Modern data engineering with Apache Spark: a hands-on guide for building mission-critical streaming applications
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...
Gespeichert in:
| Beteilige Person: | |
|---|---|
| Format: | Buch |
| Sprache: | Englisch |
| Veröffentlicht: |
Berkeley, CA
Apress
[2022]
|
| Ausgabe: | 1st ed |
| Schlagwörter: | |
| Zusammenfassung: | 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 compile reusable 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 Kubernetes.Reading this book will empower you to take advantage of Apache Spark to optimize your data pipelines and teach you to craft modular and testable Spark applications. You will create and deploy mission-critical streaming spark applications in a low-stress environment that paves the way for your own path to production.What You Will Learn - Simplify data transformation with Spark Pipelines and Spark SQL- Bridge data engineering with machine learning- Architect modular data pipeline applications- Build reusable application components and libraries- Containerize your Spark applications for consistency and reliability- Use Docker and Kubernetes to deploy your Spark applications- Speed up application experimentation using Apache Zeppelin and Docker- Understand serializable structured data and data contracts - Harness effective strategies for optimizing data in your data lakes- Build end-to-end Spark structured streaming applications using Redis and Apache Kafka- Embrace testing for your batch and streaming applications- Deploy and monitor your Spark applications Who This Book Is ForProfessional software engineers who want to take their current skills and |
| Umfang: | xxv, 585 Seiten Diagramme 1149 grams |
| ISBN: | 9781484274514 |
Internformat
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| 520 | |a 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. | ||
| 520 | |a This book will teach you to write interactive Spark applications using Apache Zeppelin notebooks, write and compile reusable 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 Kubernetes.Reading this book will empower you to take advantage of Apache Spark to optimize your data pipelines and teach you to craft modular and testable Spark applications. | ||
| 520 | |a You will create and deploy mission-critical streaming spark applications in a low-stress environment that paves the way for your own path to production.What You Will Learn - Simplify data transformation with Spark Pipelines and Spark SQL- Bridge data engineering with machine learning- Architect modular data pipeline applications- Build reusable application components and libraries- Containerize your Spark applications for consistency and reliability- Use Docker and Kubernetes to deploy your Spark applications- Speed up application experimentation using Apache Zeppelin and Docker- Understand serializable structured data and data contracts - Harness effective strategies for optimizing data in your data lakes- Build end-to-end Spark structured streaming applications using Redis and Apache Kafka- Embrace testing for your batch and streaming applications- Deploy and monitor your Spark applications Who This Book Is ForProfessional software engineers who want to take their current skills and | ||
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a Quantitative research | |
| 650 | 4 | |a Database management | |
| 650 | 4 | |a Data mining | |
| 650 | 4 | |a Java (Computer program language) | |
| 653 | |a Hardcover, Softcover / Informatik, EDV/Programmiersprachen | ||
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-1-4842-7452-1 |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-033584207 | |
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| id | DE-604.BV048203252 |
| illustrated | Not Illustrated |
| indexdate | 2024-12-20T19:38:20Z |
| institution | BVB |
| isbn | 9781484274514 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033584207 |
| oclc_num | 1334031132 |
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| owner | DE-29T |
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| physical | xxv, 585 Seiten Diagramme 1149 grams |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Apress |
| record_format | marc |
| spelling | Haines, Scott aut Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications Scott Haines 1st ed Berkeley, CA Apress [2022] © 2022 xxv, 585 Seiten Diagramme 1149 grams txt rdacontent n rdamedia nc rdacarrier 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 compile reusable 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 Kubernetes.Reading this book will empower you to take advantage of Apache Spark to optimize your data pipelines and teach you to craft modular and testable Spark applications. You will create and deploy mission-critical streaming spark applications in a low-stress environment that paves the way for your own path to production.What You Will Learn - Simplify data transformation with Spark Pipelines and Spark SQL- Bridge data engineering with machine learning- Architect modular data pipeline applications- Build reusable application components and libraries- Containerize your Spark applications for consistency and reliability- Use Docker and Kubernetes to deploy your Spark applications- Speed up application experimentation using Apache Zeppelin and Docker- Understand serializable structured data and data contracts - Harness effective strategies for optimizing data in your data lakes- Build end-to-end Spark structured streaming applications using Redis and Apache Kafka- Embrace testing for your batch and streaming applications- Deploy and monitor your Spark applications Who This Book Is ForProfessional software engineers who want to take their current skills and bicssc bisacsh Quantitative research Database management Data mining Java (Computer program language) Hardcover, Softcover / Informatik, EDV/Programmiersprachen Erscheint auch als Online-Ausgabe 978-1-4842-7452-1 |
| spellingShingle | Haines, Scott Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications bicssc bisacsh Quantitative research Database management Data mining Java (Computer program language) |
| title | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications |
| title_auth | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications |
| title_exact_search | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications |
| title_full | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications Scott Haines |
| title_fullStr | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications Scott Haines |
| title_full_unstemmed | Modern data engineering with Apache Spark a hands-on guide for building mission-critical streaming applications Scott Haines |
| title_short | Modern data engineering with Apache Spark |
| title_sort | modern data engineering with apache spark a hands on guide for building mission critical streaming applications |
| title_sub | a hands-on guide for building mission-critical streaming applications |
| topic | bicssc bisacsh Quantitative research Database management Data mining Java (Computer program language) |
| topic_facet | bicssc bisacsh Quantitative research Database management Data mining Java (Computer program language) |
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