Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required.
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Learning Real-time Analytics with Storm and Cassandra

You're reading from   Learning Real-time Analytics with Storm and Cassandra Solve real-time analytics problems effectively using Storm and Cassandra

Arrow left icon
Product type Paperback
Published in Mar 2015
Publisher
ISBN-13 9781784395490
Length 220 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Shilpi Saxena Shilpi Saxena
Author Profile Icon Shilpi Saxena
Shilpi Saxena
Arrow right icon
View More author details
Toc

Table of Contents (14) Chapters Close

Preface 1. Let's Understand Storm FREE CHAPTER 2. Getting Started with Your First Topology 3. Understanding Storm Internals by Examples 4. Storm in a Clustered Mode 5. Storm High Availability and Failover 6. Adding NoSQL Persistence to Storm 7. Cassandra Partitioning, High Availability, and Consistency 8. Cassandra Management and Maintenance 9. Storm Management and Maintenance 10. Advance Concepts in Storm 11. Distributed Cache and CEP with Storm A. Quiz Answers Index

Anchoring and acking

We have talked about DAG that is created for the execution of a Storm topology. Now when you are designing your topologies to cater to reliability, there are two items that needs to be added to Storm:

  • Whenever a new link, that is, a new stream is being added to the DAG, it is called anchoring
  • When the tuple is processed in entirety, it is called acking

When Storm knows these preceding facts, then during the processing of tuples it can gauge them and accordingly fail or acknowledge the tuples depending upon whether they are completely processed or not.

Let's take a look at the following WordCount topology bolts to understand the Storm API anchoring and acking better:

  • SplitSentenceBolt: The purpose of this bolt was to split the sentence into different words and emit it. Now let's examine the output declarer and the execute methods of this bolt in detail (specially the highlighted sections) as shown in the following code:
      public void execute(Tuple tuple) {
         ...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime