Could you guys help me out with using Array and stream (?) over it to use single element (String) to save Movie to db and return FLux. Spring specific stuff isn't important - just the way to iterate over alphabet and create random Movies. What's the best and most-kotlinish way of doing this?
val alphabet = arrayOf("A".."Z")
val exampleMovies: Flux<Movie> = Flux.just(alphabet)
.flatMap { movieRepository.save(Movie(name = it)) }
I'm getting compilation error:
Error:(15, 62) Kotlin: Type mismatch: inferred type is Array<ClosedRange<String>>! but String? was expected
The problem is that arrayOf("A".."Z") will give an Array<ClosedRange<String>>, i.e. the array has one element of type ClosedRange. What you actually wanted to have is an Array<String> with elements A, B, C, ..., Z I guess? Unfortunately, the range operator doesn't work like this for Strings, explained here.
Instead, create that array by mapping a CharRange accordingly:
val alphabet = ('A'..'Z').map(Char::toString).toTypedArray()
Related
So I got a question that was delivered as a 2D List
val SPE = listOf(
listOf('w', 'x'),
listOf('x', 'y'),
listOf('z', 'y'),
listOf('z', 'v'),
listOf('w', 'v')
)
It asks to find the shortest path between w and z. So obviously, BFS would be the best course of action here to find that path the fastest. Here's my code for it
fun shortestPath(edges: List<List<Char>>, root: Char, destination: Char): Int {
val graph = buildGraph3(edges)
val visited = hashSetOf(root)
val queue = mutableListOf(mutableListOf(root, 0))
while (queue.size > 0){
val node = queue[0].removeFirst()
val distance = queue[0].removeAt(1)
if (node == destination) return distance as Int
graph[node]!!.forEach{
if (!visited.contains(it)){
visited.add(it)
queue.add(mutableListOf(it, distance + 1))
}
}
}
queue.sortedByDescending { it.size }
return queue[0][1]
}
fun buildGraph3(edges: List<List<Char>>): HashMap<Char, MutableList<Char>> {
val graph = HashMap<Char, MutableList<Char>>()
for (i in edges.indices){
for (n in 0 until edges[i].size){
var a = edges[i][0]
var b = edges[i][1]
if (!graph.containsKey(a)) { graph[a] = mutableListOf() }
if (!graph.containsKey(b)) { graph[b] = mutableListOf() }
graph[a]?.add(b)
graph[b]?.add(b)
}
}
return graph
}
I am stuck on the return part. I wanted to use a list to keep track of the incrementation of the char, but it wont let me return the number. I could have done this wrong, so any help is appreciated. Thanks.
If I paste your code into an editor I get this warning on your return queue[0][1] statement:
Type mismatch: inferred type is {Comparable<*> & java.io.Serializable} but Int was expected
The problem here is queue contains lists that hold Chars and Int distances, mixed together. You haven't specified the type that list holds, so Kotlin has to infer it from the types of the things you've put in the list. The most general type that covers both is Any?, but the compiler tries to be as specific as it can, inferring the most specific type that covers both Char and Int.
In this case, that's Comparable<*> & java.io.Serializable. So when you pull an item out with queue[0][1], the value you get is a Comparable<*> & java.io.Serializable, not an Int, which is what your function is supposed to be returning.
You can "fix" this by casting - since you know how your list is meant to be organised, two elements with a Char then an Int, you can provide that information to the compiler, since it has no idea what you're doing beyond what it can infer:
val node = queue[0].removeFirst() as Char
val distance = queue[0].removeAt(1) as Int
...
return queue[0][1] as Int
But ideally you'd be using the type system to create some structure around your data, so the compiler knows exactly what everything is. The most simple, generic one of these is a Pair (or a Triple if you need 3 elements):
val queue = mutableListOf(Pair<Char, Int>(root, 0))
// or if you don't want to explicitly specify the type
val queue = mutableListOf(root to 0)
Now the type system knows that the items in your queue are Pairs where the first element is a Char, and the second is an Int. No need to cast anything, and it will be able to help you as you try to work with that data, and tell you if you're doing the wrong thing.
It might be better to make actual classes that reflect your data, e.g.
data class Step(node: Char, distance: Int)
because a Pair is pretty general, but it's up to you. You can pull the data out of it like this:
val node = queue[0].first
val distance = queue[0].second
// or use destructuring to assign the components to multiple variables at once
val (node, distance) = queue[0]
If you make those changes, you'll have to rework some of your algorithm - but you'll have to do that anyway, it's broken in a few ways. I'll just give you some pointers:
your return queue[0][1] line can only be reached when queue is empty
queue[0].removeAt(1) is happening on a list that now has 1 element (i.e. at index 0)
don't you need to remove items from your queue instead?
when building your graph, you call add(b) twice
try printing your graph, the queue at each stage in the loop etc to see what's happening! Make sure it's doing what you expect. Comment out any code that doesn't work so you can make sure the stuff that runs before that is working.
Good luck with it! Hopefully once you get your types sorted out things will start to fall into place more easily
I have a list of A class objects
data class A{
val abc: Abc
val values: Int?
}
val list = List<A>
If I want to count how many objects I have in list I use:
val count= a.count()
or val count= a.count(it -> {})
How to append all values in the list of objects A avoiding for loop? Generaly Im looking for proper kotlin syntax with avoiding code below
if (a!= null) {
for (i in list) {
counter += i.values!!
}
}
Either use sumBy or sum in case you have a list of non-nullable numbers already available, i.e.:
val counter = list.sumBy { it.values ?: 0 }
// or
val counter = extractedNonNullValues.sum()
The latter only makes sense if you already mapped your A.values before to a list of non-nullable values, e.g. something like:
val extractedNonNullValues= list.mapNotNull { it.values } // set somewhere else before because you needed it...
If you do not need such an intermediate extractedNonNullValues-list then just go for the sumBy-variant.
I don't see you doing any appending to a list in the question. Based on your for loop I believe what you meant was "How do I sum properties of objects in my list". If that's the case you can use sumBy, the extension function on list that takes a labmda: ((T) -> Int) and returns an Int like so:
val sum = list.sumBy { a -> a.values ?: 0 }
Also, calling an Int property values is pretty confusing, I think it should be called value. The plural indicates a list...
On another note, there is a possible NPE in your original for loop. Avoid using !! on nullable values as, if the value is null, you will get an NPE. Instead, use null coalescing (aka elvis) operator to fall back to a default value ?: - this is perfectly acceptable in a sum function. If the iteration is not to do with summing, you may need to handle the null case differently.
So I have some json response content represented as string and I want to get its property names.
What I am doing
let properties = Newtonsoft.Json.Linq.JObject.Parse(responseContent).Properties()
let propertyNames, (jprop: JProperty) = properties.Select(jprop => jprop.Name);
According to this answer I needed to annotate the call to the extension method, however, I still get the error.
A unique overload for method 'Select' could not be determined based on type information prior to this program point. A type annotation may be needed. Candidates: (extension) Collections.Generic.IEnumerable.Select<'TSource,'TResult>(selector: Func<'TSource,'TResult>) : Collections.Generic.IEnumerable<'TResult>, (extension) Collections.Generic.IEnumerable.Select<'TSource,'TResult>(selector: Func<'TSource,int,'TResult>) : Collections.Generic.IEnumerable<'TResult>
Am I doing something wrong?
First, the syntax x => y you're trying to use is C# syntax for lambda expressions, not F# syntax. In F#, the correct syntax for lambda-expressions is fun x -> y.
Second, the syntax let a, b = c means "destructure the pair". For example:
let pair = (42, "foo")
let a, b = pair // Here, a = 42 and b = "foo"
You can provide a type annotation for one of the pair elements:
let a, (b: string) = pair
But this won't have any effect on pair the way you apparently expect it to work.
In order to provide type annotation for the argument of a lambda expression, just annotate the argument, what could be simpler?
fun (x: string) -> y
So, putting all of the above together, this is how your line should look:
let propertyNames = properties.Select(fun (jprop: JProperty) -> jprop.Name)
(also, note the absence of semicolon at the end. F# doesn't require semicolons)
If you have this level of difficulty with basic syntax, I suggest you read up on F# and work your way through a few examples before trying to implement something complex.
I'm interested in building a Huffman Coding prototype. To that end, I want to begin by producing a histogram of the characters that make up an input Java String. I've seen many solutions on SO and elsewhere (e.g:here that depend on using the collect() methods for Streams as well as static imports of Function.identity() and Collectors.counting() in a very specific and intuitive way.
However, when using a piece of code eerily similar to the one I linked to above:
private List<HuffmanTrieNode> getCharsAndFreqs(String s){
Map<Character, Long> freqs = s.chars().collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));
return null;
}
I receive a compile-time-error from Intellij which essentially tells me that there is no arguments to collect that conforms to a Supplier type, as required by its signature:
Unfortunately, I'm new to the Java 8 Stream hierarchy and I'm not entirely sure what the best course of action for me should be. In fact, going the Map way might be too much boilerplate for what I'm trying to do; please advise if so.
The problem is that s.chars() returns an IntStream - a particular specialization of Stream and it does not have a collect that takes a single argument; it's collect takes 3 arguments. Obviously you can use boxed and that would transform that IntStream to Stream<Integer>.
Map<Integer, Long> map = yourString.codePoints()
.boxed()
.collect(Collectors.groupingBy(
Function.identity(),
Collectors.counting()));
But now the problem is that you have counted code-points and not chars. If you absolutely know that your String is made from characters in the BMP, you can safely cast to char as shown in the other answer. If you are not - things get trickier.
In that case you need to get the single unicode code point as a character - but it might not fit into a Java char - that has 2 bytes; and a unicode character can be up to 4 bytes.
In that case your map should be Map<String, Long> and not Map<Character, Long>.
In java-9 with the introduction of supported \X (and Scanner#findAll) this is fairly easy to do:
String sample = "A" + "\uD835\uDD0A" + "B" + "C";
Map<String, Long> map = scan.findAll("\\X")
.map(MatchResult::group)
.collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));
System.out.println(map); // {A=1, B=1, C=1, 𝔊=1}
In java-8 this would be a bit more verbose:
String sample = "AA" + "\uD835\uDD0A" + "B" + "C";
Map<String, Long> map = new HashMap<>();
Pattern p = Pattern.compile("\\P{M}\\p{M}*+");
Matcher m = p.matcher(sample);
while (m.find()) {
map.merge(m.group(), 1L, Long::sum);
}
System.out.println(map); // {A=2, B=1, C=1, 𝔊=1}
The String.chars() method returns an IntStream. You probably want to convert it to a Stream<Character> via:
s.chars().mapToObj(c -> (char)c)
As already pointed, you could transform the stream to primitive types to Object types.
s.chars().boxed()
.collect(Collectors.groupingBy(Function.identity(), Collectors.counting()));
Using Scala and Spark, I have the following construction:
val rdd1: RDD[String] = ...
val rdd2: RDD[(String, Any)] = ...
val rdd1pairs = rdd1.map(s => (s, s))
val result = rdd2.join(rdd1pairs)
.map { case (_: String, (e: Any, _)) => e }
The purpose of mapping rdd1 into a PairRDD is the join with rdd2 in the subsequent step. However, I am actually only interested in the values of rdd2, hence the mapping step in the last line which omits the keys. Actually, this is an intersection between rdd2 and rdd1 performed with Spark's join() for efficiency reasons.
My question refers to the keys of rdd1pairs: they are created for syntactical reasons only (to allow the join) in the first map step and are later discarded without any usage. How does the compiler handle this? Does it matter in terms of memory consumption whether I use the String s (as shown in the example)? Should I replace it by null or 0 to save a little memory? Does the compiler actually create and store these objects (references) or does it notice that they are never used?
In this case, it is what the Spark driver will do that influences the outcome rather than the compiler, I think. Whether or not Spark can optimise its execution pipeline in order to avoid creating the redundant duplication of s. I'm not sure but I think Spark will create the rdd1pairs, in memory.
Instead of mapping to (String, String) you could use (String, Unit):
rdd1.map(s => (s,()))
What you're doing is basically a filter of rdd2 based on rdd1. If rdd1 is significantly smaller than rdd2, another method would be to represent the data of rdd1 as a broadcast variable rather than an RDD, and simply filter rdd2. This avoids any shuffling or reduce phase, so may be quicker, but will only work if the data of rdd1 is small enough to fit on each node.
EDIT:
Considering how using Unit rather than String saves space, consider the following examples:
object size extends App {
(1 to 1000000).map(i => ("foo"+i, ()))
val input = readLine("prompt> ")
}
and
object size extends App {
(1 to 1000000).map(i => ("foo"+i, "foo"+i))
val input = readLine("prompt> ")
}
Using the jstat command as described in this question How to check heap usage of a running JVM from the command line? the first version uses significantly less heap than the latter.
Edit 2:
Unit is effectively a singleton object with no contents, so logically, it should not require any serialization. The fact that the type definition contains Unit tells you all you need to be able to deserialize a structure which has a field of type Unit.
Spark uses Java Serialization by default. Consider the following:
object Main extends App {
import java.io.{ObjectOutputStream, FileOutputStream}
case class Foo (a: String, b:String)
case class Bar (a: String, b:String, c: Unit)
val str = "abcdef"
val foo = Foo("abcdef", "xyz")
val bar = Bar("abcdef", "xyz", ())
val fos = new FileOutputStream( "foo.obj" )
val fo = new ObjectOutputStream( fos )
val bos = new FileOutputStream( "bar.obj" )
val bo = new ObjectOutputStream( bos )
fo writeObject foo
bo writeObject bar
}
The two files are of identical size:
�� sr Main$Foo3�,�z \ L at Ljava/lang/String;L bq ~ xpt abcdeft xyz
and
�� sr Main$Bar+a!N��b L at Ljava/lang/String;L bq ~ xpt abcdeft xyz