Reader small image

You're reading from  Building Big Data Pipelines with Apache Beam

Product typeBook
Published inJan 2022
Reading LevelBeginner
PublisherPackt
ISBN-139781800564930
Edition1st Edition
Languages
Right arrow
Author (1)
Jan Lukavský
Jan Lukavský
author image
Jan Lukavský

Jan Lukavský is a freelance big data architect and engineer who is also a committer of Apache Beam. He is a certified Apache Hadoop professional. He is working on open source big data systems combining batch and streaming data pipelines in a unified model, enabling the rise of real-time, data-driven applications.
Read more about Jan Lukavský

Right arrow

Task 11 – Enhancing SportTracker by runner motivation using side inputs

In our first task for this chapter, we will enhance the SportTracker application we used in Task 5. We want to create motivating push notifications for users who are currently on track. Users will be notified every minute with information on whether their running performance over the last minute was better than their average pace over the last 5 minutes. Let's look at this problem in more detail.

Problem definition

Calculate two per-user running averages over the stream of artificial GPS coordinates that we generated for Task 5. One computation will be the average pace over a longer (5-minute) interval, while the other will be over a shorter (1-minute) interval. Every minute, for each user, output information will be provided regarding whether the user's current 1-minute pace is higher or lower than the longer average if the short average differs by more than 10%.

We will use our output_topic...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Building Big Data Pipelines with Apache Beam
Published in: Jan 2022Publisher: PacktISBN-13: 9781800564930

Author (1)

author image
Jan Lukavský

Jan Lukavský is a freelance big data architect and engineer who is also a committer of Apache Beam. He is a certified Apache Hadoop professional. He is working on open source big data systems combining batch and streaming data pipelines in a unified model, enabling the rise of real-time, data-driven applications.
Read more about Jan Lukavský