Mastering Apache Hudi
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Mastering Apache Hudi
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Author : Robert Johnson
language : en
Publisher:
Release Date : 2025
Mastering Apache Hudi written by Robert Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Computers categories.
Mastering Apache Hudi
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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-06
Mastering Apache Hudi written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Computers categories.
"Mastering Apache Hudi: Building Real-Time Data Lakes" is an authoritative guide designed to equip data engineers, architects, and IT professionals with the knowledge and skills needed to leverage Apache Hudi’s powerful capabilities in managing dynamic, continuously evolving datasets. As organizations worldwide strive to harness the vast streams of real-time data for actionable insights, this book demystifies the intricacies of deploying and optimizing Hudi, turning traditional data lakes into agile, real-time analytical engines. This comprehensive resource covers a spectrum of essential topics, from the architectural components underpinning Hudi’s functionality to practical strategies for seamless integration with existing big data ecosystems. Readers will gain invaluable insights into performance tuning, schema evolution, and data governance, alongside real-world case studies that highlight industry best practices and successful Hudi implementations. With step-by-step guidance and expert insights, this book empowers professionals to transform their data infrastructures, enabling rapid and informed decision-making in a data-driven world.
Apache Hudi For Scalable Data Lakes
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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-24
Apache Hudi For Scalable Data Lakes written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.
"Apache Hudi for Scalable Data Lakes" "Apache Hudi for Scalable Data Lakes" is a comprehensive guide designed for data engineers, architects, and technical leaders seeking to harness the full potential of modern data lakes. The book opens with an exploration of the core concepts and motivations behind distributed data lake architectures, offering detailed insights into the evolution of Apache Hudi within the broader open-source ecosystem. Readers are guided through Hudi’s foundational principles, comparative positioning alongside Delta Lake and Apache Iceberg, and the unique design goals that enable workloads such as incremental processing, change data capture (CDC), and transactional ingestion. Delving deep into implementation, the book meticulously covers Hudi’s innovative storage mechanisms, including Copy-on-Write and Merge-on-Read table types, schema evolution strategies, and metadata management. Successive chapters provide hands-on guidance for efficient data ingestion—both batch and streaming—while illuminating Hudi’s transactional guarantees, scalable indexing, and best practices for tuning write and read performance. Integration with leading query engines such as Trino, Hive, Presto, and Spark SQL is addressed in detail, alongside advanced topics like time travel queries, file management, and robust failure recovery techniques. Beyond technical architecture, the text provides pragmatic approaches to scaling Hudi deployments in cloud and hybrid environments, ensuring data reliability, consistency, and high performance even at petabyte scale. With dedicated discussions on security, governance, DevOps automation, and compliance—including audit logging, encryption, GDPR controls, and continuous data quality—the book empowers practitioners to build resilient, secure, and agile data lake platforms. The final chapters engage with cutting-edge developments, community-driven extensions, and the dynamic future of Apache Hudi, making this volume an essential resource for staying ahead in the rapidly evolving world of big data.
Mastering The Modern Data Stack
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Author : Nick Jewell, PhD
language : en
Publisher: TinyTechMedia LLC
Release Date : 2023-09-28
Mastering The Modern Data Stack written by Nick Jewell, PhD and has been published by TinyTechMedia LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-28 with Computers categories.
In the age of digital transformation, becoming overwhelmed by the sheer volume of potential data management, analytics, and AI solutions is common. Then it's all too easy to become distracted by glossy vendor marketing, and then chase the latest shiny tool, rather than focusing on building resilient, valuable platforms that will outperform the competition. This book aims to fix a glaring gap for data professionals: a comprehensive guide to the full Modern Data Stack that's rooted in real-world capabilities, not vendor hype. It is full of hard-earned advice on how to get maximum value from your investments through tangible insights, actionable strategies, and proven best practices. It comprehensively explains how the Modern Data Stack is truly utilized by today's data-driven companies. Mastering the Modern Data Stack: An Executive Guide to Unified Business Analytics is crafted for a diverse audience. It's for business and technology leaders who understand the importance and potential value of data, analytics, and AI—but don’t quite see how it all fits together in the big picture. It's for enterprise architects and technology professionals looking for a primer on the data analytics domain, including definitions of essential components and their usage patterns. It's also for individuals early in their data analytics careers who wish to have a practical and jargon-free understanding of how all the gears and pulleys move behind the scenes in a Modern Data Stack to turn data into actual business value. Whether you're starting your data journey with modest resources, or implementing digital transformation in the cloud, you'll find that this isn't just another textbook on data tools or a mere overview of outdated systems. It's a powerful guide to efficient, modern data management and analytics, with a firm focus on emerging technologies such as data science, machine learning, and AI. If you want to gain a competitive advantage in today’s fast-paced digital world, this TinyTechGuide™ is for you. Remember, it’s not the tech that’s tiny, just the book!™
Mastering Aws
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2023-09-06
Mastering Aws written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-06 with Computers categories.
Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.
Mastering Databases Concepts Design And Applications
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Author : Dr. Sunil Kumar Mishra
language : en
Publisher: Chyren Publication
Release Date : 2025-05-17
Mastering Databases Concepts Design And Applications written by Dr. Sunil Kumar Mishra and has been published by Chyren Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-17 with Antiques & Collectibles categories.
Mastering Data Engineering And Analytics With Databricks
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Author : Manoj Kumar
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2024-09-30
Mastering Data Engineering And Analytics With Databricks written by Manoj Kumar and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-30 with Computers categories.
TAGLINE Master Databricks to Transform Data into Strategic Insights for Tomorrow’s Business Challenges KEY FEATURES ● Combines theory with practical steps to master Databricks, Delta Lake, and MLflow. ● Real-world examples from FMCG and CPG sectors demonstrate Databricks in action. ● Covers real-time data processing, ML integration, and CI/CD for scalable pipelines. ● Offers proven strategies to optimize workflows and avoid common pitfalls. DESCRIPTION In today’s data-driven world, mastering data engineering is crucial for driving innovation and delivering real business impact. Databricks is one of the most powerful platforms which unifies data, analytics and AI requirements of numerous organizations worldwide. Mastering Data Engineering and Analytics with Databricks goes beyond the basics, offering a hands-on, practical approach tailored for professionals eager to excel in the evolving landscape of data engineering and analytics. This book uniquely blends foundational knowledge with advanced applications, equipping readers with the expertise to build, optimize, and scale data pipelines that meet real-world business needs. With a focus on actionable learning, it delves into complex workflows, including real-time data processing, advanced optimization with Delta Lake, and seamless ML integration with MLflow—skills critical for today’s data professionals. Drawing from real-world case studies in FMCG and CPG industries, this book not only teaches you how to implement Databricks solutions but also provides strategic insights into tackling industry-specific challenges. From setting up your environment to deploying CI/CD pipelines, you'll gain a competitive edge by mastering techniques that are directly applicable to your organization’s data strategy. By the end, you’ll not just understand Databricks—you’ll command it, positioning yourself as a leader in the data engineering space. WHAT WILL YOU LEARN ● Design and implement scalable, high-performance data pipelines using Databricks for various business use cases. ● Optimize query performance and efficiently manage cloud resources for cost-effective data processing. ● Seamlessly integrate machine learning models into your data engineering workflows for smarter automation. ● Build and deploy real-time data processing solutions for timely and actionable insights. ● Develop reliable and fault-tolerant Delta Lake architectures to support efficient data lakes at scale. WHO IS THIS BOOK FOR? This book is designed for data engineering students, aspiring data engineers, experienced data professionals, cloud data architects, data scientists and analysts looking to expand their skill sets, as well as IT managers seeking to master data engineering and analytics with Databricks. A basic understanding of data engineering concepts, familiarity with data analytics, and some experience with cloud computing or programming languages such as Python or SQL will help readers fully benefit from the book’s content. TABLE OF CONTENTS SECTION 1 1. Introducing Data Engineering with Databricks 2. Setting Up a Databricks Environment for Data Engineering 3. Working with Databricks Utilities and Clusters SECTION 2 4. Extracting and Loading Data Using Databricks 5. Transforming Data with Databricks 6. Handling Streaming Data with Databricks 7. Creating Delta Live Tables 8. Data Partitioning and Shuffling 9. Performance Tuning and Best Practices 10. Workflow Management 11. Databricks SQL Warehouse 12. Data Storage and Unity Catalog 13. Monitoring Databricks Clusters and Jobs 14. Production Deployment Strategies 15. Maintaining Data Pipelines in Production 16. Managing Data Security and Governance 17. Real-World Data Engineering Use Cases with Databricks 18. AI and ML Essentials 19. Integrating Databricks with External Tools Index
Ultimate Big Data Analytics With Apache Hadoop Master Big Data Analytics With Apache Hadoop Using Apache Spark Hive And Python
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Author : Simhadri Govindappa
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2024-09-09
Ultimate Big Data Analytics With Apache Hadoop Master Big Data Analytics With Apache Hadoop Using Apache Spark Hive And Python written by Simhadri Govindappa and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-09 with Computers categories.
Master the Hadoop Ecosystem and Build Scalable Analytics Systems Key Features● Explains Hadoop, YARN, MapReduce, and Tez for understanding distributed data processing and resource management. ● Delves into Apache Hive and Apache Spark for their roles in data warehousing, real-time processing, and advanced analytics. ● Provides hands-on guidance for using Python with Hadoop for business intelligence and data analytics. Book Description In a rapidly evolving Big Data job market projected to grow by 28% through 2026 and with salaries reaching up to $150,000 annually—mastering big data analytics with the Hadoop ecosystem is most sought after for career advancement. The Ultimate Big Data Analytics with Apache Hadoop is an indispensable companion offering in-depth knowledge and practical skills needed to excel in today's data-driven landscape. The book begins laying a strong foundation with an overview of data lakes, data warehouses, and related concepts. It then delves into core Hadoop components such as HDFS, YARN, MapReduce, and Apache Tez, offering a blend of theory and practical exercises. You will gain hands-on experience with query engines like Apache Hive and Apache Spark, as well as file and table formats such as ORC, Parquet, Avro, Iceberg, Hudi, and Delta. Detailed instructions on installing and configuring clusters with Docker are included, along with big data visualization and statistical analysis using Python. Given the growing importance of scalable data pipelines, this book equips data engineers, analysts, and big data professionals with practical skills to set up, manage, and optimize data pipelines, and to apply machine learning techniques effectively. Don’t miss out on the opportunity to become a leader in the big data field to unlock the full potential of big data analytics with Hadoop. What you will learn ● Gain expertise in building and managing large-scale data pipelines with Hadoop, YARN, and MapReduce. ● Master real-time analytics and data processing with Apache Spark’s powerful features. ● Develop skills in using Apache Hive for efficient data warehousing and complex queries. ● Integrate Python for advanced data analysis, visualization, and business intelligence in the Hadoop ecosystem. ● Learn to enhance data storage and processing performance using formats like ORC, Parquet, and Delta. ● Acquire hands-on experience in deploying and managing Hadoop clusters with Docker and Kubernetes. ● Build and deploy machine learning models with tools integrated into the Hadoop ecosystem. Table of Contents 1. Introduction to Hadoop and ASF 2. Overview of Big Data Analytics 3. Hadoop and YARN MapReduce and Tez 4. Distributed Query Engines: Apache Hive 5. Distributed Query Engines: Apache Spark 6. File Formats and Table Formats (Apache Ice-berg, Hudi, and Delta) 7. Python and the Hadoop Ecosystem for Big Data Analytics - BI 8. Data Science and Machine Learning with Hadoop Ecosystem 9. Introduction to Cloud Computing and Other Apache Projects Index
Learning Spark
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Author : Jules S. Damji
language : en
Publisher: O'Reilly Media
Release Date : 2020-07-16
Learning Spark written by Jules S. Damji and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-16 with Computers categories.
Data is bigger, arrives faster, and comes in a variety of formatsâ??and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, youâ??ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
Applied Hudi Systems
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-06-03
Applied Hudi Systems written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-03 with Computers categories.
"Applied Hudi Systems" "Applied Hudi Systems" is a comprehensive and authoritative guide to architecting, operating, and optimizing Apache Hudi for modern, large-scale data lakes. The book begins with a thorough exploration of Hudi’s architectural foundations and design philosophy, clarifying core concepts such as table abstractions (Copy-on-Write vs. Merge-on-Read), metadata management, transactional guarantees, and integration with distributed storage systems like HDFS, S3, and GCS. Readers will come away with a deep understanding of Hudi’s unique approach to reliable data storage, time-travel queries, and its positioning relative to other leading lakehouse formats. The book progresses from foundational principles to advanced engineering, covering high-throughput data ingestion using real-time and micro-batch pipelines, mutation management (upserts, deletes), data validation, and change data capture integration. Practical chapters on query processing, indexing, partitioning, clustering, and fine-grained performance tuning provide real-world strategies for achieving scalable, low-latency analytics. Detailed treatments of storage layout, compaction, lifecycle management, and cost optimization empower practitioners to build resilient and efficient Hudi-based architectures suitable for petabyte-scale deployments. Recognizing the demands of enterprise data platforms, "Applied Hudi Systems" addresses mission-critical topics such as security, governance, auditing, multi-tenancy, and disaster recovery. Readers will find comprehensive guidance on monitoring, telemetry, alerting, resource management, and extensibility with today’s data ecosystem tools (e.g., Spark, Trino, Airflow, Prometheus). The book culminates with best practices, operational playbooks, benchmark results, and in-depth case studies from production Hudi environments—making it an indispensable resource for engineers, architects, and data leaders seeking to deploy robust, future-ready data lake solutions.