Lesser Known jOOλ Features: Useful Collectors

jOOλ is our second most popular library. It implements a set of useful extensions to the JDK’s Stream API, which are useful especially when streams are sequential only, which according to our assumptions is how most people use streams in Java.

Such extensions include:

// (1, 2, 3, 1, 2, 3, 1, 2, 3, 1, 2, ...)
Seq.of(1, 2, 3).cycle();

// tuple((1, 2, 3), (1, 2, 3))
Seq.of(1, 2, 3).duplicate();

// (1, 0, 2, 0, 3, 0, 4)
Seq.of(1, 2, 3, 4).intersperse(0);

// (4, 3, 2, 1)
Seq.of(1, 2, 3, 4).reverse();

… and many more.

Collectors

But that’s not the only thing jOOλ offers. It also ships with a set of useful Collectors, which can be used both with JDK streams, as well as with jOOλ’s Seq type. Most of them are available from the org.jooq.lambda.Agg type, where Agg stands for aggregations.

Just like the rest of jOOλ, these collectors are inspired by SQL, and you will find quite a few SQL aggregate functions represented in this class.

Here are some of these collectors:

Counting

While the JDK has Collectors.counting(), jOOλ also has a way to count distinct values, just like SQL:

// A simple wrapper for two values:
class A {
    final String s;
    final long l;
    A(String s, long l) {
        this.s = s;
        this.l = l;
    }

    static A A(String s, long l) {
        return new A(s, l);
    }
}

@Test
public void testCount() {
    assertEquals(7L, (long) 
        Stream.of(1, 2, 3, 3, 4, 4, 5)
              .collect(Agg.count()));
    assertEquals(5L, (long) 
        Stream.of(1, 2, 3, 3, 4, 4, 5)
              .collect(Agg.countDistinct()));
    assertEquals(5L, (long) 
        Stream.of(A("a", 1), 
                  A("b", 2), 
                  A("c", 3), 
                  A("d", 3), 
                  A("e", 4), 
                  A("f", 4), 
                  A("g", 5))
              .collect(Agg.countDistinctBy(a -> a.l)));
    assertEquals(7L, (long) 
        Stream.of(A("a", 1),
                  A("b", 2), 
                  A("c", 3), 
                  A("d", 3), 
                  A("e", 4), 
                  A("f", 4), 
                  A("g", 5))
              .collect(Agg.countDistinctBy(a -> a.s)));
}

These are pretty self explanatory, I think.

Percentiles

Just recently, I’ve blogged about the usefulness of SQL’s percentile functions, and how to emulate them if they’re unavailable.

Percentiles can also be nicely calculated on streams. Why not? As soon as a Stream’s contents implements Comparable, or if you supply your custom Comparator, percentiles are easy to calculate:

// Assuming a static import of Agg.percentile:
assertEquals(
    Optional.empty(), 
    Stream.<Integer> of().collect(percentile(0.25)));
assertEquals(
    Optional.of(1), 
    Stream.of(1).collect(percentile(0.25)));
assertEquals(
    Optional.of(1), 
    Stream.of(1, 2).collect(percentile(0.25)));
assertEquals(
    Optional.of(1), 
    Stream.of(1, 2, 3).collect(percentile(0.25)));
assertEquals(
    Optional.of(1), 
    Stream.of(1, 2, 3, 4).collect(percentile(0.25)));
assertEquals(
    Optional.of(2), 
    Stream.of(1, 2, 3, 4, 10).collect(percentile(0.25)));
assertEquals(
    Optional.of(2), 
    Stream.of(1, 2, 3, 4, 10, 9).collect(percentile(0.25)));
assertEquals(
    Optional.of(2), 
    Stream.of(1, 2, 3, 4, 10, 9, 3).collect(percentile(0.25)));
assertEquals(
    Optional.of(2), 
    Stream.of(1, 2, 3, 4, 10, 9, 3, 3).collect(percentile(0.25)));
assertEquals(
    Optional.of(3), 
    Stream.of(1, 2, 3, 4, 10, 9, 3, 3, 20).collect(percentile(0.25)));
assertEquals(
    Optional.of(3), 
    Stream.of(1, 2, 3, 4, 10, 9, 3, 3, 20, 21).collect(percentile(0.25)));
assertEquals(
    Optional.of(3), 
    Stream.of(1, 2, 3, 4, 10, 9, 3, 3, 20, 21, 22).collect(percentile(0.25)));

Notice that jOOλ implements SQL’s percentile_disc semantics. Also, there are 3 “special” percentiles that deserve their own names:

A variety of overloads allows for calculating:

  • The percentile of the values contained in the stream
  • The percentile of the values contained in the stream, if sorted by another value mapped by a function
  • The percentile of the values mapped to another value by a function

Mode

Speaking of statistics. What about the mode? I.e. the value that appears the most often in a stream? Easy, with Agg.mode()

assertEquals(
    Optional.of(1), 
    Stream.of(1, 1, 1, 2, 3, 4).collect(Agg.mode()));
assertEquals(
    Optional.of(1), 
    Stream.of(1, 1, 2, 2, 3, 4).collect(Agg.mode()));
assertEquals(
    Optional.of(2), 
    Stream.of(1, 1, 2, 2, 2, 4).collect(Agg.mode()));

Other useful collectors

Other collectors that can be useful occasionally are:

Combine the aggregations

And one last important feature when working with jOOλ is the capability of combining aggregations, just like in SQL. Following the examples above, I can easily calculate several percentiles in one go:

// Unfortunately, Java's type inference might need
// a little help here
var percentiles =
Stream.of(1, 2, 3, 4, 10, 9, 3, 3).collect(
  Tuple.collectors(
    Agg.<Integer>percentile(0.0),
    Agg.<Integer>percentile(0.25),
    Agg.<Integer>percentile(0.5),
    Agg.<Integer>percentile(0.75),
    Agg.<Integer>percentile(1.0)
  )
);

System.out.println(percentiles);

The result being:

(Optional[1], Optional[2], Optional[3], Optional[4], Optional[10])

2 thoughts on “Lesser Known jOOλ Features: Useful Collectors

  1. Cool stuff, especially the Tuple.collectors.

    Does median work with a stream like (1, 1, 3, 3) ? In general, it can’t work, but with numbers (or anything having an average function), it can.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

This site uses Akismet to reduce spam. Learn how your comment data is processed.