| 书目名称 | Modern Data Engineering with Apache Spark | | 副标题 | A Hands-On Guide for | | 编辑 | Scott Haines | | 视频video | | | 概述 | Provides a practical approach to data engineering through the lens of Apache Spark.Includes lessons from the author’s experience in managing massive data pipelines.Gives you a toolbox of solutions to | | 图书封面 |  | | 描述 | Leverage Apache Spark within a modern data engineering ecosystem. This hands-on guide will teach you how to write fully functional applications, follow industry best practices, and learn the rationale behind these decisions. With Apache Spark as the foundation, you will follow a step-by-step journey beginning with the basics of data ingestion, processing, and transformation, and ending up with an entire local data platform running Apache Spark, Apache Zeppelin, Apache Kafka, Redis, MySQL, Minio (S3), and Apache Airflow..Apache Spark applications solve a wide range of data problems from traditional data loading and processing to rich SQL-based analysis as well as complex machine learning workloads and even near real-time processing of streaming data. Spark fits well as a central foundation for any data engineering workload. This book will teach you to write interactive Spark applications using Apache Zeppelin notebooks, write and compilereusable applications and modules, and fully test both batch and streaming. You will also learn to containerize your applications using Docker and run and deploy your Spark applications using a variety of tools such as Apache Airflow, Docker and Kube | | 出版日期 | Book 2022 | | 关键词 | Apache Spark; Data Engineering; Data Modeling; Data Pipelines; Data Architecture; Streaming Data; Big Data | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4842-7452-1 | | isbn_softcover | 978-1-4842-7451-4 | | isbn_ebook | 978-1-4842-7452-1 | | copyright | Scott Haines 2022 |
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发表于 2025-3-21 18:03:59
