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所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-certified-associate-for-spark-30-practice-exams/
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**课程名称：** Databricks Certified Associate for Spark 3.0 模拟考试 **课程概述：** 本课程旨在帮助学员准备Databricks Certified Associate Developer for Apache Spark认证考试。考试重点考察学员对Spark DataFrame API的理解以及运用其完成基本数据处理任务的能力。具体涵盖： * **DataFrame API应用：** 列选择、重命名与操作；行过滤、删除、排序与聚合；处理缺失值；DataFrame的合并、读写与分区（包含Schema）；以及UDF（用户自定义函数）和Spark SQL函数的运用。 * **Spark架构基础：** 包括执行/部署模式、执行层级、容错机制、垃圾回收和广播机制。 通过本课程的学习，学员应能熟练使用Python或Scala完成基本的Spark DataFrame数据处理任务。 **考试内容分布：** 考试共包含60道选择题，考试时间为120分钟。题目分布如下： * Apache Spark 架构概念：17% (10题) * Apache Spark 架构应用：11% (7题) * Apache Spark DataFrame API 应用：72% (43题)
Databricks Certified Associate Developer for Apache SparkThe Databricks Certified Associate Developer for Apache Spark certification exam assesses the understanding of the Spark DataFrame API and the ability to apply the Spark DataFrame API to complete basic data manipulation tasks within a Spark session. These tasks include selecting, renaming and manipulating columns; filtering, dropping, sorting, and aggregating rows; handling missing data; combining, reading, writing and partitioning DataFrames with schemas; and working with UDFs and Spark SQL functions. In addition, the exam will assess the basics of the Spark architecture like execution/deployment modes, the execution hierarchy, fault tolerance, garbage collection, and broadcasting. Individuals who pass this certification exam can be expected to complete basic Spark DataFrame tasks using Python or Scala.Understanding the basics of the Spark architecture, including Adaptive Query ExecutionApply the Spark DataFrame API to complete individual data manipulation task, including:selecting, renaming and manipulating columnsfiltering, dropping, sorting, and aggregating rowsjoining, reading, writing and partitioning DataFramesworking with UDFs and Spark SQL functionsThere are 60 multiple-choice questions on the certification exam. The questions will be distributed by high-level topic in the following way:Apache Spark Architecture Concepts - 17% (10/60)Apache Spark Architecture Applications - 11% (7/60)Apache Spark DataFrame API Applications - 72% (43/60)Total number of questions: 60Time limit 120 minutes Question types Multiple choiceLanguages English
