One way to improve performance when working with many objects or large data structures is lazy initialization or evaluation. The concept is to defer expensive operations to the latest moment possible – ideally never. I want to show some examples how to use lazy techniques in java and give you pointers to other languages where it is even easier and part of the core language.
One use case was a large JTable showing hundreds of domain objects consisting of meta-data and measured values. Initially our domain objects held both types of data in memory even though only part of the meta data was displayed in the table. Building the table took several seconds and we were limited to showing a few hundred entries at once. After some analysis we changed our implementation to roughly look like this:
public class DomainObject { private final DataParser parser; private final Map<String, String> header = new HashMap<>(); private final List<Data> data = new ArrayList<>(); public DomainObject(DataParser aParser) { parser = aParser; } public String getHeaderField(String name) { // Here we lazily parse and fill the header map if (header.isEmpty()) { header.addAll(parser.header()); } return header.get(name); } public Iterable<Data> getMeasurementValues() { // again lazy-load and parse the data if (data.isEmpty()) { data.addAll(parser.measurements()); } return data; } }
This improved both the time to display the entries and the number of entries we could handle significantly. All the data loading and parsing was only done when someone wanted the details of a measurement and double-clicked an entry.
A situation where you get lazy evaluation in Java out-of-the-box is in conditional statements:
// lazy and fast because the expensive operation will only execute when needed if (aCondition() && expensiveOperation()) { ... } // slow order (still lazy evaluated!) if (expensiveOperation() && aCondition()) { ... }
Persistence frameworks like Hibernate often times default to lazy-loading because database access and data transmission is quite costly in general.
Most functional languages are built around lazy evaluation of and their concept of functions as first class citizens and isolated/minimized side-effects support lazyness very well. Scala as a hybrid OO/functional language introduces the lazy keyword to simplify typical java-style lazy initialization code like above to something like this:
public class DomainObject(parser: DataParser) { // evaluated on first access private lazy val header = { parser.header() } def getHeaderField(name : String) : String = { header.get(name).getOrElse("") } // evaluated on first access lazy val measurementValues : Iterable[Data] = { parser.measurements() } }
Conclusion
Lazy evaluation is nothing new or revolutionary but a very useful tool when dealing with large datasets or slow resources. There may be many situations where you can use it to improve performance or user experience using it.
The downsides are a bit of implementation cost if language support is poor (like in Java) and some cases where the application can feel more responsive with precomputed/prefetched values when the user wants to see the details.