申请试用
HOT
登录
注册
 
Writing Continuous Applications with Structured Streaming PySpark API

Writing Continuous Applications with Structured Streaming PySpark API

Spark开源社区
/
发布于
/
8196
人观看
“We’re amidst the Big Data Zeitgeist era in which data comes at us fast, in myriad forms and formats at intermittent intervals or in a continuous stream, and we need to respond to streaming data immediately. This need has created a notion of writing a streaming application that’s continuous, reacts and interacts with data in real-time. We call this continuous application. In this tutorial we’ll explore the concepts and motivations behind the continuous application, how Structured Streaming Python APIs in Apache Spark™ enable writing continuous applications, examine the programming model behind Structured Streaming, and look at the APIs that support them. Through presentation, code examples, and notebooks, I will demonstrate how to write an end-to-end Structured Streaming application that reacts and interacts with both real-time and historical data to perform advanced analytics using Spark SQL, DataFrames and Datasets APIs. You’ll walk away with an understanding of what’s a continuous application, appreciate the easy-to-use Structured Streaming APIs, and why Structured Streaming in Apache Spark is a step forward in developing new kinds of streaming applications. This tutorial will be both instructor-led and hands-on interactive session. Instructions in how to get tutorial materials will be covered in class. WHAT YOU’LL LEARN: – Understand the concepts and motivations behind Structured Streaming – How to use DataFrame APIs – How to use Spark SQL and create tables on streaming data – How to write a simple end-to-end continuous application PREREQUISITES – A fully-charged laptop (8-16GB memory) with Chrome or Firefox –Pre-register for Databricks Community Edition”
0 点赞
1 收藏
2下载
确认
3秒后跳转登录页面
去登陆