focus on building high-end applications and explain various unsupervised methodologies and challenges to tackle when implementing with big data ML systems. Style and approach This book is packed with intuitive recipes supported with line-by-line explanations to help you understand how to optimize your work flow and resolve problems when working with complex data modeling tasks and predictive algorithms. This is a valuable resource for data scientists and those working on large scale data projects.

Download or read book Clojure Programming Cookbook written by Makoto Hashimoto and published by Packt Publishing Ltd. This book was released on 2016-10-28 with total page 613 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handle every problem you come across in the world of Clojure programming with this expert collection of recipes About This Book Discover a wide variety of practical cases and real world techniques to enhance your productivity with Clojure. Learn to resolve the everyday issues you face with a functional mindset using Clojure You will learn to write highly efficient, more productive, and error-free programs without the risk of deadlocks and race-conditions Who This Book Is For This book is for Clojure developers who have some Clojure programming experience and are well aware of their shortcomings. If you want to learn to tackle common problems, become an expert, and develop a solid skill set, then this book is for you. What You Will Learn Manipulate, access, filter, and transform your data with Clojure Write efficient parallelized code through Clojure abstractions Tackle Complex Concurrency easily with Reactive Programming Build on Haskell abstractions to write dynamic functional tests Write AWS Lambda functions effortlessly Put Clojure in use into your IoT devices Use Clojure with Slack for instant monitoring Scaling your Clojure application using Docker Develop real-time system interactions using MQTT and websockets In Detail When it comes to learning and using a new language you need an effective guide to be by your side when things get rough. For Clojure developers, these recipes have everything you need to take on everything this language offers. This book is divided into three high impact sections. The first section gives you an introduction to live programming and best practices. We show you how to interact with your connections by manipulating, transforming, and merging collections. You'll learn how to work with macros, protocols, multi-methods, and transducers. We'll also teach you how to work with languages such as Java, and Scala. The next section deals with intermediate-level content and enhances your Clojure skills, here we'll teach you concurrency programming with Clojure for high performance. We will provide you with advanced best practices, tips on Clojure programming, and show you how to work with Clojure while developing applications. In the final section you will learn how to test, deploy and analyze websocket behavior when your app is deployed in the cloud. Finally, we will take you through DevOps. Developing with Clojure has never been easier with these recipes by your side! Style and approach This book takes a recipe-based approach by diving directly into helpful programming concepts. It will give you a foolproof approach to programming and teach you how to deal with problems that may arise while working with Clojure. The book is divided into three sections giving you the freedom skip to the section of your choice depending on the problem faced.

Download or read book Kafka The Definitive Guide written by Neha Narkhede and published by "O'Reilly Media, Inc.". This book was released on 2017-08-31 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to take full advantage of Apache Kafka, the distributed, publish-subscribe queue for handling real-time data feeds. With this comprehensive book, you will understand how Kafka works and how it is designed. Authors Neha Narkhede, Gwen Shapira, and Todd Palino show you how to deploy production Kafka clusters; secure, tune, and monitor them; write rock-solid applications that use Kafka; and build scalable stream-processing applications. Learn how Kafka compares to other queues, and where it fits in the big data ecosystem. Dive into Kafka's internal designPick up best practices for developing applications that use Kafka. Understand the best way to deploy Kafka in production monitoring, tuning, and maintenance tasks. Learn how to secure a Kafka cluster.

Download or read book Artificial Intelligence for IoT Cookbook written by Michael Roshak and published by Packt Publishing Ltd. This book was released on 2021-03-05 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Implement machine learning and deep learning techniques to perform predictive analytics on real-time IoT data Key FeaturesDiscover quick solutions to common problems that you'll face while building smart IoT applicationsImplement advanced techniques such as computer vision, NLP, and embedded machine learningBuild, maintain, and deploy machine learning systems to extract key insights from IoT dataBook Description Artificial intelligence (AI) is rapidly finding practical applications across a wide variety of industry verticals, and the Internet of Things (IoT) is one of them. Developers are looking for ways to make IoT devices smarter and to make users' lives easier. With this AI cookbook, you'll be able to implement smart analytics using IoT data to gain insights, predict outcomes, and make informed decisions, along with covering advanced AI techniques that facilitate analytics and learning in various IoT applications. Using a recipe-based approach, the book will take you through essential processes such as data collection, data analysis, modeling, statistics and monitoring, and deployment. You'll use real-life datasets from smart homes, industrial IoT, and smart devices to train and evaluate simple to complex models and make predictions using trained models. Later chapters will take you through the key challenges faced while implementing machine learning, deep learning, and other AI techniques, such as natural language processing (NLP), computer vision, and embedded machine learning for building smart IoT systems. In addition to this, you'll learn how to deploy models and improve their performance with ease. By the end of this book, you'll be able to package and deploy end-to-end AI apps and apply best practice solutions to common IoT problems. What you will learnExplore various AI techniques to build smart IoT solutions from scratchUse machine learning and deep learning techniques to build smart voice recognition and facial detection systemsGain insights into IoT data using algorithms and implement them in projectsPerform anomaly detection for time series data and other types of IoT dataImplement embedded systems learning techniques for machine learning on small devicesApply pre-trained machine learning models to an edge deviceDeploy machine learning models to web apps and mobile using TensorFlow.js and JavaWho this book is for If you're an IoT practitioner looking to incorporate AI techniques to build smart IoT solutions without having to trawl through a lot of AI theory, this AI IoT book is for you. Data scientists and AI developers who want to build IoT-focused AI solutions will also find this book useful. Knowledge of the Python programming language and basic IoT concepts is required to grasp the concepts covered in this artificial intelligence book more effectively.

Download or read book Apache Spark for Data Science Cookbook written by Padma Priya Chitturi and published by Packt Publishing Ltd. This book was released on 2016-12-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book Use Apache Spark for data processing with these hands-on recipes Implement end-to-end, large-scale data analysis better than ever before Work with powerful libraries such as MLLib, SciPy, NumPy, and Pandas to gain insights from your data Who This Book Is For This book is for novice and intermediate level data science professionals and data analysts who want to solve data science problems with a distributed computing framework. Basic experience with data science implementation tasks is expected. Data science professionals looking to skill up and gain an edge in the field will find this book helpful. What You Will Learn Explore the topics of data mining, text mining, Natural Language Processing, information retrieval, and machine learning. Solve real-world analytical problems with large data sets. Address data science challenges with analytical tools on a distributed system like Spark (apt for iterative algorithms), which offers in-memory processing and more flexibility for data analysis at scale. Get hands-on experience with algorithms like Classification, regression, and recommendation on real datasets using Spark MLLib package. Learn about numerical and scientific computing using NumPy and SciPy on Spark. Use Predictive Model Markup Language (PMML) in Spark for statistical data mining models. In Detail Spark has emerged as the most promising big data analytics engine for data science professionals. The true power and value of Apache Spark lies in its ability to execute data science tasks with speed and accuracy. Spark's selling point is that it combines ETL, batch analytics, real-time stream analysis, machine learning, graph processing, and visualizations. It lets you tackle the complexities that come with raw unstructured data sets with ease. This guide will get you comfortable and confident performing data science tasks with Spark. You will learn about implementations including distributed deep learning, numerical computing, and scalable machine learning. You will be shown effective solutions to problematic concepts in data science using Spark's data science libraries such as MLLib, Pandas, NumPy, SciPy, and more. These simple and efficient recipes will show you how to implement algorithms and optimize your work. Style and approach This book contains a comprehensive range of recipes designed to help you learn the fundamentals and tackle the difficulties of data science. This book outlines practical steps to produce powerful insights into Big Data through a recipe-based approach.

Download or read book PySpark SQL Recipes written by Raju Kumar Mishra and published by Apress. This book was released on 2019-03-18 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation summarization, and exploratory analysis. You will improve your skills in graph data analysis using graphframes and see how to optimize your PySpark SQL code. PySpark SQL Recipes starts with recipes on creating dataframes from different types of data source, data aggregation and summarization, and exploratory data analysis using PySpark SQL. You’ll also discover how to solve problems in graph analysis using graphframes. On completing this book, you’ll have ready-made code for all your PySpark SQL tasks, including creating dataframes using data from different file formats as well as from SQL or NoSQL databases. What You Will Learn Understand PySpark SQL and its advanced features Use SQL and HiveQL with PySpark SQL Work with structured streaming Optimize PySpark SQL Master graphframes and graph processing Who This Book Is ForData scientists, Python programmers, and SQL programmers.

Download or read book Akka Cookbook written by Hector Veiga Ortiz and published by Packt Publishing Ltd. This book was released on 2017-05-26 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use the Akka framework to build effective applications in Scala About This Book Covers a discussion on Lagom—the newest launched Akka framework that is built to create complex microservices easily The recipe approach of the book allows the reader to know important and independent concepts of Scala and Akka in a seamless manner Provides a comprehensive understanding of the Akka actor model and implementing it to create reactive web applications Who This Book Is For If you are a Scala developer who wants to build scalable and concurrent applications, then this book is for you. Basic knowledge of Akka will help you take advantage of this book. What You Will Learn Control an actor using the ContolAware mailbox Test a fault-tolerant application using the Akka test kit Create a parallel application using futures and agents Package and deploy Akka application inside Docker Deploy remote actors programmatically on different nodes Integrate Streams with Akka actors Install Lagom and create a Lagom project In Detail Akka is an open source toolkit that simplifies the construction of distributed and concurrent applications on the JVM. This book will teach you how to develop reactive applications in Scala using the Akka framework. This book will show you how to build concurrent, scalable, and reactive applications in Akka. You will see how to create high performance applications, extend applications, build microservices with Lagom, and more. We will explore Akka's actor model and show you how to incorporate concurrency into your applications. The book puts a special emphasis on performance improvement and how to make an application available for users. We also make a special mention of message routing and construction. By the end of this book, you will be able to create a high-performing Scala application using the Akka framework. Style and approach This highly practical recipe-based approach will allow you to build scalable, robust, and reactive applications using the Akka framework.

Download or read book Elasticsearch 8 x Cookbook written by Alberto Paro and published by Packt Publishing Ltd. This book was released on 2022-05-27 with total page 750 pages. Available in PDF, EPUB and Kindle. Book excerpt: Search, analyze, store and manage data effectively with Elasticsearch 8.x Key Features • Explore the capabilities of Elasticsearch 8.x with easy-to-follow recipes • Extend the Elasticsearch functionalities and learn how to deploy on Elastic Cloud • Deploy and manage simple Elasticsearch nodes as well as complex cluster topologies Book Description Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics. The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch and create efficient data applications powered by enhanced functionalities and custom plugins. By the end of this Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch. What you will learn • Become well-versed with the capabilities of X-Pack • Optimize search results by executing analytics aggregations • Get to grips with using text and numeric queries as well as relationship and geo queries • Install Kibana to monitor clusters and extend it for plugins • Build complex queries by managing indices and documents • Monitor the performance of your cluster and nodes • Design advanced mapping to take full control of index steps • Integrate Elasticsearch in Java, Scala, Python, and big data applications Who this book is for If you're a software engineer, big data infrastructure engineer, or Elasticsearch developer, you'll find this Elasticsearch book useful. The book will also help data professionals working in e-commerce and FMCG industries who use Elastic for metrics evaluation and search analytics to gain deeper insights and make better business decisions. Prior experience with Elasticsearch will help you get the most out of this book.