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

Introducing the primitive PTransform object – stateful ParDo

This section will focus on a theoretical description of the stateful ParDo transform, which is the most complex transform that a typical user of Beam needs to understand. We will divide this section into two subsections. First, we will describe its theoretical properties and the differences from the stateless version of ParDo. Then, we will see how this theoretical knowledge applies to API changes.

Describing the theoretical properties of the stateful ParDo object

As we have seen, the main difference between a stateful ParDo object and a stateless ParDo object is – as the name suggests – the presence of user state or timers. This alone brings one important requirement: every meaningful access to a state must be keyed. That is to say, the PCollection object we apply to a stateful ParDo object must be of the KV<K, V> type. We must assign a key to every element of a PCollection object (or use...

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