Coursera 笔记

IBM

Introduction to Big Data with Spark and Hadoop

Spark 与 Hadoop 大数据入门

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Module 01

What Is Big Data?

13 篇
  1. 01Course Introduction大数据、Hadoop 与 Spark 入门课程
  2. 02What is Big Data?什么是大数据？
  3. 03Impact of Big Data大数据的影响
  4. 04Parallel Processing, Scaling, and Data Parallelism大数据的并行处理与可扩展性
  5. 05Big Data Tools and Ecosystem大数据工具与生态系统
  6. 06Open Source and Big Data开源与大数据
  7. 07Beyond the Hype超越炒作：大数据的真相
  8. 08Big Data Use Cases大数据应用案例
  9. 09Introduction to Emerging Big Data Technologies新兴大数据技术导论
  10. 10Summary and Highlights: Introduction to Big Data摘要和重点：大数据导论
  11. 11Practice Quiz: Introduction to Big Data练习测验：大数据导论
  12. 12Module 1 Glossary: What Is Big Data?模块 1 词汇表：什么是大数据？
  13. 13Graded Quiz: What Is Big Data?评分测验：什么是大数据？
Module 02

Introduction to the Hadoop Ecosystem

14 篇
  1. 01Introduction to HadoopHadoop 简介
  2. 02Intro to MapReduceMapReduce 简介
  3. 03Hadoop EcosystemHadoop 生态系统
  4. 04HDFSHadoop 分布式文件系统
  5. 05HIVEHive 数据仓库
  6. 06Hands-on Lab: Getting Started with Hive实践实验室：初识 Hive
  7. 07HBASEHBase 列式数据库
  8. 08Hands-on Lab: Hadoop MapReduce动手实验：Hadoop MapReduce
  9. 09Hands-on Lab: Hadoop Cluster (Optional)实践实验：Hadoop 集群（可选）
  10. 10Summary and Highlights: Introduction to Hadoop摘要和重点：Hadoop 简介
  11. 11Practice Quiz: Introduction to Hadoop练习测验：Hadoop 简介
  12. 12Cheat Sheet: Introduction to the Hadoop Ecosystem速查表：Hadoop 生态系统简介
  13. 13Module 2 Glossary: Introduction to the Hadoop Ecosystem模块 2 词汇表：Hadoop 生态系统简介
  14. 14Graded Quiz: Introduction to Hadoop Ecosystem评分测验：Hadoop 生态系统简介
Module 03

Apache Spark

12 篇
  1. 01Why use Apache Spark?为什么使用 Apache Spark？
  2. 02Functional Programming Basics函数式编程基础
  3. 03Parallel Programming using Resilient Distributed Datasets并行编程与弹性分布式数据集（RDD）
  4. 04Scale out / Data Parallelism in Apache SparkApache Spark 中的扩展与数据并行性
  5. 05Dataframes and SparkSQLSparkSQL 和 DataFrames
  6. 06Practice Lab: Getting Started with Pyspark and Pandas实践实验室：开始使用 PySpark 和 Pandas
  7. 07Hands-on Lab: Getting Started with Spark using Python动手实验室：使用 Python 开始使用 Spark
  8. 08Summary and Highlights: Introduction to Apache Spark摘要和重点：Apache Spark 导论
  9. 09Practice Quiz: Introduction to Apache Spark练习测验：Apache Spark 导论
  10. 10Cheat Sheet: Apache Spark速查表：Apache Spark
  11. 11Module 3 Glossary: Apache Spark模块 3 术语表：Apache Spark
  12. 12Graded Quiz: Apache Spark评分测验：Apache Spark
Module 04

DataFrames and Spark SQL

0 / 10 篇
  1. 01RDDs in Parallel Programming and Spark
  2. 02Data-frames and Datasets
  3. 03Catalyst and Tungsten
  4. 04Reading: User-Defined Schema (UDS) for DSL and SQL
  5. 05ETL with DataFrames
  6. 06Real-world usage of SparkSQL
  7. 07Reading: Common Transformations and Optimization Techniques in Spark
  8. 08Summary and Highlights: Introduction to DataFrames and Spark SQL
  9. 09Cheat Sheet: DataFrames and Spark SQL
  10. 10Module 4 Glossary: DataFrames and Spark SQL
Module 05

Development and Runtime Environment Options

0 / 12 篇
  1. 01Apache Spark Architecture
  2. 02Overview of Apache Spark Cluster Modes
  3. 03How to Run an Apache Spark Application
  4. 04Summary and Highlights: Spark Architecture
  5. 05Spark Environments - Overview and Options
  6. 06Using Apache Spark on IBM Cloud
  7. 07How to Set Up Your Own Spark Environments (Optional)
  8. 08Setting Apache Spark Configuration
  9. 09Running Spark on Kubernetes
  10. 10Summary and Highlights: Spark Runtime Environments
  11. 11Cheat Sheet: Development and Runtime Environment Options
  12. 12Module 5 Glossary: Development and Runtime Environment Options
Module 06

Monitoring and Tuning

0 / 9 篇
  1. 01The Apache Spark User Interface
  2. 02Monitoring Application Progress
  3. 03Debugging Apache Spark Application Issues
  4. 04Understanding Memory Resources
  5. 05Understanding Processor Resources
  6. 06[Optional] Batch Data Ingestion Methods
  7. 07Summary and Highlights: Introduction to Monitoring and Tuning
  8. 08Cheat Sheet: Monitoring and Tuning
  9. 09Module 6 Glossary: Monitoring and Tuning
Module 07

Final Project and Assessment

0 / 5 篇
  1. 01Final Project Overview
  2. 02Instructions for the Final Assessment
  3. 03Glossary: Introduction to Big Data with Spark and Hadoop
  4. 04Congratulations and Next Steps
  5. 05Thanks from the Course Team