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    Engineering Lakehouses with Open Table Formats. Build scalable and efficient lakehouses with Apache Iceberg, Apache Hudi, and Delta Lake Dipankar Mazumdar, Vinoth Govindarajan

    (ebook) (audiobook) (audiobook) Książka w języku 1
    Engineering Lakehouses with Open Table Formats. Build scalable and efficient lakehouses with Apache Iceberg, Apache Hudi, and Delta Lake Dipankar Mazumdar, Vinoth Govindarajan - okladka książki

    Engineering Lakehouses with Open Table Formats. Build scalable and efficient lakehouses with Apache Iceberg, Apache Hudi, and Delta Lake Dipankar Mazumdar, Vinoth Govindarajan - okladka książki

    Engineering Lakehouses with Open Table Formats. Build scalable and efficient lakehouses with Apache Iceberg, Apache Hudi, and Delta Lake Dipankar Mazumdar, Vinoth Govindarajan - audiobook MP3

    Engineering Lakehouses with Open Table Formats. Build scalable and efficient lakehouses with Apache Iceberg, Apache Hudi, and Delta Lake Dipankar Mazumdar, Vinoth Govindarajan - audiobook CD

    Autorzy:
    Dipankar Mazumdar, Vinoth Govindarajan
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Engineering Lakehouses with Open Table Formats provides detailed insights into lakehouse concepts, and dives deep into the practical implementation of open table formats such as Apache Iceberg, Apache Hudi, and Delta Lake. If you are a data engineer or architect looking to understand the intricacies of open lakehouse architectures, this book is for you.
    You'll start by exploring the internals of a table format and learn in detail about the transactional capabilities of lakehouses. You’ll also work with each table format with hands-on exercises using popular computing engines such as Apache Spark, Flink, Trino, dbt, and Python-based tools. The book addresses advanced topics, including performance optimization techniques and interoperability among different formats, equipping you to build production-ready lakehouses. With step-by-step explanations, you’ll get to grips with the key components of Lakehouse architecture and learn how to build, maintain, and optimize them.
    By the end, you'll be proficient in evaluating and implementing open table formats, optimizing lakehouse performance, and applying these concepts to real-world scenarios, ensuring you make informed decisions in selecting the right architecture for your organization’s data needs.

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    O autorach książki

    Dipankar Mazumdar is currently a Staff Data Engineer Advocate at Onehouse.ai, where he focuses on open source projects such as Apache Hudi and XTable to help engineering teams build and scale robust data analytics platforms. Before this, he worked on critical open source projects such as Apache Iceberg and Apache Arrow at Dremio. For most of his career, he worked at the intersection of data visualization and machine learning. He has also been a speaker at numerous conferences, such as Data+AI, ApacheCon, Scale By the Bay, and Data Day Texas, among others. Dipankar has a master's degree in computer science with research focused on explainable AI techniques.
    Vinoth Govindarajan is a seasoned data expert and staff software engineer at Apple Inc., where he spearheads data platforms using open-source technologies like Iceberg, Spark, Trino, and Flink. Before this, he worked on designing incremental ETL frameworks for real-time data processing at Uber. He is a dedicated contributor to the open source community in projects such as Apache Hudi and dbt-spark. As a thought leader, Vinoth has shared his expertise through speaking engagements at conferences such as dbt Coalesce and Hudi OSS community meetups. He has published numerous blogs on building open lakehouses. Holding a bachelor's degree in information technology, Vinoth has also authored multiple research papers published in journals like IEEE.

    Packt Publishing - inne książki

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