Over a million developers have joined DZone.

Need Micro Caching? Memoization to the Rescue

DZone's Guide to

Need Micro Caching? Memoization to the Rescue

· Java Zone
Free Resource

Build vs Buy a Data Quality Solution: Which is Best for You? Gain insights on a hybrid approach. Download white paper now!

Caching solves wide sort of performance problems. There are many ways to integrate caching into our applications. For example when we use Spring there is easy to use @Cacheable support. Quite easy but we still have to configure cache manager, cache regions, etc. Sometimes it's unfortunately like taking a sledgehammer to crack a nut. So what can we do to "go lighter"?

There is a technique called memoization. Technically it's as easy as pie but true genius lies in simplicity. Model solution looks as follows:

public Foo getValue() {
  if (storedValue == null) {
    storedValue = retrieveFoo();
  return storedValue;

As you can see there is no problem in implementing it manually, but as long as we remember about DRY rule we can use already implemented solutions which additionally provides thread safety. Pretty good idea is to use Guava library.

// create
Supplier<Foo> memoizer = Suppliers.memoize(this::retrieveFoo);
// and use
Foo variable = memoizer.get();

Sometimes it's enough but what can we do if we need to specify TTL for our value? We have to store (cache) retrieved value only for few seconds and after exceeding defined duration get this value one more time? One more time we can use functionality provided by Guava. 

Supplier<Foo> memoizer = Suppliers.memoizeWithExpiration(this::retrieveFoo, 
    5, TimeUnit.SECONDS);
The above line builds memoizer with TTL = 5 seconds. As you can see - simple... but powerful :)

Build vs Buy a Data Quality Solution: Which is Best for You? Maintaining high quality data is essential for operational efficiency, meaningful analytics and good long-term customer relationships. But, when dealing with multiple sources of data, data quality becomes complex, so you need to know when you should build a custom data quality tools effort over canned solutions. Download our whitepaper for more insights into a hybrid approach.


Published at DZone with permission of Jakub Kubrynski, DZone MVB. See the original article here.

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}