private Map<String, Set<Square>> populateZuloSquare(List<Square> squares) {
if (squares == null || squares.isEmpty()) {
return emptyMap();
}
Map<String, Set<Square>> res = new HashMap<>();
squares.stream()
.filter(square -> {
if (square.getZuloCodes().isEmpty()) {
LOG("Ignored {}", square.id);
return false;
}
return true;
})
.forEach(square -> {
square.getZuloCodes()
.forEach(code -> {
res.putIfAbsent(code, new HashSet<>());
res.get(code).add(square);
}));
});
return Collections.unmodifiableMap(res);
}
The code above receives a list of Squares, and those squares may contain ZuloCodes inside. The output should be a immutable Map zuloCode and value all the squares with that UniquePrefix. As you can see I cannot figure out a way to remove the auxiliar collection res and make the code easily readable, is there a way to explode that collection into a [zuloCode, square] and then collect.groupBy ? Also that if inside the filter is so unreadable, how would you tackle it?
The standard approach is using flatMap
before collecting using groupingBy
, but since you need the original Square
for each element, you need to map to an object holding both, the Square
instance and the zulo code String
.
Since there is no standard pair or tuple type in Java (yet), a work-around is to use a Map.Entry
instance, like this
private Map<String, Set<Square>> populateZuloSquare0(List<Square> squares) {
if (squares == null || squares.isEmpty()) {
return emptyMap();
}
return squares.stream()
.filter(square -> logMismatch(square, !square.getZuloCodes().isEmpty()))
.flatMap(square -> square.getZuloCodes().stream()
.map(code -> new AbstractMap.SimpleEntry<>(code, square)))
.collect(Collectors.collectingAndThen(
Collectors.groupingBy(Map.Entry::getKey,
Collectors.mapping(Map.Entry::getValue, Collectors.toSet())),
Collections::unmodifiableMap));
}
private static boolean logMismatch(Square square, boolean match) {
if(!match) LOG("Ignored {}", square.id);
return match;
}
An alternative is to use a custom collector which will iterate over the keys:
private Map<String, Set<Square>> populateZuloSquare(List<Square> squares) {
if (squares == null || squares.isEmpty()) {
return emptyMap();
}
return squares.stream()
.filter(square -> logMismatch(square, !square.getZuloCodes().isEmpty()))
.collect(Collector.of(
HashMap<String, Set<Square>>::new,
(m,square) -> square.getZuloCodes()
.forEach(code -> m.computeIfAbsent(code, x -> new HashSet<>()).add(square)),
(m1,m2) -> {
if(m1.isEmpty()) return m2;
m2.forEach((key,set) ->
m1.merge(key, set, (s1,s2) -> { s1.addAll(s2); return s1; }));
return m1;
},
Collections::unmodifiableMap)
);
}
Note that this custom collector can be seen as a parallel capable variant of the following looping code:
private Map<String, Set<Square>> populateZuloSquare(List<Square> squares) {
if (squares == null || squares.isEmpty()) {
return emptyMap();
}
Map<String, Set<Square>> res = new HashMap<>();
squares.forEach(square -> {
if(square.getZuloCodes().isEmpty()) LOG("Ignored {}", square.id);
else square.getZuloCodes().forEach(
code -> res.computeIfAbsent(code, x -> new HashSet<>()).add(square));
});
return Collections.unmodifiableMap(res);
}
which might not look so bad now, when you don’t need the code to be parallel capable…