What's the (hidden) cost of Scala's lazy val? - performance

Question

One handy feature of Scala is lazy val, where the evaluation of a val is delayed until it's necessary (at first access).
Of course, a lazy val must have some overhead - somewhere Scala must keep track of whether the value has already been evaluated and the evaluation must be synchronized, because multiple threads might try to access the value for the first time at the same time.
What exactly is the cost of a lazy val - is there a hidden boolean flag associated with a lazy val to keep track if it has been evaluated or not, what exactly is synchronized and are there any more costs?
In addition, suppose I do this:
class Something {
lazy val (x, y) = { ... }
}
Is this the same as having two separate lazy vals x and y or do I get the overhead only once, for the pair (x, y)?

Answer 1

This is taken from the scala mailing list and gives implementation details of lazy in terms of Java code (rather than bytecode):
class LazyTest {
lazy val msg = "Lazy"
}
is compiled to something equivalent to the following Java code:
class LazyTest {
public int bitmap$0;
private String msg;
public String msg() {
if ((bitmap$0 & 1) == 0) {
synchronized (this) {
if ((bitmap$0 & 1) == 0) {
synchronized (this) {
msg = "Lazy";
}
}
bitmap$0 = bitmap$0 | 1;
}
}
return msg;
}
}

Answer 2

It looks like the compiler arranges for a class-level bitmap int field to flag multiple lazy fields as initialized (or not) and initializes the target field in a synchronized block if the relevant xor of the bitmap indicates it is necessary.
Using:
class Something {
lazy val foo = getFoo
def getFoo = "foo!"
}
produces sample bytecode:
0 aload_0 [this]
1 getfield blevins.example.Something.bitmap$0 : int [15]
4 iconst_1
5 iand
6 iconst_0
7 if_icmpne 48
10 aload_0 [this]
11 dup
12 astore_1
13 monitorenter
14 aload_0 [this]
15 getfield blevins.example.Something.bitmap$0 : int [15]
18 iconst_1
19 iand
20 iconst_0
21 if_icmpne 42
24 aload_0 [this]
25 aload_0 [this]
26 invokevirtual blevins.example.Something.getFoo() : java.lang.String [18]
29 putfield blevins.example.Something.foo : java.lang.String [20]
32 aload_0 [this]
33 aload_0 [this]
34 getfield blevins.example.Something.bitmap$0 : int [15]
37 iconst_1
38 ior
39 putfield blevins.example.Something.bitmap$0 : int [15]
42 getstatic scala.runtime.BoxedUnit.UNIT : scala.runtime.BoxedUnit [26]
45 pop
46 aload_1
47 monitorexit
48 aload_0 [this]
49 getfield blevins.example.Something.foo : java.lang.String [20]
52 areturn
53 aload_1
54 monitorexit
55 athrow
Values initialed in tuples like lazy val (x,y) = { ... } have nested caching via the same mechanism. The tuple result is lazily evaluated and cached, and an access of either x or y will trigger the tuple evaluation. Extraction of the individual value from the tuple is done independently and lazily (and cached). So the above double-instantiation code generates an x, y, and an x$1 field of type Tuple2.

Answer 3

With Scala 2.10, a lazy value like:
class Example {
lazy val x = "Value";
}
is compiled to byte code that resembles the following Java code:
public class Example {
private String x;
private volatile boolean bitmap$0;
public String x() {
if(this.bitmap$0 == true) {
return this.x;
} else {
return x$lzycompute();
}
}
private String x$lzycompute() {
synchronized(this) {
if(this.bitmap$0 != true) {
this.x = "Value";
this.bitmap$0 = true;
}
return this.x;
}
}
}
Note that the bitmap is represented by a boolean. If you add another field, the compiler will increase the size of the field to being able to represent at least 2 values, i.e. as a byte. This just goes on for huge classes.
But you might wonder why this works? The thread-local caches must be cleared when entering a synchronized block such that the non-volatile x value is flushed into memory. This blog article gives an explanation.

Answer 4

Scala SIP-20 proposes a new implementation of lazy val, which is more correct but ~25% slower than the "current" version.
The proposed implementation looks like:
class LazyCellBase { // in a Java file - we need a public bitmap_0
public static AtomicIntegerFieldUpdater<LazyCellBase> arfu_0 =
AtomicIntegerFieldUpdater.newUpdater(LazyCellBase.class, "bitmap_0");
public volatile int bitmap_0 = 0;
}
final class LazyCell extends LazyCellBase {
import LazyCellBase._
var value_0: Int = _
#tailrec final def value(): Int = (arfu_0.get(this): #switch) match {
case 0 =>
if (arfu_0.compareAndSet(this, 0, 1)) {
val result = 0
value_0 = result
#tailrec def complete(): Unit = (arfu_0.get(this): #switch) match {
case 1 =>
if (!arfu_0.compareAndSet(this, 1, 3)) complete()
case 2 =>
if (arfu_0.compareAndSet(this, 2, 3)) {
synchronized { notifyAll() }
} else complete()
}
complete()
result
} else value()
case 1 =>
arfu_0.compareAndSet(this, 1, 2)
synchronized {
while (arfu_0.get(this) != 3) wait()
}
value_0
case 2 =>
synchronized {
while (arfu_0.get(this) != 3) wait()
}
value_0
case 3 => value_0
}
}
As of June 2013 this SIP hasn't been approved. I expect that it's likely to be approved and included in a future version of Scala based on the mailing list discussion. Consequently, I think you'd be wise to heed Daniel Spiewak's observation:
Lazy val is *not* free (or even cheap). Use it only if you absolutely
need laziness for correctness, not for optimization.

Answer 5

I've written a post with regard to this issue https://dzone.com/articles/cost-laziness
In nutshell, the penalty is so small that in practice you can ignore it.

Answer 6

given the bycode generated by scala for lazy, it can suffer thread safety problem as mentioned in double check locking http://www.javaworld.com/javaworld/jw-05-2001/jw-0525-double.html?page=1