Data for Streaming Analytics

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'); $(document.body).append('
loading reading lists ...
'); function adjustReadingListIcon(isInReadingList){ $readingListToggle.toggleClass("fa-plus", !isInReadingList); $readingListToggle.toggleClass("fa-check", isInReadingList); var tooltipMessage = isInReadingList ? "edit in reading lists" : "add to reading list"; $readingListToggle.attr("title", tooltipMessage); $readingListToggle.attr("data-original-title", tooltipMessage); } $.ajax({ url: "/readingList/isInReadingList", data: { productId: 3759 } }).done(function (data) { adjustReadingListIcon(data && data.hasProductInReadingList); }).catch(function(e){ console.log(e); adjustReadingListIcon(false); }); $readingListToggle.on("click", function(){ if(codePromise == null){ showToast() } loadCode().then(function(store){ store.requestReadingListSpecificationForProduct({ id: window.readingListsServerVars.externalId, manningId: window.readingListsServerVars.productId, title: window.readingListsServerVars.title }); ReadingLists.ReactDOM.render( ReadingLists.React.createElement(ReadingLists.ManningOnlineReadingListModal, { store: store, }), document.getElementById("reading-lists-modal") ); }).catch(function(e){ console.log("Error loading code reading list code"); }); }); var codePromise var readingListStore function loadCode(){ if(codePromise) { return codePromise } return codePromise = new Promise(function (resolve, reject){ $.getScript(window.readingListsServerVars.libraryLocation).done(function(){ hideToast() readingListStore = new ReadingLists.ReadingListStore( new ReadingLists.ReadingListProvider( new ReadingLists.ReadingListWebProvider( ReadingLists.SourceApp.marketplace, getDeploymentType() ) ) ); readingListStore.onReadingListChange(handleChange); readingListStore.onReadingListModalChange(handleChange); resolve(readingListStore); }).catch(function(){ hideToast(); console.log("Error downloading reading lists source"); $readingListToggle.css("display", "none"); reject(); }); }); } function handleChange(){ if(readingListStore != null) { adjustReadingListIcon(readingListStore.isInAtLeastOneReadingList({ id: window.readingListsServerVars.externalId, manningId: window.readingListsServerVars.productId })); } } var $readingListToast = $("#reading-list-toast"); function showToast(){ $readingListToast.css("display", "flex"); setTimeout(function(){ $readingListToast.addClass("shown"); }, 16); } function hideToast(){ $readingListToast.removeClass("shown"); setTimeout(function(){ $readingListToast.css("display", "none"); }, 150); } function getDeploymentType(){ switch(window.readingListsServerVars.deploymentType){ case "development": case "test": return ReadingLists.DeploymentType.dev; case "qa": return ReadingLists.DeploymentType.qa; case "production": return ReadingLists.DeploymentType.prod; case "docker": return ReadingLists.DeploymentType.docker; default: console.error("Unknown deployment environment, defaulting to production"); return ReadingLists.DeploymentType.prod; } } }); } });
prerequisites
Basic understanding of Apache Flink and its stream processing capabilities • Familiarity with real-time analytics concepts • Knowledge of AWS services for data orchestration and monitoring
skills learned
Setting up Apache Flink and Apache Zeppelin for real-time stream processing • Automating infrastructure setup with IaC templates for Flink and Zeppelin • Building real-time streaming analytics solutions using Apache Flink • Deploying and integrating streaming analytics pipelines with AWS services • Monitoring and scaling streaming analytics solutions to ensure reliability and performance

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team

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Look inside

In this liveProject, you'll harness the power of Apache Flink to build a real-time data transformation pipeline for Nexstellar Corp. You'll master reading data from Amazon Kinesis using an enhanced fan-out configuration, write SQL queries in Apache Zeppelin, and create real-time visualizations. Your challenge: Deploy a fully operational streaming analytics application on AWS, starting from a Zeppelin notebook, and conduct a comprehensive comparison between AWS Glue Streaming and Apache Flink.

This project uses Amazon Web Services, which should cost less than 7 USD for the whole project, including cleanup.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

project author

Gianluigi Mucciolo
Gianluigi Mucciolo is a highly skilled computer engineer who specializes in AWS technologies and agile methodologies. As an AWS Authorized Instructor and Cloud Technical Principal, he is dedicated to advancing cloud professionals’ knowledge and participates in community-building initiatives. With a strong background in Artificial Intelligence and Big Data, Gianluigi constantly seeks growth opportunities. A team player, he excels in both collaborative and independent work settings. In his free time, Gianluigi enjoys intellectual discussions, reading, and connecting with nature for inspiration.

prerequisites

This liveProject is for engineers who want to build a Data Lake Lambda architecture with AWS Fully Managed Services. To begin this liveProject, you will need to know:


TOOLS
  • Basics of Amazon Web Services
  • Basic of SQL
TECHNIQUES
  • Basics of Infrastructure Automation
  • Basics of Lambda Architecture

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Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.
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  • Data for Streaming Analytics project for free
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