PySpark – Build DataFrames with Python, Apache Spark and SQL

本课程涵盖了有关使用Python进行Apache Spark流式处理的所有基础知识，并教您有关使用PySpark（Spark的Python API）开发Spark流式处理应用程序所需的一切知识。在本课程的最后，您将获得有关Spark流传输和一般大数据操作技能的深入知识，以帮助您的公司适应Spark Streaming以构建大数据处理管道和数据分析应用程序。对于今天想要在数据科学领域中取得成功的任何人，这门课程都是至关重要的。

Spark的执行速度比Hadoop MapReduce快100倍，这导致对此技能的需求激增！因为Spark 2.0 DataFrame框架是如此新，所以您现在可以迅速成为就业市场上最有知识的人之一！

本课程将通过Python速成班讲授基础知识，并继续学习如何将Spark DataFrames与最新的Spark 2.0语法一起使用！完成之后，我们将介绍如何将MLlib Machine Library与DataFrame语法和Spark一起使用。一路走来，您将拥有练习和模拟咨询项目，可以将您带入现实世界中，在这种情况下，您需要使用新技能来解决实际问题！

我们还将介绍最新的Spark技术，例如Spark SQL，Spark Streaming，以及高级模型，例如Gradient Boosted Trees！完成本课程后，您将放心将Spark和PySpark放在简历上！该课程还具有30天的全额退款保证，并随附LinkedIn结业证书！

Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 48.0 KHz
Language: English | VTT | Size: 2.10 GB | Duration: 5h 56m

What you’ll learn
Create big data streaming pipelines with Spark using Python
Learn how to apply Spark on distributed Dataframes
Use Python with Big Data on a distributed framework (Apache Spark)

Description
This course covers all the fundamentals about Apache Spark streaming with Python and teaches you everything you need to know about developing Spark streaming applications using PySpark, the Python API for Spark. At the end of this course, you will gain in-depth knowledge about Spark streaming and general big data manipulation skills to help your company to adapt Spark Streaming for building big data processing pipelines and data analytics applications. This course will be absolutely critical to anyone trying to make it in data science today.

Spark can perform up to 100x faster than Hadoop MapReduce, which has caused an explosion in demand for this skill! Because the Spark 2.0 DataFrame framework is so new, you now have the ability to quickly become one of the most knowledgeable people in the job market!

This course will teach the basics with a crash course in Python, continuing on to learning how to use Spark DataFrames with the latest Spark 2.0 syntax! Once we’ve done that we’ll go through how to use the MLlib Machine Library with the DataFrame syntax and Spark. All along the way, you’ll have exercises and Mock Consulting Projects that put you right into a real-world situation where you need to use your new skills to solve a real problem!

We also cover the latest Spark Technologies, like Spark SQL, Spark Streaming, and advanced models like Gradient Boosted Trees! After you complete this course you will feel comfortable putting Spark and PySpark on your resume! This course also has a full 30-day money-back guarantee and comes with a LinkedIn Certificate of Completion!

If you’re ready to jump into the world of Python, Spark, and Big Data, this is the course for you!

Who this course is for:
Someone who knows Python and would like to learn how to use it for Big Data
Someone who is very familiar with another programming language and needs to learn Spark
Developers transferring from other languages
Python Developers looking to get better at Data Streaming
Spark Developers eager to expand their skills.