Communities
A collaborative platform to connect and grow with like-minded Informaticans across the globe
Product Communities
Connect and collaborate with Informatica experts and champions
Discussions
Have a question? Start a Discussion and get immediate answers you are looking for
User Groups
Customer-organized groups that meet online and in-person. Join today to network, share ideas, and get tips on how to get the most out of Informatica
Get Started
Community Guidelines
Knowledge Center
Troubleshooting documents, product guides, how to videos, best practices, and more
Knowledge Base
One-stop self-service portal for solutions, FAQs, Whitepapers, How Tos, Videos, and more
Support TV
Video channel for step-by-step instructions to use our products, best practices, troubleshooting tips, and much more
Documentation
Information library of the latest product documents
Velocity (Best Practices)
Best practices and use cases from the Implementation team
Learn
Rich resources to help you leverage full capabilities of our products
Trainings
Role-based training programs for the best ROI
Certifications
Get certified on Informatica products. Free, Foundation, or Professional
Product Learning Paths
Free and unlimited modules based on your expertise level and journey
Resources
Library of content to help you leverage the best of Informatica products
Tech Tuesdays Webinars
Most popular webinars on product architecture, best practices, and more
Product Availability Matrix
Product Availability Matrix statements of Informatica products
SupportFlash
Monthly support newsletter
Support Documents
Informatica Support Guide and Statements, Quick Start Guides, and Cloud Product Description Schedule
Product Lifecycle
End of Life statements of Informatica products
Ideas
Events
Change Request Tracking
Marketplace
English
  • Data Engineering Integration H2L
  • All Products

Table of Contents

Search

  1. Abstract
  2. Supported Versions
  3. Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

Tuning and Sizing Guidelines for Data Engineering Integration (10.4.x)

Back Next

Case Study: Java String Port Conversion Overhead

Case Study: Java String Port Conversion Overhead

The following case study compares performance between string ports and numeric ports and evaluates the UTF conversion overhead for port processing.

Test Setup

The study compares one operation on 25 string ports to one operation on 25 numeric ports. The operation is performed in the Java transformation. For additional comparison, the same operation is performed in the Expression transformation.

Environment

Chipset
Intel® Xeon® CPU E5-2650 v4 @ 2.20GHz
Cores
12 cores
Memory
256 GB
Operating system
Red Hat Enterprise Linux 7.2
Hadoop cluster
12 nodes
String ports
7 ports
Data volume
~ 750 GB

Performance Chart

The following performance chart compares the time taken for the operation to process the string and numeric ports in the Java transformation and the Expression transformation:
This image shows a performance chart on the performance of string ports and numeric ports that are processed by the Java transformation and the Expression transformation. The graph on the left shows performance for string ports. The graph on the right shows performance for numeric ports. In the graph on the left, the blue bar depicts performance of string ports in the Expression transformation. The orange bar depicts performance of string ports in the Java transformation. The blue bar is shorter than the orange bar. On the right, the blue bar and the orange bar have more similar heights.

Conclusions

Based on the case study, the Java transformation experiences an overhead cost of around 10% for numeric ports. For string ports, the same overhead cost is around 40%.
0 COMMENTS
We’d like to hear from you!