Databricks Certified Associate Developer for Apache Spark Using Python - Shah, Saba

Résumé :
Learn the concepts and exercises needed to confidently prepare for the Databricks Associate Developer for Apache Spark 3.0 exam and validate your Spark skills with an industry-recognized credential Key Features: - Understand the fundamentals of Apache Spark to design robust and fast Spark applications - Explore various data manipulation components for each phase of your data engineering project - Prepare for the certification exam with sample questions and mock exams - Purchase of the print or Kindle book includes a free PDF eBook Book Description: Spark has become a de facto standard for big data processing. Migrating data processing to Spark saves resources, streamlines your business focus, and modernizes workloads, creating new business opportunities through Spark's advanced capabilities. Written by a senior solutions architect at Databricks, with experience in leading data science and data engineering teams in Fortune 500s as well as startups, this book is your exhaustive guide to achieving the Databricks Certified Associate Developer for Apache Spark certification on your first attempt. You'll explore the core components of Apache Spark, its architecture, and its optimization, while familiarizing yourself with the Spark DataFrame API and its components needed for data manipulation. You'll also find out what Spark streaming is and why it's important for modern data stacks, before learning about machine learning in Spark and its different use cases. What's more, you'll discover sample questions at the end of each section along with two mock exams to help you prepare for the certification exam. By the end of this book, you'll know what to expect in the exam and gain enough understanding of Spark and its tools to pass the exam. You'll also be able to apply this knowledge in a real-world setting and take your skillset to the next level. What You Will Learn: - Create and manipulate SQL queries in Apache Spark - Build complex Spark functions using Spark's user-defined functions (UDFs) - Architect big data apps with Spark fundamentals for optimal design - Apply techniques to manipulate and optimize big data applications - Develop real-time or near-real-time applications using Spark Streaming - Work with Apache Spark for machine learning applications Who this book is for: This book is for data professionals such as data engineers, data analysts, BI developers, and data scientists looking for a comprehensive resource to achieve Databricks Certified Associate Developer certification, as well as for individuals who want to venture into the world of big data and data engineering. Although working knowledge of Python is required, no prior knowledge of Spark is necessary. Additionally, experience with Pyspark will be beneficial. Table of Contents - Overview of Certification Guide and Exam - Understanding Apache Spark and Its Applications - Spark Architecture & Transformations - Spark Datarames and its Operations - Advanced Operations in Spark - SQL Queries in Spark - Structured Streaming in Spark - Machine Learning with Spark ML - Mock Test...

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Sommaire:
Learn the concepts and exercises needed to get certified as a Databricks Associate Developer for Apache Spark 3.0 and validate your skills as a Spark expert with an industry-recognized credential Key Features - Understand the fundamentals of Apache Spark to help you design robust and fast Spark applications - Delve into various data manipulation components for each phase of your data engineering project - Prepare for the certification exam with sample questions and mock exams, and get closer to your goal - Purchase of the print or Kindle book includes a free PDF eBook Book Description With extensive data being collected every second, computing power cannot keep up with this pace of rapid growth. To make use of all the data, Spark has become a de facto standard for big data processing. Migrating data processing to Spark will not only help you save resources that will allow you to focus on your business, but also enable you to modernize your workloads by leveraging the capabilities of Spark and the modern technology stack for creating new business opportunities. This book is a comprehensive guide that lets you explore the core components of Apache Spark, its architecture, and its optimization. You'll become familiar with the Spark dataframe API and its components needed for data manipulation. Next, you'll find out what Spark streaming is and why it's important for modern data stacks, before learning about machine learning in Spark and its different use cases. What's more, you'll discover sample questions at the end of each section along with two mock exams to help you prepare for the certification exam. By the end of this book, you'll know what to expect in the exam and how to pass it with enough understanding of Spark and its tools. You'll also be able to apply this knowledge in a real-world setting and take your skillset to the next level. What you will learn - Create and manipulate SQL queries in Spark - Build complex Spark functions using Spark UDFs - Architect big data apps with Spark fundamentals for optimal design - Apply techniques to manipulate and optimize big data applications - Build real-time or near-real-time applications using Spark Streaming - Work with Apache Spark for machine learning applications Who this book is for This book is for you if you're a professional looking to venture into the world of big data and data engineering, a data professional who wants to endorse your knowledge of Spark, or a student. Although working knowledge of Python is required, no prior Spark knowledge is needed. Additionally, experience with Pyspark will be beneficial. Table of Contents - Overview of Certification Guide and Exam - Understanding Apache Spark and Its Applications - Spark Architecture & Transformations - Spark Datarames and its Operations - Advanced Operations in Spark - SQL Queries in Spark - Structured Streaming in Spark - Machine Learning with Spark ML - Mock Test...