How can the following method be written using Java Stream API?
public Map<String, String> getMap() {
Map<String, String> mapB = new HashMap<>();
for (String parameterKey : listOfKeys) {
String parameterValue = mapA.get(parameterKey);
mapB.put(parameterKey, Objects.requireNonNullElse(parameterValue, ""));
}
return ImmutableMap.copyOf(mapB);
}
I tried something like this:
return listOfKeys.stream()
.map(firstMap::get)
.collect( ? )
But I don't know how to continue from here.
Guava
If you need Guava's ImmutableMap, you can make use of the Collector returned by ImmutableMap.toImmutableMap() available since Guava's version 21.0.
Note: the minimum JDK version required by the Guava 21.0 release is Java 8 (see), hence below is a valid Java 8 compliant solution.
public Map<String, String> getMap() {
return listOfKeys.stream()
.collect(ImmutableMap.toImmutableMap(
Function.identity(), // keyMapper - generating keys
str -> mapA.getOrDefault(str, ""), // valueMapper - generating values
(left, right) -> left // mergeFunction - resolving duplicates
));
}
In case if you're using Guava's version earlier than 21.0, then you can generate the resulting map using standard JDK collector toMap() and wrap it with an ImmutableMap by the means of collectingAndThen().
This approach would be cleaner, cramming the stream as an argument of the copyOf() method as suggested in another answer:
public Map<String, String> getMap() {
return istOfKeys.stream()
.collect(Collectors.collectingAndThen(
Collectors.toMap(
Function.identity(), // keyMapper - generating keys
str -> mapA.getOrDefault(str, ""), // valueMapper - generating values
(left, right) -> right), // mergeFunction - resolving duplicates
ImmutableMap::copyOf
));
}
Note:
If all elements contained in listOfKeys are guaranteed to be unique, then you can remove mergeFunction (the third argument of the collector).
I've replaced Objects.requireNonNullElse() with Map.getOrDefault() which would guard against the cases when a key is not present in the mapA. If you also want you protect against situations when the value associated with the key is null, then replace it with requireNonNullElse(). But you need to be aware that it's a sign of a faulty design if null values are being stored in the map because they have some special meaning in your business logic (and therefore you can't get rid of them).
Standard JDK
Otherwise, you can use collector Collectors.toUnmodifiableMap()
It internally uses a combination of collectors toMap(), accumulates stream data into a map, and collectingAndThen()) which performs the final transformation into a so-called unmodifiable map created via Map.ofEntries().
public Map<String, String> getMap() {
return listOfKeys.stream()
.collect(Collectors.toUnmodifiableMap(
Function.identity(), // keyMapper - generating keys
str -> mapA.getOrDefault(str, ""), // valueMapper - generating values
(left, right) -> left // mergeFunction - resolving duplicates
));
}
Related
I have a map inside a map which looks like this:
Map<String, Map<Integer, BigDecimal>> mapInMap; //--> with values like:
/*
"a": (1: BigDecimal.ONE),
"b": (2: BigDecimal.TEN),
"c": (1: BigDecimal.ZERO)
*/
And I would like to combine the inner maps by expecting the following result:
Map<Integer, BigDecimal> innerMapCombined; //--> with values:
/*
1: BigDecimal.ZERO,
2: BigDecimal.TEN
*/
This is my solution with predefining the combined map and using forEach:
Map<Integer, BigDecimal> combined = new HashMap<>();
mapInMap.forEach((str, innerMap) -> {
innerMap.forEach(combined::putIfAbsent);
});
But this will ignore (1: BigDecimal.ZERO).
Could you provide a 1-line solution with java 8 stream?
The issue with your problem is that as soon as you initialize your maps, and add the duplicate keys on the inner maps, you will rewrite those keys, since those maps do not accept duplicated keys. Therefore, you need to first change this:
Map<String, Map<Integer, BigDecimal>> mapInMap;
to a Map that allows duplicated keys, for instance Multimap from Google Guava:
Map<String, Multimap<Integer, BigDecimal>> mapInMap = new HashMap<>();
where the inner maps are created like this:
Multimap<Integer, BigDecimal> x1 = ArrayListMultimap.create();
x1.put(1, BigDecimal.ONE);
mapInMap.put("a", x1);
Only now you can try to solve your problem using Java 8 Streams API. For instance:
Map<Integer, BigDecimal> map = multiMap.values()
.stream()
.flatMap(map -> map.entries().stream())
.collect(Collectors.toMap(Map.Entry::getKey,
Map.Entry::getValue,
(v1, v2) -> v2));
The duplicate keys conflicts are solved using mergeFunction parameter of the toMap method. We explicitly express to take the second value (v1, v2) -> v2 in case of duplicates.
Problem:
To address why your current solution doesn't work is because Map#putIfAbsent method only adds and doesn't replace a value in a map if is already present.
Solution using for-each:
Map#put is a way to go, however its limitation is that you cannot decide whether you want to keep always the first value for such key, calculate a new one or use always the last value. For such reason I recommend to use either a combination of Map#computeIfPresent and Map#putIfAbsent or better a method that does all that at once which is Map#merge(K, V, BiFunction) with a BiFunction remappingFunction:
remappingFunction - the function to recompute a value if present
Map<Integer, BigDecimal> resultMap = new HashMap<>();
for (Map<Integer, BigDecimal> map: mapInMap.values()) {
for (Map.Entry<Integer, BigDecimal> entry: map.entrySet()) {
resultMap.merge(entry.getKey(), entry.getValue(), (l, r) -> r);
}
}
Solution using Stream API:
To rewrite it in the Stream-alike solution, the approach would be identical. The only difference is the declarative syntax of Stream API, however, the idea is very same.
Just flatMap the structure and collect to a map with a Collector.toMap(Function, Function, BinaryOperator using BinaryOperator mergeFunction to merge duplicated keys.
mergeFunction - a merge function, used to resolve collisions between values associated with the same key, as supplied to Map.merge(Object, Object, BiFunction)
Map<Integer, BigDecimal> resultMap = mapInMap.values().stream()
.flatMap(entries -> entries.entrySet().stream())
.collect(Collectors.toMap( Map.Entry::getKey, Map.Entry::getValue, (l, r) -> r));
Note: #dreamcrash also deserves a credit for his good Stream API answer in terms of speed.
Result:
{1=1, 2=10} is the result when you pring out such map (note that BigDecimal is printed as a number). This output matches your expected output.
1=BigDecimal.ZERO
2=BigDecimal.TEN
Notice the similarities between Map#merge(K, V, BiFunction) and Collector.toMap(Function, Function, BinaryOperator that use a very similar approach to the same result.
I am trying to rewrite the method below using streams but I am not sure what the best approach is? If I use flatMap on the values of the entrySet(), I lose the reference to the current key.
private List<String> asList(final Map<String, List<String>> map) {
final List<String> result = new ArrayList<>();
for (final Entry<String, List<String>> entry : map.entrySet()) {
final List<String> values = entry.getValue();
values.forEach(value -> result.add(String.format("%s-%s", entry.getKey(), value)));
}
return result;
}
The best I managed to do is the following:
return map.keySet().stream()
.flatMap(key -> map.get(key).stream()
.map(value -> new AbstractMap.SimpleEntry<>(key, value)))
.map(e -> String.format("%s-%s", e.getKey(), e.getValue()))
.collect(Collectors.toList());
Is there a simpler way without resorting to creating new Entry objects?
A stream is a sequence of values (possibly unordered / parallel). map() is what you use when you want to map a single value in the sequence to some single other value. Say, map "alturkovic" to "ALTURKOVIC". flatMap() is what you use when you want to map a single value in the sequence to 0, 1, or many other values. Hence why a flatMap lambda needs to turn a value into a stream of values. flatMap can thus be used to take, say, a list of lists of string, and turn that into a stream of just strings.
Here, you want to map a single entry from your map (a single key/value pair) into a single element (a string describing it). 1 value to 1 value. That means flatMap is not appropriate. You're looking for just map.
Furthermore, you need both key and value to perform your mapping op, so, keySet() is also not appropriate. You're looking for entrySet(), which gives you a set of all k/v pairs, juts what we need.
That gets us to:
map.entrySet().stream()
.map(e -> String.format("%s-%s", e.getKey(), e.getValue()))
.collect(Collectors.toList());
Your original code makes no effort to treat a single value from a map (which is a List<String>) as separate values; you just call .toString() on the entire ordeal, and be done with it. This means the produced string looks like, say, [Hello, World] given a map value of List.of("Hello", "World"). If you don't want this, you still don't want flatmap, because streams are also homogenous - the values in a stream are all of the same kind, and thus a stream of 'key1 value1 value2 key2 valueA valueB' is not what you'd want:
map.entrySet().stream()
.map(e -> String.format("%s-%s", e.getKey(), myPrint(e.getValue())))
.collect(Collectors.toList());
public static String myPrint(List<String> in) {
// write your own algorithm here
}
Stream API just isn't the right tool to replace that myPrint method.
A third alternative is that you want to smear out the map; you want each string in a mapvalue's List<String> to first be matched with the key (so that's re-stating that key rather a lot), and then do something to that. NOW flatMap IS appropriate - you want a stream of k/v pairs first, and then do something to that, and each element is now of the same kind. You want to turn the map:
key1 = [value1, value2]
key2 = [value3, value4]
first into a stream:
key1:value1
key1:value2
key2:value3
key2:value4
and take it from there. This explodes a single k/v entry in your map into more than one, thus, flatmapping needed:
return map.entrySet().stream()
.flatMap(e -> e.getValue().stream()
.map(v -> String.format("%s-%s", e.getKey(), v))
.collect(Collectors.toList());
Going inside-out, it maps a single entry within a list that belongs to a single k/v pair into the string Key-SingleItemFromItsList.
Adding my two cents to excellent answer by #rzwitserloot. Already flatmap and map is explained in his answer.
List<String> resultLists = myMap.entrySet().stream()
.flatMap(mapEntry -> printEntries(mapEntry.getKey(),mapEntry.getValue())).collect(Collectors.toList());
System.out.println(resultLists);
Splitting this to a separate method gives good readability IMO,
private static Stream<String> printEntries(String key, List<String> values) {
return values.stream().map(val -> String.format("%s-%s",key,val));
}
I would like to convert my map which looks like this:
{
key="someKey1", value=Apple(id="1", color="green"),
key="someKey2", value=Apple(id="2", color="red"),
key="someKey3", value=Apple(id="3", color="green"),
key="someKey4", value=Apple(id="4", color="red"),
}
to another map which puts all apples of the same color into the same list:
{
key="red", value=list={apple1, apple3},
key="green", value=list={apple2, apple4},
}
I tried the following:
Map<String, Set<Apple>> sortedApples = appleMap.entrySet()
.stream()
.collect(Collectors.toMap(l -> l.getColour, ???));
Am I on the right track? Should I use filters for this task? Is there an easier way?
Collectors.groupingBy is more suitable than Collectors.toMap for this task (though both can be used).
Map<String, List<Apple>> sortedApples =
appleMap.values()
.stream()
.collect(Collectors.groupingBy(Apple::getColour));
Or, to group them into Sets use:
Map<String, Set<Apple>> sortedApples =
appleMap.values()
.stream()
.collect(Collectors.groupingBy(Apple::getColour,
Collectors.mapping(Function.identity(),
Collectors.toSet())));
or (as Aomine commented):
Map<String, Set<Apple>> sortedApples =
appleMap.values()
.stream()
.collect(Collectors.groupingBy(Apple::getColour, Collectors.toSet()));
if you want to proceed with toMap you can get the result as follows:
map.values() // get the apples
.stream() // Stream<Apple>
.collect(toMap(Apple::getColour, // group by colour
v -> new HashSet<>(singleton(v)), // have values as set of apples
(l, r) -> {l.addAll(r); return l;})); // merge colliding apples by colour
stream over the map values instead of entrySet because we're not concerned with the map keys.
Apple::getColour is the keyMapper function used to extract the "thing" we wish to group by, in this case, the Apples colour.
v -> new HashSet<>(singleton(v)) is the valueMapper function used for the resulting map values
(l, r) -> {l.addAll(r); return l;} is the merge function used to combine two HashSet's when there is a key collision on the Apple's colour.
finally, the resulting map is a Map<String, Set<Apple>>
but this is better with groupingBy and toSet as downstream:
map.values().stream().collect(groupingBy(Apple::getColour, toSet()));
stream over the map values instead of entrySet because we're not concerned with the map keys.
groups the Apple's by the provided classification function i.e. Apple::getColour and then collect the values in a Set hence the toSet downstream collector.
finally, the resulting map is a Map<String, Set<Apple>>
short, readable and the idiomatic approach.
You could also do it without a stream:
Map<String, Set<Apple>> res = new HashMap<>();
map.values().forEach(a -> res.computeIfAbsent(a.getColour(), e -> new HashSet<>()).add(a));
iterate over the map values instead of entrySet because we're not concerned with the map keys.
if the specified key a.getColour() is not already associated with a value, attempts to compute its value using the given mapping function e -> new HashSet<>() and enters it into the map. we then add the Apple to the resulting set.
if the specified key a.getColour() is already associated with a value computeIfAbsent returns the existing value associated with it and then we call add(a) on the HashSet to enter the Apple into the set.
finally, the resulting map is a Map<String, Set<Apple>>
You can use Collectors.groupingBy and Collectors.toSet()
Map<String, Set<Apple>> sortedApples = appleMap.values() // Collection<Apple>
.stream() // Stream<Apple>
.collect(Collectors.groupingBy(Apple::getColour, // groupBy colour
Collectors.mapping(a -> a, Collectors.toSet()))); // collect to Set
You've asked how to do it with streams, yet here's another way:
Map<String, Set<Apple>> result = new LinkedHashMap<>();
appleMap.values().forEach(apple ->
result.computeIfAbsent(apple.getColor(), k -> new LinkedHashSet<>()).add(apple));
This uses Map.computeIfAbsent, which either returns the set mapped to that color or puts an empty LinkedHashSet into the map if there's nothing mapped to that color yet, then adds the apple to the set.
EDIT: I'm using LinkedHashMap and LinkedHashSet to preserve insertion order, but could have used HashMap and HashSet, respectively.
I have two maps that use the same object as keys. I want to merge these two streams by key. When a key exists in both maps, I want the resulting map to run a formula. When a key exists in a single map I want the value to be 0.
Map<MyKey, Integer> map1;
Map<MyKey, Integer> map2;
<Map<MyKey, Double> result =
Stream.concat(map1.entrySet().stream(), map2.entrySet().stream())
.collect(Collectors.toMap(
Map.Entry::getKey, Map.Entry::getValue,
(val1, val2) -> (val1 / (double)val2) * 12D));
This will use the formula if the key exists in both maps, but I need an easy way to set the values for keys that only existed in one of the two maps to 0D.
I can do this by doing set math and trying to calculate the inner-join of the two keySets, and then subtracting the inner-join result from the full outer join of them... but this is a lot of work that feels unnecessary.
Is there a better approach to this, or something I can easily do using the Streaming API?
Here is a simple way, only stream the keys, and then looking up the values, and leaving the original maps unchanged.
Map<String, Double> result =
Stream.concat(map1.keySet().stream(), map2.keySet().stream())
.distinct()
.collect(Collectors.toMap(k -> k, k -> map1.containsKey(k) && map2.containsKey(k)
? map1.get(k) * 12d / map2.get(k) : 0d));
Test
Map<String, Integer> map1 = new HashMap<>();
Map<String, Integer> map2 = new HashMap<>();
map1.put("A", 1);
map1.put("B", 2);
map2.put("A", 3);
map2.put("C", 4);
// code above here
result.entrySet().forEach(System.out::println);
Output
A=4.0
B=0.0
C=0.0
For this solution to work, your initial maps should be Map<MyKey, Double>. I'll try to find another solution that will work if the values are initially Integer.
You don't even need streams for this! You should simply be able to use Map#replaceAll to modify one of the Maps:
map1.replaceAll((k, v) -> map2.containsKey(k) ? 12D * v / map2.get(k) : 0D);
Now, you just need to add every key to map1 that is in map2, but not map1:
map2.forEach((k, v) -> map1.putIfAbsent(k, 0D));
If you don't want to modify either of the Maps, then you should create a deep copy of map1 first.
Stream.concat is not the right approach here, as you are throwing the elements of the two map together, creating the need to separate them afterward.
You can simplify this by directly doing the intended task of processing the intersection of the keys by applying your function and processing the other keys differently. E.g. when you stream over one map instead of the concatenation of two maps, you only have to check for the presence in the other map to either, apply the function or use zero. Then, the keys only present in the second map need to be put with zero in a second step:
Map<MyKey, Double> result = map1.entrySet().stream()
.collect(Collectors.collectingAndThen(
Collectors.toMap(Map.Entry::getKey, e -> {
Integer val2 = map2.get(e.getKey());
return val2==null? 0.0: e.getValue()*12.0/val2;
}),
m -> {
Map<MyKey, Double> rMap = m.getClass()==HashMap.class? m: new HashMap<>(m);
map2.keySet().forEach(key -> rMap.putIfAbsent(key, 0.0));
return rMap;
}));
This clearly suffers from the fact that Streams don’t offer convenience methods for processing map entries. Also, we have to deal with the unspecified map type for the second processing step. If we provided a map supplier, we also had to provide a merge function, making the code even more verbose.
The simpler solution is to use the Collection API rather than the Stream API:
Map<MyKey, Double> result = new HashMap<>(Math.max(map1.size(),map2.size()));
map2.forEach((key, value) -> result.put(key, map1.getOrDefault(key, 0)*12D/value));
map1.keySet().forEach(key -> result.putIfAbsent(key, 0.0));
This is clearly less verbose and potentially more efficient as it omits some of the Stream solution’s processing steps and provides the right initial capacity to the map. It utilizes the fact that the formula evaluates to the desired zero result if we use zero as default for the first map’s value for absent keys. If you want to use a different formula which doesn’t have this property or want to avoid the calculation for absent mappings, you’d have to use
Map<MyKey, Double> result = new HashMap<>(Math.max(map1.size(),map2.size()));
map2.forEach((key, value2) -> {
Integer value1 = map1.get(key);
result.put(key, value1 != null? value1*12D/value2: 0.0);
});
map1.keySet().forEach(key -> result.putIfAbsent(key, 0.0));
I have a Stream<String>, and I want a Map<Integer, String>. Let's call my classifier function getKey(String) - it can be expensive. Sometimes it returns zero, which means that the String should be discarded and not included in the resulting map.
So, I can use this code:
Stream<String> stringStream;
Map<Integer, String> result =
stringStream.collect(Collectors.groupingBy(this::getKey, Collectors.joining());
result.remove(0);
This first adds the unwanted Strings to the Map keyed by zero, and then removes them. There may be a lot of them. Is there an elegant way to avoid adding them to the map in the first place?
I don't want to add a filter step before grouping, because that would mean executing the decision/classification code twice.
You said that calling getKey is expensive, but you could still map the elements of the stream up-front before filtering them. The call to getKey will be only done once in this case.
Map<Integer, String> result =
stringStream.map(s -> new SimpleEntry<>(this.getKey(s), s))
.filter(e -> e.getKey() != 0)
.collect(groupingBy(Map.Entry::getKey, mapping(Map.Entry::getValue, joining())));
Note that there is no tuple classes in the standard API. You may roll your own one or use AbstractMap.SimpleEntry as a substitute.
Alternatively, if you think the first version creates a lot of entries, you can use the collect method where you provide yourself the supplier, accumulator and combiner.
Map<Integer, String> result = stringStream
.collect(HashMap::new,
(m, e) -> {
Integer key = this.getKey(e);
if(key != 0) {
m.merge(key, e, String::concat);
}
},
Map::putAll);
You may use a stream of pairs like this:
stringStream.map(x -> new Pair(getKey(x), x))
.filter(pair -> pair.left != 0) // or whatever predicate
.collect(Collectors.groupingBy(pair -> pair.left,
Collectors.mapping(pair -> pair.right, Collectors.joining())));
This code assumes simple Pair class with two fields left and right.
Some third-party libraries like my StreamEx provide additional methods to remove the boilerplate:
StreamEx.of(stringStream)
.mapToEntry(this::getKey, x -> x)
.filterKeys(key -> key != 0) // or whatever
.grouping(Collectors.joining());