Delta Lake The Definitive Guide

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Delta Lake The Definitive Guide

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Author : Denny Lee
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-30

Delta Lake The Definitive Guide written by Denny Lee and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-30 with Computers categories.

Ready to simplify the process of building data lakehouses and data pipelines at scale? In this practical guide, learn how Delta Lake is helping data engineers, data scientists, and data analysts overcome key data reliability challenges with modern data engineering and management techniques. Authors Denny Lee, Tristen Wentling, Scott Haines, and Prashanth Babu (with contributions from Delta Lake maintainer R. Tyler Croy) share expert insights on all things Delta Lake--including how to run batch and streaming jobs concurrently and accelerate the usability of your data. You'll also uncover how ACID transactions bring reliability to data lakehouses at scale. This book helps you: Understand key data reliability challenges and how Delta Lake solves them Explain the critical role of Delta transaction logs as a single source of truth Learn the Delta Lake ecosystem with technologies like Apache Flink, Kafka, and Trino Architect data lakehouses with the medallion architecture Optimize Delta Lake performance with features like deletion vectors and liquid clustering

Delta Lake

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Author : Denny Lee
language : en
Publisher:
Release Date : 2022

Delta Lake written by Denny Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.

Analysis and machine learning models are only as good as the data they're built on. Querying processed data and getting insights from it requires a robust data pipeline--and an effective storage solution that ensures data quality, data integrity, and performance. This guide introduces you to Delta Lake, an open-source format that enables building a lakehouse architecture on top of existing storage systems such as S3, ADLS, GCS, and HDFS. Delta Lake enhances Apache Spark and makes it easy to store and manage massive amounts of complex data by supporting data integrity, data quality, and performance. Data engineers, data scientists, and data practitioners will learn how to build reliable data lakes and data pipelines at scale using Delta Lake. Understand key data reliability challenges and how to tackle them Learn how to use Delta Lake to realize data reliability improvements Concurrently run streaming and batch jobs against your data lake Execute update, delete, and merge commands against your data lake Use time travel to roll back and examine previous versions of your data Learn best practices to build effective, high-quality end-to-end data pipelines for real world use cases Integrate with other data technologies like Presto, Athena, Redshift and other BI tools Learn how thousands of companies are processing exabytes of data per month with their lakehouse architecture using Delta Lake.

The Definitive Guide To Data Integration

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Author : Pierre-Yves BONNEFOY
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-03-29

The Definitive Guide To Data Integration written by Pierre-Yves BONNEFOY and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-29 with Computers categories.

Learn the essentials of data integration with this comprehensive guide, covering everything from sources to solutions, and discover the key to making the most of your data stack Key Features Learn how to leverage modern data stack tools and technologies for effective data integration Design and implement data integration solutions with practical advice and best practices Focus on modern technologies such as cloud-based architectures, real-time data processing, and open-source tools and technologies Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe Definitive Guide to Data Integration is an indispensable resource for navigating the complexities of modern data integration. Focusing on the latest tools, techniques, and best practices, this guide helps you master data integration and unleash the full potential of your data. This comprehensive guide begins by examining the challenges and key concepts of data integration, such as managing huge volumes of data and dealing with the different data types. You’ll gain a deep understanding of the modern data stack and its architecture, as well as the pivotal role of open-source technologies in shaping the data landscape. Delving into the layers of the modern data stack, you’ll cover data sources, types, storage, integration techniques, transformation, and processing. The book also offers insights into data exposition and APIs, ingestion and storage strategies, data preparation and analysis, workflow management, monitoring, data quality, and governance. Packed with practical use cases, real-world examples, and a glimpse into the future of data integration, The Definitive Guide to Data Integration is an essential resource for data eclectics. By the end of this book, you’ll have the gained the knowledge and skills needed to optimize your data usage and excel in the ever-evolving world of data.What you will learn Discover the evolving architecture and technologies shaping data integration Process large data volumes efficiently with data warehousing Tackle the complexities of integrating large datasets from diverse sources Harness the power of data warehousing for efficient data storage and processing Design and optimize effective data integration solutions Explore data governance principles and compliance requirements Who this book is for This book is perfect for data engineers, data architects, data analysts, and IT professionals looking to gain a comprehensive understanding of data integration in the modern era. Whether you’re a beginner or an experienced professional enhancing your knowledge of the modern data stack, this definitive guide will help you navigate the data integration landscape.

Data Engineering With Apache Spark Delta Lake And Lakehouse

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Author : Manoj Kukreja
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-10-22

Data Engineering With Apache Spark Delta Lake And Lakehouse written by Manoj Kukreja and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-22 with Computers categories.

Understand the complexities of modern-day data engineering platforms and explore strategies to deal with them with the help of use case scenarios led by an industry expert in big data Key FeaturesBecome well-versed with the core concepts of Apache Spark and Delta Lake for building data platformsLearn how to ingest, process, and analyze data that can be later used for training machine learning modelsUnderstand how to operationalize data models in production using curated dataBook Description In the world of ever-changing data and schemas, it is important to build data pipelines that can auto-adjust to changes. This book will help you build scalable data platforms that managers, data scientists, and data analysts can rely on. Starting with an introduction to data engineering, along with its key concepts and architectures, this book will show you how to use Microsoft Azure Cloud services effectively for data engineering. You'll cover data lake design patterns and the different stages through which the data needs to flow in a typical data lake. Once you've explored the main features of Delta Lake to build data lakes with fast performance and governance in mind, you'll advance to implementing the lambda architecture using Delta Lake. Packed with practical examples and code snippets, this book takes you through real-world examples based on production scenarios faced by the author in his 10 years of experience working with big data. Finally, you'll cover data lake deployment strategies that play an important role in provisioning the cloud resources and deploying the data pipelines in a repeatable and continuous way. By the end of this data engineering book, you'll know how to effectively deal with ever-changing data and create scalable data pipelines to streamline data science, ML, and artificial intelligence (AI) tasks. What you will learnDiscover the challenges you may face in the data engineering worldAdd ACID transactions to Apache Spark using Delta LakeUnderstand effective design strategies to build enterprise-grade data lakesExplore architectural and design patterns for building efficient data ingestion pipelinesOrchestrate a data pipeline for preprocessing data using Apache Spark and Delta Lake APIsAutomate deployment and monitoring of data pipelines in productionGet to grips with securing, monitoring, and managing data pipelines models efficientlyWho this book is for This book is for aspiring data engineers and data analysts who are new to the world of data engineering and are looking for a practical guide to building scalable data platforms. If you already work with PySpark and want to use Delta Lake for data engineering, you'll find this book useful. Basic knowledge of Python, Spark, and SQL is expected.

Snowflake The Definitive Guide

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Author : Joyce Kay Avila
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-08-11

Snowflake The Definitive Guide written by Joyce Kay Avila and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-11 with Computers categories.

Snowflake's ability to eliminate data silos and run workloads from a single platform creates opportunities to democratize data analytics, allowing users at all levels within an organization to make data-driven decisions. Whether you're an IT professional working in data warehousing or data science, a business analyst or technical manager, or an aspiring data professional wanting to get more hands-on experience with the Snowflake platform, this book is for you. You'll learn how Snowflake users can build modern integrated data applications and develop new revenue streams based on data. Using hands-on SQL examples, you'll also discover how the Snowflake Data Cloud helps you accelerate data science by avoiding replatforming or migrating data unnecessarily. You'll be able to: Efficiently capture, store, and process large amounts of data at an amazing speed Ingest and transform real-time data feeds in both structured and semistructured formats and deliver meaningful data insights within minutes Use Snowflake Time Travel and zero-copy cloning to produce a sensible data recovery strategy that balances system resilience with ongoing storage costs Securely share data and reduce or eliminate data integration costs by accessing ready-to-query datasets available in the Snowflake Marketplace

Trino The Definitive Guide

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Author : Matt Fuller
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-10-03

Trino The Definitive Guide written by Matt Fuller and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-03 with Computers categories.

Perform fast interactive analytics against different data sources using the Trino high-performance distributed SQL query engine. In the second edition of this practical guide, you'll learn how to conduct analytics on data where it lives, whether it's a data lake using Hive, a modern lakehouse with Iceberg or Delta Lake, a different system like Cassandra, Kafka, or SingleStore, or a relational database like PostgreSQL or Oracle. Analysts, software engineers, and production engineers learn how to manage, use, and even develop with Trino and make it a critical part of their data platform. Authors Matt Fuller, Manfred Moser, and Martin Traverso show you how a single Trino query can combine data from multiple sources to allow for analytics across your entire organization. Explore Trino's use cases, and learn about tools that help you connect to Trino for querying and processing huge amounts of data Learn Trino's internal workings, including how to connect to and query data sources with support for SQL statements, operators, functions, and more Deploy and secure Trino at scale, monitor workloads, tune queries, and connect more applications Learn how other organizations apply Trino successfully

Apache Iceberg The Definitive Guide

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Author : Tomer Shiran
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-02

Apache Iceberg The Definitive Guide written by Tomer Shiran and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Computers categories.

Traditional data architecture patterns are severely limited. To use these patterns, you have to ETL data into each tool—a cost-prohibitive process for making warehouse features available to all of your data. The lack of flexibility with these patterns requires you to lock into a set of priority tools and formats, which creates data silos and data drift. This practical book shows you a better way. Apache Iceberg provides the capabilities, performance, scalability, and savings that fulfill the promise of an open data lakehouse. By following the lessons in this book, you'll be able to achieve interactive, batch, machine learning, and streaming analytics with this high-performance open source format. Authors Tomer Shiran, Jason Hughes, and Alex Merced from Dremio show you how to get started with Iceberg. With this book, you'll learn: The architecture of Apache Iceberg tables What happens under the hood when you perform operations on Iceberg tables How to further optimize Iceberg tables for maximum performance How to use Iceberg with popular data engines such as Apache Spark, Apache Flink, and Dremio Discover why Apache Iceberg is a foundational technology for implementing an open data lakehouse.

Practical Lakehouse Architecture

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Author : Gaurav Ashok Thalpati
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-07-24

Practical Lakehouse Architecture written by Gaurav Ashok Thalpati and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.

This concise yet comprehensive guide explains how to adopt a data lakehouse architecture to implement modern data platforms. It reviews the design considerations, challenges, and best practices for implementing a lakehouse and provides key insights into the ways that using a lakehouse can impact your data platform, from managing structured and unstructured data and supporting BI and AI/ML use cases to enabling more rigorous data governance and security measures. Practical Lakehouse Architecture shows you how to: Understand key lakehouse concepts and features like transaction support, time travel, and schema evolution Understand the differences between traditional and lakehouse data architectures Differentiate between various file formats and table formats Design lakehouse architecture layers for storage, compute, metadata management, and data consumption Implement data governance and data security within the platform Evaluate technologies and decide on the best technology stack to implement the lakehouse for your use case Make critical design decisions and address practical challenges to build a future-ready data platform Start your lakehouse implementation journey and migrate data from existing systems to the lakehouse

Building Medallion Architectures

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Author : Piethein Strengholt
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-03-28

Building Medallion Architectures written by Piethein Strengholt and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-28 with Computers categories.

In today's data-driven world, organizations must manage and analyze vast amounts of information to deliver the insights that give them a competitive advantage. Many turn to the medallion architecture because it's a proven and well-known design. Yet implementing a robust data pipeline can be difficult, particularly when it comes to using the medallion architecture's bronze, silver, and gold layers—done wrong, it can hamper your ability to make data-driven decisions. This practical guide helps you build a medallion architecture the right way with Azure Databricks and Microsoft Fabric. Drawing on hands-on experience from the field, Piethein Strengholt demystifies common assumptions and complex problems you'll face when embarking on a new data architecture. Architects and engineers of all stripes will find answers to the most typical questions along with insights from real organizations about what's worked, what hasn't, and why. You'll learn: Lakehouse and medallion architecture fundamentals and key concepts Design considerations for Azure Databricks and Microsoft Fabric Scaling considerations, including governance, security, automation, and more How to make informed decisions when designing or implementing new data architectures Proven patterns for success that align with broader organizational objectives

Data Engineering Design Patterns

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Author : Bartosz Konieczny
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-09

Data Engineering Design Patterns written by Bartosz Konieczny and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-09 with Computers categories.

Data projects are an intrinsic part of an organization’s technical ecosystem, but data engineers in many companies continue to work on problems that others have already solved. This hands-on guide shows you how to provide valuable data by focusing on various aspects of data engineering, including data ingestion, data quality, idempotency, and more. Author Bartosz Konieczny guides you through the process of building reliable end-to-end data engineering projects, from data ingestion to data observability, focusing on data engineering design patterns that solve common business problems in a secure and storage-optimized manner. Each pattern includes a user-facing description of the problem, solutions, and consequences that place the pattern into the context of real-life scenarios. Throughout this journey, you’ll use open source data tools and public cloud services to apply each pattern. You'll learn: Challenges data engineers face and their impact on data systems How these challenges relate to data system components Useful applications of data engineering patterns How to identify and fix issues with your current data components TTechnology-agnostic solutions to new and existing data projects, with open source implementation examples Bartosz Konieczny is a freelance data engineer who's been coding since 2010. He's held various senior hands-on positions that allowed him to work on many data engineering problems in batch and stream processing.