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This page is for Scala performance coding hints that should be used for performance critical code, such as the repetitive places in the Daffodil runtime module.

These ideas basically amount to writing "java-like" Scala code. 

Do not use this style except in performance critical areas, as it makes the code less readable, less compact, much harder to get correct, etc.

Hopefully in the future improvements in JVMs and the Scala compiler will make some of these techniques less necessary.

Here's a link to a page about Java performance coding - avoiding unnecessary allocation for Java code. The same principles apply to Scala code:

Avoid Unnecessary Allocation

Many things in Scala cause allocation of objects on the heap. This involves quite a lot of overhead to allocate the object (which has extra locations in it beyond the members), initialize memory, call the constructor, etc.

Measurements have often shown allocation to be a large cost, so there is a bunch of techniques for avoiding excess allocation.

Avoid Passing Functions - While Loops for Iteration - or Macros

Scala's map, flatmap, fold, reduce, foreach, etc. All these things take a function argument. Due to JVM issues, even though these functions are only used downward, they still end up allocated on the heap.

In general this means writing plain-old while-loops instead of Scala's much more compact idioms.

In some cases Macros can be used to create something about as compact as a scala map/fold idiom but without expressing a function object at all. See LoggerMacros.scala for examples of this.

Avoid Passing Functions - By Name Arguments - Use Macros

Code like this

def foo (a: Int, b : => Int) = { .... }

Every time method foo is called, a little function closure is allocated for the 'b' argument passing.

Probably the worst offender in this is

val opt : Option[Foo] = ....

opt.getOrElse(Assert.invariantFailed("opt should be defined")) // allocates closure around assertion.

So don't call getOrElse in performance code!

In our own classes, a macro can often be used instead to avoid the need for the by-name argument. (See AssertMacros.scala and/or LoggerMacros.scala for examples of this)

Avoid Return Objects and Tuples

These are often used to pass information back to the caller of a more complex nature, but then are discarded.

The alternative is to pass in a mutable object that is filled in by the called method. (See OnStack/LocalStack below about where that mutable object might come from.)

For the very common case of wanting to return an optional result, e.g., where you would want to return Option[T], instead return a Maybe[T] for objects, and use MaybeInt, MaybeLong, etc. for numbers. See below about avoiding Option type.

Similar common return types are small tuples of values, and the Either[L, R] and Try[T] types.

See also the Cursor & Accessor Idiom below.

Avoid Option Type - Use Maybe Family of Types

Scala's Option type (Some, None) involves a heap-allocated object to represent the Some case. Furthermore, if you make a

val foo: Option[Int] = Some(5)

That's two objects. Because the 5 has to be boxed so that it can appear in the generic "collection" type Some. 

We have a AnyVal-derived family of Maybe types. There are specialized variants for the unboxed types like Int

val foo: MaybeInt = MaybeInt(5)
val bar: MaybeInt = MaybeInt.Nope

For objects, the basic

val foo : Maybe[String] = One("foobar")

However, see below about MStack and generic collections.

Built-in Scala libraries often make heavy use of the Option type. See section about HashMap below.

Avoid match-case with Pattern Matching

Scala's very nice match-case, and case classes uses Option types underneath in the matching.

Instead of this:

foo match {
case Foo(a, b) => ....

Write this instead:

foo match {
case f: Foo => { val a = f.a ; val b = f.b ; ....

This doesn't allocate in execution.

Avoid scala.collections.HashMap. Use Java HashMap Instead

This is a library instance of the "avoid Option type" problem.

Scala's mutable HashMap allocates a Some[T] object for every successful get(key) call.

This is unacceptable overhead for something done so frequently. Use Java's HashMap instead, where get(key) returns a value or null, and never allocates anything.

Avoid Generic Collections of Unboxed Types

val boxedInts = new ArrayBuffer(len)  // adding an Int allocates a box every time. Accessing an Int discards the box.
var unboxedInts = new Array[Int](len) // Non allocating - note var idea - in case you need to resize it.

Use MStack, avoid mutable.Stack

We need lots of stacks, and since Scala's general stacks are generic collections, we created our own non-boxing flavors:

  • MStack.Of[T] - generic
  • MStack.OfInt - stack of Int - non-boxing
  • MStack.OfMaybe[T] - doesn't create box for the Maybe object. Uses null for Nope, and a regular object reference for One.
    • However, MStackOfMaybe[Int] will box and unbox the Int
    • Note JIRA issue DFDL-1456 - MStack.OfMaybe[T] really should not be accepting and returning null or object, it should be accepting and returning Maybe[T], and just storing internally as null vs object to avoid boxing the Maybe[T]

Allocate on "the stack" Using OnStack and LocalStack

TBD: See the definitions of these. These make it convenient to reuse objects in recursive code, as is common in Daffodil. A small pool of reusable objects is maintained per thread. Accessing one causes it to either be created, or an existing one initialized. They get put back on exit of scope, and Scala 2.11's macros are used to avoid allocating closure objects as well.

Use Reusable Pools of Stored Objects

When reusable objects do not follow a stack discipline, then you can still reuse them by pooling them.

TBD: See Pool.scala for a common pooling idiom

Iteration Patterns - Avoid Iterators - Use Cursors and Accessors

(New stuff - being added as part of Unparser work - 2015-12-11)

If you consider that we have to avoid scala's nice generic collection functional operations like foreach and map, one might be tempted to just use the Iterator[T] class.

However, if the generic type T here is a value type (e.g., Int, or Long or Boolean) then calling next() will return a boxed object. Whether that box is saved somewhere or is being created and discarded immediately depends on what you are iterating over.

But the real issue here is about return objects - when they're not just returned from a method call, but you want to iterate over them.

We want to iterate over something, but the items in whatever we're iterating are aggregates of things that we immediately want to just break apart and use the pieces.

val iter : Iterator[(String, String)] = ....
val (left, right) =

Now each time we iterate, an object is created for return from (that is unless that object already exists in some collection, but in many cases it doesn't exist.)

An alternative idiom is the Cursor & Accessor pattern:

case class R(var left: String, var right: String) extends Accessor[R] { // note mutable vars !
   def cpy(): R = R(left, right)
   def assignFrom(other: R) { 
      this.left = other.left
      this.right = other.right

class RCursor[R] extends Cursor[R] {

    val advanceAccessor = R(null, null)

    override def advance : Boolean = { ... }

The idea here is you call the advance method, and it returns a boolean telling you if it was able to advance the cursor to another object. The object is "returned" by side-effecting the accessor. Each call to advance clobbers the same object. This is a way to iterate over vast amounts of complex data without having to create any objects.

There is also an inspect method (which works like peek() - looks ahead at next thing, but doesn't 'advance' to it. It fills in a different accessor so that you don't have to copy to look at the current and next items simultaneously.

If you want to revert to using ordinary Scala idioms like collections and Iterators you can copy the accessor, or assign to them with methods on the Accessor class (cpy and assignFrom).

See Cursor.scala for the traits.




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