We know that EnumSet and EnumMap are faster than HashSet/HashMap due to the power of bit manipulation. But are we actually harnessing the true power of EnumSet/EnumMap when it really matters? If we have a set of millions of record and we want to find out if some object is present in that set or not, can we take advantage of EnumSet's speed?
I checked around but haven't found anything discussing this. Everywhere the usual stuff is found i.e. because EnumSet and EnumMap uses a predefined set of keys lookups on small collections are very fast. I know enums are compile-time constants but can we have best of both worlds - an EnumSet-like data structure without needing enums as keys?
Interesting insight; the short answer is no, but your question is exploring some good data-structure design concepts which I'll try to discuss.
First, lets talk about HashMap (HashSet uses a HashMap internally, so they share most behavior); a hash-based data structure is powerful because it is fast and general. It's fast (i.e. approximately O(1)) because we can find the key we're looking for with a very small number of computations. Roughly, we have an array of lists of keys, convert the key to an integer index into that array, then look through the associated list for the key. As the mapping gets bigger, the backing array is repeatedly resized to hold more lists. Assuming the lists are evenly distributed, this lookup is very fast. And because this works for any generic object (that has a proper .hashcode() and .equals()) it's useful for just about any application.
Enums have several interesting properties, but for the purpose of efficient lookup we only care about two of them - they're generally small, and they have a fixed number of values. Because of this, we can do better than HashMap; specifically, we can map every possible value to a unique integer, meaning we don't need to compute a hash, and we don't need to worry about hashes colliding. So EnumMap simply stores an array of the same size as the enum and looks up directly into it:
// From Java 7's EnumMap
public V get(Object key) {
return (isValidKey(key) ?
unmaskNull(vals[((Enum)key).ordinal()]) : null);
}
Stripping away some of the required Map sanity checks, it's simply:
return vals[key.ordinal()];
Note that this is conceptually no different than a standard HashMap, it's simply avoiding a few computations. EnumSet is a little more clever, using the bits in one or more longs to represent array indices, but functionally it's no different than the EnumMap case - we allocate enough slots to cover all possible enum values and can use their integer .ordinal() rather than compute a hash.
So how much faster than HashMap is EnumMap? It's clearly faster, but in truth it's not that much faster. HashMap is already a very efficient data structure, so any optimization on it will only yield marginally better results. In particular, both HashMap and EnumMap are asymptotically the same speed (O(1)), meaning as they get bigger, they behave equally well. This is the primary reason why there isn't a more general data-structure like EnumMap - because it wouldn't be worth the effort relative to HashMap.
The second reason we don't want a more general "FiniteKeysMap" is it would make our lives as users more complicated, which would be worthwhile if it were a marked speed increase, but since it's not would just be a hassle. We would have to define an interface (and probably also a factory pattern) for any type that could be a key in this map. The interface would need to provide a guarantee that every unique instance returns a unique hashcode in the range [0-n), and also provide a way for the map to get n and potentially all n elements. Those last two operations would be better as static methods, but since we can't define static methods in an interface, they'd have to either be passed in directly to every map we create, or a separate factory object with this information would have to exist and be passed to the map/set at construction. Because enums are part of the language, they get all of those benefits for free, meaning there's no such cost for end-user programmers to need to take advantage of.
Furthermore, it would be very easy to make mistakes with this interface; say you have a type that has exactly 100,000 unique values. Should it implement our interface? It could. But you'd likely actually be shooting yourself in the foot. This would eat up a lot of unnecessary memory, since our FiniteKeysMap would allocate a new 100,000 length array to represent even an empty map. Generally speaking, that sort of wasted space is not worth the marginal improvement such a data structure would provide.
In short, while your idea is possible, it is not practical. HashMap is so efficient that attempting to create a separate data structure for a very limited number of cases would add far more complexity than value.
For the specific case of faster .contains() checks, you might like Bloom Filters. It's a set-like data structure that very efficiently stores very large sets, with the condition that it may sometimes incorrectly say an element is in the set when it is not (but not the other way around - if it says an element isn't in the set, it's definitely not). Guava provides a nice BloomFilter implementation.
Related
An EnumMap uses the restriction that all keys of a map will be from the same enum to gain performance benefits:
Enum maps are represented internally as arrays. This representation is extremely compact and efficient.
In this case, the keys and values are stored in separate arrays and the values are ordinal-ordered. Iteration is done with the internal EnumMapIterator class.
An immutable map created by the various Map.of methods use the restriction that the map will not change structurally to gain performance benefits. If the map is not of size 0 or 1, it uses the MapN internal class that also stores its entries in an array. In this case, the value is stored 1 index after its key. Iteration is done with the internal MapNIterator.
For an immutable map of enum keys of size 2 or more, which answers both of the above's requirements, which map performs better? (Criteria could be space efficiency, time efficiency for containsKey, containsValue, get, and iteration efficiency of entrySet, keySet and values.)
which map gives better space efficiency, and time efficiency for its operations and iteration: containsKey, containsValue, get, entrySet, keySet and values?
You're raising 1 + 6 (or 2 * 6, depending on how it's understood) questions, that's a bit too much. If you want a definite answer, you have to concentrate on a single thing and profile it (nobody's gonna do it for you unless you find a very interesting problem).
The space efficiency for an EnumMap simply must be better. There's no need to store the keys as a shared enum array can be used. There's no need for a holes-containing hash lookup array.
There may be exceptions like a small map based on a huge enum.
The most important operation is get. With an EnumMap, it involves no lookup, just a trivial class comparison and an array access. With Map.of(...), there's a loop, which for enums, usually terminates after the first iteration as Enum.hashCode is IMHO stupid, but usually well distributed.
As containsKey is based on the same lookup, it's clear.
I doubt, I've ever used containsValue, but it doesn't do anything smarter than linear search. I'd expect a tiny win for EnumMap because of the holes (needing trivial null test, but causing branch mispredictions).
The remaining three operations are not worth looking up as they return a collection containing no data and simply pointing to the map, i.e., a constant time operation. For example, map.keySet().contains(x) simply delegates to map.containsKey().
The efficiency of the iteration would be a more interesting question, but you didn't ask it.
We use a HashMap<Integer, SomeType>() with more than a million entries. I consider that large.
But integers are their own hash code. Couldn't we save memory with a, say, IntegerHashMap<Integer, SomeType>() that uses a special Map.Entry, using int directly instead of a pointer to an Integer object? In our case, that would save 1000000x the memory required for an Integer object.
Any faults in my line of thought? Too special to be of general interest? (at least, there is an EnumHashMap)
add1. The first generic parameter of IntegerHashMap is used to make it closely similar to the other Map implementations. It could be dropped, of course.
add2. The same should be possible with other maps and collections. For example ToIntegerHashMap<KeyType, Integer>, IntegerHashSet<Integer>, etc.
What you're looking for is a "Primitive collections" library. They are usually much better with memory usage and performance. One of the oldest/popular libraries was called "Trove". However, it is a bit outdated now. The main active libraries in use now are:
Goldman Sach Collections
Fast Util
Koloboke
See Benchmarks Here
Some words of caution:
"integers are their own hash code" I'd be very careful with this statement. Depending on the integers you have, the distribution of keys may be anything from optimal to terrible. Ideally, I'd design the map so that you can pass in a custom IntFunction as hashing strategy. You can still default this to (i) -> i if you want, but you probably want to introduce a modulo factor, or your internal array will be enormous. You may even want to use an IntBinaryOperator, where one param is the int and the other is the number of buckets.
I would drop the first generic param. You probably don't want to implement Map<Integer, SomeType>, because then you will have to box / unbox in all your methods, and you will lose all your optimizations (except space). Trying to make a primitive collection compatible with an object collection will make the whole exercise pointless.
Assuming one needs to store a list of items, but it can be stored in any variable type; what would be the most efficient type, if used mostly for matching?
To clarify, a list of items needs to be contained, but the form it's contained in doesn't matter (enum, list, hashmap, Arraylist, etc..)
This list of items would be matched against on a regular basis, but not edited. What would the most efficient storage method be, assuming you only need to write to the list once, but could be matching multiple times per second?
Note: No multi-threading
A HashSet (and HashMap) offers O(1) complexity. Also note that you should create a large enough HashSet with small loadfactor which means that after a hashcode check the elements in the result bucket will also be found very quickly (in a bucket there is a sequential search). Optimally each bucket should contain 1 element at the most.
You can read more about the concept of capacity and load factor in the Javadoc of HashMap.
An even faster solution would be if the number of items is no more than 64 is to create an Enum for them and use EnumSet or EnumMap which stores the elements in a long and uses simple and very fast bit operations to test if an element is in the set or map (a contains operation is just a simple bitmask test).
If you choose to go with the HashSet and not with the Enum approach, know that HashSet uses the hashCode() and equals() methods of the elements. You might consider overriding them to provide a faster implementation knowing the internals of the items you wish to store.
A trivial optimization of overriding the hashCode() can be for example to cache a once computed hash code in the item itself if it doesn't change (and subsequent calls to hashCode() should just return the cached value).
From your description it seems that order doesn't matter. If this is so, use a Set. Java's standard implementation is the HashSet.
Most efficient for repeated lookup would almost certainly be an EnumSet
... Enum sets are represented internally as bit vectors. This representation is extremely compact and efficient. The space and time performance of this class should be good enough to allow its use as a high-quality, typesafe alternative to traditional int-based "bit flags." Even bulk operations (such as containsAll and retainAll) should run very quickly if their argument is also an enum set.
...
Implementation note: All basic operations execute in constant time. They are likely (though not guaranteed) to be much faster than their HashSet counterparts. Even bulk operations execute in constant time if their argument is also an enum set.
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When to use HashMap over LinkedList or ArrayList and vice-versa
Since coming across Maps in Java i have been using them extensively. In particular HashMap is an excellent option for many scenarios. It seems that it trumps an ArrayList in every category - some say that iteration isn't predictable but for that we have the LinkedHashMap.
So, my question is: why not use a HashMap all the time provided we have a solid immutable key?
Additionally, is it appropriate to use a something like a HashMap for a very small (<10) number of items or is there some additional overhead I am not considering?
Use an ArrayList when your keys are sequential integers. (If they aren't based at 0, just use an offset.) It's much more efficient for access (particularly random access) and update. Otherwise, sure, HashMap (or, as you say, LinkedHashMap) are extremely useful data structures.
I believe that the default initial size for a HashMap is 16 buckets, so there's a bit of overhead for very small lists. But unless you're creating a lot of maps, it shouldn't be a factor in your coding.
HashMap has a significant amount of overhead compared to an array (or ArrayList):
You need to hash the key to get an index into the backing array, then store the value and the key. This is slower and uses more memory than an array. This is more important when your key is something large or complicated, since it will take longer to hash or take more space.
You also need to hash the key every time you look up a value.
When you resize an ArrayList, you just create a new array and copy everything. When you resize a HashMap, you create a new array, then calculate the hashes all over again (so they'll be spread out through the new array).
HashMap's perform badly when they're full, so they generally leave something like 25% of their space empty.
These are all pretty minor, so you could get away with just using HashMaps all the time (in fact, this is what PHP seems to do), but it's wasteful to use a HashMap when you don't really need it.
A comparison might be helpful: Anything you can do with an integer, you can also do with a string, so why do we have integers? Because they're smaller and faster to work with (and provide some nice guarantees, like that they always contain a number).
I use Maps all the time - it is one of the most powerful and versatile data structures. I mostly use LinkedHashMap but, when working with Strings as key I use TreeMap because of the additional benefit of having the keys sorted.
However:
if your key is an int and you plan to use all the keys 0..n,use
an array (remember - int is more efficient than Integer). But a map is better if you have "sparse values"
if you need a list of unindexed items, use a linkedlist
if you need to store unique elements, use a set (why waste space to keep the values if you just need the keys)!
Remember - Java gives you very powerful collections (Set, Map,List) and, for each one, multiple implementations with different features - they are there for a reason.
Every data structure has its use, even if many can be implemented using a map as a backend, the most appropriate data structure is... more appropriate (and, usually, more efficient, with less overhead and providing more functionalities)
The size does not matter - 5 or 500 elements, if it looks like a map, use a map (there maybe few exceptions and corner cases where you need maximum efficiency and hard coded values are better). But if it looks like a set - use a set!
Assume you need to store/retrieve items in a Collection, don't care about ordering, and duplicates are allowed, what type of Collection do you use?
By default, I've always used ArrayList, but I remember reading/hearing somewhere that a Queue implementation may be a better choice. A List allows items to be added/retrieved/removed at arbitrary positions, which incurs a performance penalty. As a Queue does not provide this facility it should in theory be faster when this facility is not required.
I realise that all discussions about performance are somewhat meaningless, the only thing that really matters is measurement. Nevertheless, I'm interested to know what others use for a Collection, when they don't care about ordering, and duplicates are allowed, and why?
"It depends". The question you really need to answer first is "What do I want to use the collection for?"
If you often insert / remove items on one of the ends (beginning, end) a Queue will be better than a ArrayList. However in many cases you create a Collection in order to just read from it. In this case a ArrayList is far more efficient: As it is implemented as an array, you can iterate over it quite efficient (same applies for a LinkedList). However a LinkedList uses references to link single items together. So if you do not need random removals of items (in the middle), a ArrayList is better: An ArrayList will use less memory as the items don't need the storage for the reference to the next/prev item.
To sum it up:
ArrayList = good if you insert once and read often (random access or sequential)
LinkedList = good if you insert/remove often at random positions and read only sequential
ArrayDeque (java6 only) = good if you insert/remove at start/end and read random or sequential
As a default, I tend to prefer LinkedList to ArrayList. Obviously, I use them not through the List interface, but rather through the Collection interface.
Over the time, I've indeed found out that when I need a generic collection, it's more or less to put some things in, then iterate over it. If I need more evolved behaviour (say random access, sorting or unicity checks), I will then maybe change the used implementation, but before that I will change the used interface to the most appropriated. This way, I can ensure feature is provided before to concentrate on optimization and implementation.
ArrayList basicly contains an array inside (that's why it is called ArrayList). And operations like addd/remove at arbitrary positions are done in a straightforward way, so if you don't use them - there is no harm to performance.
If ordering and duplicates is not a problem and case is only for storing,
I use ArrayList, As it implements all the list operations. Never felt any performance issues with these operations (Never impacted my projects either). Actually using these operations have simple usage & I don't need to care how its managed internally.
Only if multiple threads will be accessing this list I use Vector because its methods are synchronized.
Also ArrayList and Vector are collections which you learn first :).
It depends on what you know about it.
If I have no clue, I tend to go for a linked list, since the penalty for adding/removing at the end is constant. If I have a rough idea of the maximum size of it, I go for an arraylist with the capacity specified, because it is faster if the estimation is good. If I really know the exact size I tend to go for a normal array; although that isn't really a collection type.
I realise that all discussions about performance are somewhat meaningless, the only thing that really matters is measurement.
That's not necessarily true.
If your knowledge of how the application is going to work tells you that certain collections are going to be very large, then it is a good idea to pick the right collection type. But the right collection type depends crucially on how the collections are going to be used; i.e. on the algorithms.
For example, if your application is likely to be dominated by testing if a collection holds a given object, the fact that Collection.contains(Object) is O(N) for both LinkedList<T> and ArrayList<T> might mean that neither is an appropriate collection type. Instead, maybe you should represent the collection as a HashMap<T, Integer>, where the Integer represents the number of occurrences of a T in the "collection". That will give you O(1) testing and removal, at the cost of more space overheads and slower (though still O(1)) insertion.
But the thing to stress is that if you are likely to be dealing with really large collections, there should be no such thing as a "default" collection type. You need to think about the collection in the context of the algorithms. (And the flip side is that if the collections are always going to be small, it probably makes little difference which collection type you pick.)