Weird exception when using .view on list - scala

I had quite a big list of numbers. I needed to apply some operation on them, then take only those results that satisfy some condition. The list is sequential, so once I find the number that does not satisfy the condition, I can stop looking.
I wanted to avoid doing too much computation, so I moved on like in this example:
List(1,2,3,4,5).view.map(2 *).takeWhile(_ < 8)
But it gives me an exception:
java.lang.UnsupportedOperationException: SeqViewM(...).newBuilder
at scala.collection.TraversableViewLike$class.newBuilder(TraversableViewLike.scala:69)
at scala.collection.SeqViewLike$$anon$3.newBuilder(SeqViewLike.scala:77)
at scala.collection.IterableLike$class.takeWhile(IterableLike.scala:139)
at scala.collection.SeqViewLike$$anon$3.takeWhile(SeqViewLike.scala:77)
at scala.collection.SeqViewLike$$anon$3.takeWhile(SeqViewLike.scala:77)
Using Scala 2.9.0.1 (same behavior with 2.9.1). What is wrong here?

Looks like a bug. (File a bug report, if it's not already reported and/or fixed!)
In the meantime, you can use iterator as a workaround for this particular code:
List(1,2,3,4,5).iterator.map(2 *).takeWhile(8 >).toList
(drop the .toList if you're happy to end up with an iterator).

Related

Scala spark: Efficient check if condition is matched anywhere?

What I want is roughly equivalent to
df.where(<condition>).count() != 0
But I'm pretty sure it's not quite smart enough to stop once it finds any such violation. I would expect some sort of aggregator to be able to do this, but I haven't found one? I could do it with a max and some sort of conversion, but again I don't think it would necessarily know to quit (not being specific to bool, I'm not sure if understands no value is larger than true).
More specifically, I want to check if a column contains only a single element. Right now my best idea is to do this is by grabbing the first value and comparing everything.
I would try this option, it should be much faster:
df.where(<condition>).head(1).isEmpty
You can also try to define your conditions on a row together with scala's exists (which stops at the first occurence of true):
df.mapPartitions(rows => if(rows.exists(row => <condition>)) Iterator(1) else Iterator.empty).isEmpty
At the end you should benchmark the alternatives

Why doesn't scala's parallel sequences have a contains method?

Why does
List.range(0,100).contains(2)
Work, while
List.range(0,100).par.contains(2)
Does not?
This is planned for the future?
The non-teleological answer is that it's because contains is defined in SeqLike but not in ParSeqLike.
If that doesn't satisfy your curiosity, you can find that SeqLike's contains is defined thus:
def contains(elem: Any): Boolean = exists (_ == elem)
So for your example you can write
List.range(0,100).par.exists(_ == 2)
ParSeqLike is missing a few other methods as well, some of which would be hard to implement efficiently (e.g. indexOfSlice) and some for less obvious reasons (e.g. combinations - maybe because that's only useful on small datasets). But if you have a parallel collection you can also use .seq to get back to the linear version and get your methods back:
List.range(0,100).par.seq.contains(2)
As for why the library designers left it out... I'm totally guessing, but maybe they wanted to reduce the number of methods for simplicity's sake, and it's nearly as easy to use exists.
This also raises the question, why is contains defined on SeqLike rather than on the granddaddy of all collections, GenTraversableOnce, where you find exists? A possible reason is that contains for Map is semantically a different method to that on Set and Seq. A Map[A,B] is a Traversable[(A,B)], so if contains were defined for Traversable, contains would need to take a tuple (A,B) argument; however Map's contains takes just an A argument. Given this, I think contains should be defined in GenSeqLike - maybe this is an oversight that will be corrected.
(I thought at first maybe parallel sequences don't have contains because searching where you intend to stop after finding your target on parallel collections is a lot less efficient than the linear version (the various threads do a lot of unnecessary work after the value is found: see this question), but that can't be right because exists is there.)

Scala linked list stackoverflow

Using scala I have added about 100000 nodes to a linked list. When I use the function length, for example mylist.length. I get a 'java.lang.StackOverflowError' error, is my list to big to process? The list is only string objects.
It appears the library implementation is not tail-recursive override def length: Int = if (isEmpty) 0 else next.length + 1. It seems like this is something that could be discussed on the mailing list to check if an enhancement ticket should be opened.
You can compute the length like this:
def length[T](l:LinkedList[T], acc:Int=0): Int =
if (l.isEmpty) acc else length(l.tail, acc + 1)
In Scala, computing the length of a List is an order n operation, therefore you should try to avoid it. You might consider switching to an Array, as that is a constant time operation.
You could try increasing the stack/heap size available to the JVM.
scala JAVA_OPTS="-Xmx512M -Xms16M -Xss16M" MyClass.scala
Where
-Xss<size> maximum native stack size for any thread
-Xms<size> set initial Java heap size
-Xmx<size> set maximum Java heap size
This question has some more information.
See also this This Scala document.
Can you confirm that you truly need to use the length method? It sounds like you might not be using the correct collection type for your use-case (hard to tell without any extra information). Lists are optimised to be mapped over using folds or a tail-recursive function.
Despite saying that, this is absolutely an oversight that can easily be fixed in the standard library with a tail-recursive function. Hopefully we can get it in time for 2.9.0.

head and tail calls on empty list bringing an exception

I'm following a tutorial. (Real World Haskell)
And I have one beginner question about head and tail called on empty lists: In GHCi it returns exception.
Intuitively I think I would say they both should return an empty list. Could you correct me ? Why not ? (as far as I remember in OzML left or right of an empty list returns nil)
I surely have not yet covered this topic in the tutorial, but isnt it a source of bugs (if providing no arguments)?
I mean if ever passing to a function a list of arguments which may be optionnal, reading them with head may lead to a bug ?
I just know the GHCi behaviour, I don't know what happens when compiled.
Intuitively I think would say they both should return an empty list. Could you correct me ? Why not ?
Well - head is [a] -> a. It returns the single, first element; no list.
And when there is no first element like in an empty list? Well what to return? You can't create a value of type a from nothing, so all that remains is undefined - an error.
And tail? Tail basically is a list without its first element - i.e. one item shorter than the original one. You can't uphold these laws when there is no first element.
When you take one apple out of a box, you can't have the same box (what happened when tail [] == []). The behaviour has to be undefined too.
This leads to the following conclusion:
I surely have not yet covered this topic in the tutorial, but isnt it a source of bugs ? I mean if ever passing to a function a list of arguments which may be optionnal, reading them with head may lead to a bug ?
Yes, it is a source of bugs, but because it allows to write flawed code. Code that's basically trying to read a value that doesn't exist. So: *Don't ever use head/tail** - Use pattern matching.
sum [] = 0
sum (x:xs) = x + sum xs
The compiler can guarantee that all possible cases are covered, values are always defined and it's much cleaner to read.

How to delete elements from a transformed collection using a predicate?

If I have an ArrayList<Double> dblList and a Predicate<Double> IS_EVEN I am able to remove all even elements from dblList using:
Collections2.filter(dblList, IS_EVEN).clear()
if dblList however is a result of a transformation like
dblList = Lists.transform(intList, TO_DOUBLE)
this does not work any more as the transformed list is immutable :-)
Any solution?
Lists.transform() accepts a List and helpfully returns a result that is RandomAccess list. Iterables.transform() only accepts an Iterable, and the result is not RandomAccess. Finally, Iterables.removeIf (and as far as I see, this is the only one in Iterables) has an optimization in case that the given argument is RandomAccess, the point of which is to make the algorithm linear instead of quadratic, e.g. think what would happen if you had a big ArrayList (and not an ArrayDeque - that should be more popular) and kept removing elements from its start till its empty.
But the optimization depends not on iterator remove(), but on List.set(), which is cannot be possibly supported in a transformed list. If this were to be fixed, we would need another marker interface, to denote that "the optional set() actually works".
So the options you have are:
Call Iterables.removeIf() version, and run a quadratic algorithm (it won't matter if your list is small or you remove few elements)
Copy the List into another List that supports all optional operations, then call Iterables.removeIf().
The following approach should work, though I haven't tried it yet.
Collection<Double> dblCollection =
Collections.checkedCollection(dblList, Double.class);
Collections2.filter(dblCollection, IS_EVEN).clear();
The checkCollection() method generates a view of the list that doesn't implement List. [It would be cleaner, but more verbose, to create a ForwardingCollection instead.] Then Collections2.filter() won't call the unsupported set() method.
The library code could be made more robust. Iterables.removeIf() could generate a composed Predicate, as Michael D suggested, when passed a transformed list. However, we previously decided not to complicate the code by adding special-case logic of that sort.
Maybe:
Collection<Double> odds = Collections2.filter(dblList, Predicates.not(IS_EVEN));
or
dblList = Lists.newArrayList(Lists.transform(intList, TO_DOUBLE));
Collections2.filter(dblList, IS_EVEN).clear();
As long as you have no need for the intermediate collection, then you can just use Predicates.compose() to create a predicate that first transforms the item, then evaluates a predicate on the transformed item.
For example, suppose I have a List<Double> from which I want to remove all items where the Integer part is even. I already have a Function<Double,Integer> that gives me the Integer part, and a Predicate<Integer> that tells me if it is even.
I can use these to get a new predicate, INTEGER_PART_IS_EVEN
Predicate<Double> INTEGER_PART_IS_EVEN = Predicates.compose(IS_EVEN, DOUBLE_TO_INTEGER);
Collections2.filter(dblList, INTEGER_PART_IS_EVEN).clear();
After some tries, I think I've found it :)
final ArrayList<Integer> ints = Lists.newArrayList(1, 2, 3, 4, 5);
Iterables.removeIf(Iterables.transform(ints, intoDouble()), even());
System.out.println(ints);
[1,3,5]
I don't have a solution, instead I found some kind of a problem with Iterables.removeIf() in combination with Lists.TransformingRandomAccessList.
The transformed list implements RandomAccess, thus Iterables.removeIf() delegates to Iterables.removeIfFromRandomAccessList() which depends on an unsupported List.set() operation.
Calling Iterators.removeIf() however would be successful, as the remove() operation IS supported by Lists.TransformingRandomAccessList.
see: Iterables: 147
Conclusion: instanceof RandomAccess does not guarantee List.set().
Addition:
In special situations calling removeIfFromRandomAccessList() even works:
if and only if the elements to erase form a compact group at the tail of the List or all elements are covered by the Predicate.