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所在平台: Udemy |
课程主页: https://www.udemy.com/course/databricks-fundamentals-apache-spark-core/
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课程名称：Databricks基础与Apache Spark核心 概述：欢迎参加关于Databricks和Apache Spark 2.4及3.0.0的课程。Apache Spark是一个可以大规模处理大数据的框架。在本课程中，我们将学习如何使用Scala和SQL编写Spark应用程序。Databricks是Apache Spark的创始人创办的一家公司，提供了一个托管和优化的Apache Spark云服务版本。本课程的主要重点是教您如何使用DataFrame API和SQL完成以下任务： - 使用Databricks编写和运行Apache Spark代码 - 从Databricks文件系统（DBFS）读取和写入数据 - 解释Apache Spark在多个节点集群上的运行机制 - 使用DataFrame API和SQL进行数据操作，例如选择、重命名和处理列，过滤、删除和聚合行，连接DataFrames - 创建用户定义函数（UDF）并与DataFrame API或Spark SQL结合使用 - 将DataFrames写入外部存储系统 - 列出并解释Apache Spark执行层次结构的元素，如作业、阶段和任务 这个课程将为您提供使用Databricks和Apache Spark进行大数据处理所需的基础知识和实践技能。
Welcome to this course on Databricks and Apache Spark 2.4 and 3.0.0Apache Spark is a Big Data Processing Framework that runs at scale.In this course, we will learn how to write Spark Applications using Scala and SQL.Databricks is a company founded by the creator of Apache Spark.Databricks offers a managed and optimized version of Apache Spark that runs in the cloud.The main focus of this course is to teach you how to use the DataFrame API & SQL to accomplish tasks such as:Write and run Apache Spark code using Databricks Read and Write Data from the Databricks File System - DBFSExplain how Apache Spark runs on a cluster with multiple NodesUse the DataFrame API and SQL to perform data manipulation tasks such asSelecting, renaming and manipulating columnsFiltering, dropping and aggregating rowsJoining DataFramesCreate UDFs and use them with DataFrame API or Spark SQLWriting DataFrames to external storage systemsList and explain the element of Apache Spark execution hierarchy such asJobsStagesTasks
