Module Review

This chapter looked at FME Performance and some of the techniques available to improve it

What You Should Have Learned from this Module

The following are key points to be learned from this session:

Analyzing a log file helps to determine where performance improvements can be made
Performance is the measure of useful work done in a given time. Excess data and caching to disk are two factors that impact performance
Reading performance is improved by reducing the amount of data being read
Writing performance is improved by ordering the FME Writers correctly
Transformation performance is improved by removing excess attributes and properly managing group-based transformers
Database performance is improved by passing tasks to the database and setting reader/writer parameters correctly
FME Server and FME Cloud process large quantities of data in a scalable environment
Batch processing is a way to make use of the full processing power of a given computer

The ability to analyze and deconstruct an FME log file
The ability to measure workspace performance for each set of components
The ability to use various methods for optimizing reader, writer, and transformer performance
The ability to use database parameters to improve performance
The ability to batch process data with the WorkspaceRunner transformer