Streams: Grouping and Partitioning in Java

In the preceding section, you saw how to collect all languages in a given country. But the process was a bit tedious. You had to generate a singleton set for each map value and then specify how to merge the existing and new values. Forming groups of values with the same characteristic is very common, so the groupingBy method supports it directly.

Let’s look at the problem of grouping locales by country. First, form this map:

Map<String, List<Locate>> countryToLocates = locales.cotlect(

Cotlectors.groupingBy(Locale::getCountry));

The function Locale::getCountry is the classifier function of the grouping. You can now look up all locales for a given country code, for example

List<Locale> swissLocales = countryToLocales.get(“CH”);

// Yields locales de_CH, fr_CH, it_CH and maybe more

When the classifier function is a predicate function (that is, a function return­ing a boolean value), the stream elements are partitioned into two lists: those where the function returns true and the complement. In this case, it is more efficient to use partitioningBy instead of groupingBy. For example, here we split all locales into those that use English and all others:

Map<Boolean, List<Locale>> englishAndOtherLocales = locales.collect(
Collectors.partitioningBy(l -> l.getLanguage().equals(“en”)));
List<Locale> englishLocales = englishAndOtherLocales.get(true);

Source: Horstmann Cay S. (2019), Core Java. Volume II – Advanced Features, Pearson; 11th edition.

Source: Horstmann Cay S. (2019), Core Java. Volume II – Advanced Features, Pearson; 11th edition.