使用Apache Spark进行大数据分析

Big Data Analysis with Apache Spark

Learn how to apply data science techniques using parallel programming in Apache Spark to explore big data.

1399 次查看
加州大学伯克利分校
edX
  • 完成时间大约为 4
  • 中级
  • 英语
注:因开课平台的各种因素变化,以上开课日期仅供参考

你将学到什么

How to use Apache Spark to perform data analysis

How to use parallel programming to explore data sets

Apply log mining, textual entity recognition and collaborative filtering techniques to real-world data questions

课程概况

Organizations use their data to support and influence decisions and build data-intensive products and services, such as recommendation, prediction, and diagnostic systems. The collection of skills required by organizations to support these functions has been grouped under the term ‘data science’.

This statistics and data analysis course will attempt to articulate the expected output of data scientists and then teach students how to use PySpark (part of Spark) to deliver against these expectations. The course assignments include log mining, textual entity recognition, and collaborative filtering exercises that teach students how to manipulate data sets using parallel processing with PySpark.

This course covers advanced undergraduate-level material. It requires a programming background and experience with Python (or the ability to learn it quickly). All exercises will use PySpark (the Python API for Spark), and previous experience with Spark equivalent to Introduction to Apache Spark, is required.

预备知识

Programming background and experience with Python required. All exercises will use PySpark (part of Apache Spark). Previous experience with Spark equivalent to CS105x: Introduction to Spark required.

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