Fp java8

1
Ready for
"Functional Programming"
with Java 8 ?
Yanai Franchi , Tikal

2
Agenda
● First-Class Functions
● FP with Streams
● Working Concurrency
● Demo

4
Our Inventory = List of Apples

5
Class Apple
● getColor() : String
● getWeight() : int

8
Filter Green Apples
public static List<Apple> filterGreenApples(List<Apple> inventory){
List<Apple> result = new ArrayList<>();
for (Apple apple: inventory){
if (apple.getColor().equals(“green”)) {
result.add(apple);
}
}
return result;
}
Starts empty,
add green apples
one by one
Select only green apples

10
Easy...We Copy&Paste :(
public static List<Apple> filterHeavyApples(List<Apple> inventory){
if (apple.getWeight() > 150) {
result.add(apple);
}
}
return result;
}
We only change
the predicate

11
What's the Difference ?
public static List<Apple> filterGreenApples
(List<Apple> inventory){
if (apple.getColor.equals(“green”)) {
result.add(apple);
}
}
return result;
}
public static List<Apple> filterHeavyApples
(List<Apple> inventory){
if (apple.getWeight() > 150) {
result.add(apple);
}
}
return result;
}

13
New Behavior
Behavior
Parameterization
Output
apple.getWeight > 150 apple.getColor.equals(“green”)
Heavy Apples Green Apples
static List<Apple> filterApples(
List<Apple> inventory, Predicate<Apple> p) {
if (p.test(apple)) {
result.add(apple);
}
}
return result;
}

14
In Practice, Our Client...Yuck :(
List<Apple> greenApples =
filterApples(inventory,new Predicate<Apple>() {
@Override
public boolean test(Apple a) {
return a.getColor().equals(“green”);
}
});
A lot of “noise”

16
Java8 Lambda to Rescue
filterApples(inventory,
(Apple a) → {return a.getColor().equals(“green”)});

17
Sending Lambda Expression
(Apple a) → a.getColor().equals(“green”));

18
Making it Shorter
(a) → a.getColor().equals(“green”));
Apple Type is
Inferred

19
...Even Shorter
a → a.getColor().equals(“green”));

20
“Capture” Values (a.k.a “Closure”)
String color = “green”;
a → a.getColor().equals(color));
Implicitly final

22
Anonymous Function that Can Be
Passed Around
a → a.equals.getColor(“green”));

23
Switch to Method Reference
filterApples(inventory,a → a.equals.getColor(“green”));

24
Switch to Method Reference
filterApples(inventory,Apple::isGreen);
filterApples(inventory,a → a.getColor().equals(“green”));
isGreen is
declared in Apple

27
Lambda Type = Functional Interface
Predicate<Apple> redApple = a → a.getColor().equals(“red”);
Predicate is the
type of our lambda

28
Meet Functional Interface
@FunctionalInterface
public interface Predicate<T>{
boolean test(T t);
}
Just Marker
● Definition: a
functional interface is
an interface with one
abstract method
● Single Abstract
Method (SAM) type
SAM

29
Default Methods
Implementations in Interface
@FunctionalInterface
public interface Predicate<T>{
boolean test(T t);
default Predicate<T> negate(){
return (t) -> !test(t);
}
default or(Predicate<? super T> other){
return (t) -> test(t) ||
other.test(t);
}
default and(Predicate<? super T> other){
return (t) -> test(t) &&
other.test(t);
}
}
Default Method

30
Existing Function Interfaces
interface Comparator<T> { boolean compare(T x, T y); }
(int x, int y) → x - y ;
interface FileFilter { boolean accept(File x); }
f → f.isDirectory()
interface Runnable { void run(); }
() → someCode();
interface ActionListener{ void actionPerformed(ActionEvent ae); }
(ae -> log.debug(“Got it!”));

31
New Function Interfaces
● Predicate<T> : boolean test(T t);
– Determine if the input of type T matches some criteria :
● Consumer<T> : void accept(T t);
– Accept a single input argument of type T, and return no
result :
● Supplier<T> : T get();
– A factory that’s expected to return either a new instance
or a pre-created instance :
● Function<T, R> : R apply(T t);
– Apply a function to the input type T, generating a result
of type R

33
Sorting with Anonymous Class
inventory.sort(new Comparator<Apple>() {
public int compare(Apple a1, Apple a2){
return a1.getWeight().compareTo(a2.getWeight());
}
});
High Order
Function

34
Sort with Lambda
inventory.sort(
(a1,a2) → a1.getWeight().compareTo(a2.getWeight())
);

35
Using “comparing” Method
Comparator Interface
Static method
inventory.sort(comparing(Apple::getWeight));
Static method that accept
Function and return Comparator

37
Dish
Row 1 Row 2 Row 3 Row 4
0
2
4
6
8
10
12
Column 1
Column 2
Column 3
● String getName()
● boolean isVegeterian()
● int getCalories()
● Type getType()
● List<String> getNickNames()
● CaloricLevel getCaloricLevel()

38
Three Fat Dishes - Imperative
● Client controls iteration
● Inherently serial: iterate
from beginning to end
● Not thread-safe because
business logic is stateful
(mutable accumulator
variable)
● Frustratingly imperative
List<String> fatsDishes = ...
int count = 0;
for(Dish d : menu){
if (count > 3)
break;
if(d.getCalories > 300){
count++;
fatsDishes.add(d.getName());
}
}
External
Iteration

40
FP → Declarative Code
List<String> fatDishes =
menu.stream()
.filter(d -> d.getCalories() > 300)
.map(Dish::getName)
.limit(3)
.collect(toList());

42
But What is a Stream ?
● A sequence of elements from a source that
supports aggregate operations
– Aimed for computations and aggregations (In
contrary to collections which are data structures)
– Consume from a data-providing source such as
Collections, Arrays, or IO resources.
– Support SQL-like operations and common
operations from functional programing languages
such as filter, map, reduce, find, match, sorted etc.

43
Creating Stream
● IntStream.range(1, 100)
● Stream.of("Java 8 ", "Lambdas");
● File.list(Paths.get("some-folder"))
● Files.lines(Paths.get("data.txt"))
● myList.parallelStream()
● Create infinite stream
– Iterate
● Stream.iterate(0, n -> n + 2)
● Stream.iterate(new int[]{0, 1}, t -> new int[]{t[1], t[0]+t[1]})
– Stream.generate(Math::random)

44
High Order Function - map
● <R> Stream<R>
map(Function<? super T, ? extends R> mapper);
● Apply the mapper function on each element of
the stream , and create a new stream from its
outputs by placing the results of the mapper on
the new stream
● map(Dish::getName). Converts a Stream of
dishes to Stream names (Strings), by applying
Dish.getName() on the elements.

45
High Order Function - flatMap
●
<R> Stream<R>
flatMap(Function<? super T, ? extends Stream<? extends R>> mapper);
● Apply the mapper function on each element of
the stream and create a new stream from its
outputs, by placing contents of the mapped
streams in the new stream
● menu.stream().flatMap(d → d.getNickNames().stream())
– Converts a Stream of dishes to Stream of
nickNames (String), by replacing all nicknames as
elements of the stream.

46
Limit - “Short Circuit”
List<String> names = menu.stream()
.filter(d -> {System.out.println("filtering" + d);
return d.getCalories() > 300;})
.map(d -> {System.out.println("mapping" + d);
return d.getName();})
.limit(3)
.collect(toList());
filtering pork
mapping pork
filtering beef
filtering chicken
mapping chicken
filtering egg
filtering spaghetti
mapping spaghetti
Short Circuit:
Stopped printing
after 3 dishes

47
Finding & Matching - “Short Circuit”
● No need to process the whole stream
● As soon as an element is found a result can be
produced.
● Finding Operations:
– anyMatch, noneMatch, findFirst and findAny
boolean found =
menu.stream().anyMatch(Dish::isVegatarian)

48
Group Dishes by Type - Imperative
Map<Dish.Type, List<Dish>> groupDishesByTypeMap =
new HashMap<>();
for (Dish dish : menu) {
final Type type = dish.getType();
List<Dish> dishesForType = groupDishesByTypeMap.get(type);
if(dishesForType == null){
dishesForType = new ArrayList<>();
groupDishesByTypeMap.put(type, dishesForType);
}
dishesForType.add(dish);
}
return groupDishesByTypeMap;

49
Grouping with FP - Declarative
Map<Dish.Type, List<Dish>> groupDishesByTypeMap =
menu.stream().collect(groupingBy(Dish::getType));
Collectors static method

50
Count Dishes Per Type
Map<Dish.Type, Long> typesCount =
menu.stream().collect(
groupingBy(Dish::getType,counting()));
{MEAT=3, FISH=2, OTHER=4}
Output
Collectors static method

52
One More Level...
Map<Dish.Type, Map<CaloricLevel, List<Dish>>>
groupDishesByTypeAndCaloricLevel =
menu.stream()
.collect(groupingBy(
Dish::getType,
groupingBy(Dish::getCaloricLevel)));
{
MEAT={DIET=[chicken], NORMAL=[beef], FAT=[pork]},
FISH={DIET=[prawns], NORMAL=[salmon]},
OTHER={DIET=[rice, seasonal fruit], NORMAL=[french fries, pizza]}
}
Output

54
Process Dishes in Parallel
● Uses the ForkJoin framework behind the scenes
● By Default number of threads is as the number of
processors
● Will NOT keep the original order of the stream
menu.parallelStream().forEach(Dish::heavyCalculation);

55
Total Calories in Menu – Imperative
int i=0;
i += dish.getCalories();
}
Side Effect

56
We Know What To Do...
● The only difference is the reduction function
● For min, max, avg etc – The code will look the
same
int i=0;
i += dish.getCalories();
}
int i=0;
i = Math.max(dish.getCalories(),i);
}

57
Move To FP – Bad Way :(
Accumulator accumulator = new Accumulator();
menu.stream()
.map(Dish::getCalories)
.forEach(accumulator::add);
accumulator.getTotal();
class Accumulator {
private long total = 0;
long getTotal(){return total);
public void add(long value) {
total += value;
}
} Side Effect

58
Break Concurrency!!! :(
Accumulator accumulator = new Accumulator();
menu.parallelStream()
.forEach(accumulator::add)
accumulator.getTotal();
Different result
For the same input

59
Reducing
Row 1 Row 2 Row 3 Row 4
0
2
4
6
8
10
12
Column 1
Column 2
Column 3
.sum();
.reduce(0,Integer:sum);
=

60
FP - Data is Immutable
● Once object is created, it can't be changed.
● If you need to change an object, make a copy.
– Enables concurrency
– Rollback of data
– Simplicity

61
Mutable Tree – What's Wrong ?
class Tree {
private String key;
private int val;
private Tree left, right;
public Tree(String k, int v, Tree l, Tree r) {
key = k; val = v; left = l; right = r;
}
}
public static Tree update(String k, int newval, Tree t) {
if (t == null)
t = new Tree(k, newval, null, null);
else if (k.equals(t.key))
t.val = newval;
else if (k.compareTo(t.key) < 0)
t.left = update(k, newval, t.left);
else
t.right = update(k, newval, t.right);
return t;
}

62
Concurrency Problems
● Every user wants to share the identical data
structure and see updates caused by any part
of the program.
● Hence it is vital (but often overlooked) in
nonfunctional code that whenever we add some
form of structured value to a tree then we copy
it - Who knows, someone may later assume
they can update it.
● In Functional approach – Share storage for
common parts of structure.

63
Marry
22
Emily
20 Titan
29
Alan
50
Georgie
23
Raoul
25
Persistent Tree

64
Marry
22
Emily
20 Titan
29
Alan
50
Georgie
23
Raoul
25
Input : “will”, 26
Persistent Tree

65
Marry
22
Emily
20 Titan
29
Alan
50
Georgie
23
Raoul
25
Marry
22
Titan
29
Will
26
Output of updateInput : “will”, 26
Persistent Tree

66
Persistent Tree
class Tree {
private String key;
private int val;
private Tree left, right;
public Tree(String k, int v, Tree l, Tree r) {
key = k; val = v; left = l; right = r;
}
}
public static Tree fupdate(String k, int newval, Tree t) {
return (t == null) ?
new Tree(k, newval, null, null) :
k.equals(t.key) ?
new Tree(k, newval, t.left, t.right) :
k.compareTo(t.key) < 0 ?
new Tree(t.key, t.val, fupdate(k,newval, t.left), t.right) :
new Tree(t.key, t.val, t.left, fupdate(k,newval, t.right));
}

67
Analyze Multiple Apache Logs

68
Analyze Multiple Apache Logs
● Host, Time, Request, Response, Resp-Length
199.72.81.55 - - [02/Jul/1995:00:00:01 -0400] "GET /history/apollo/ HTTP/1.0" 200 6245
unicomp6.unicomp.net - - [02/Jul/1995:00:00:06 -0400] "GET /shuttle/countdown/ HTTP/1.0" 200 3985
199.120.110.21 - - [01/Jul/1995:00:00:09 -0400] "GET /shuttle/missions/sts-73/mission-sts-73.html HTTP/1.0" 200 4085
burger.letters.com - - [01/Jul/1995:00:00:11 -0400] "GET /shuttle/countdown/liftoff.html HTTP/1.0" 304 0
199.120.110.21 - - [01/Jul/1995:00:00:11 -0400] "GET /shuttle/missions/sts-73/sts-73-patch-small.gif HTTP/1.0" 200 4179
burger.letters.com - - [01/Jul/1995:00:00:12 -0400] "GET /images/NASA-logosmall.gif HTTP/1.0" 304 0
burger.letters.com - - [01/Jul/1995:00:00:12 -0400] "GET /shuttle/countdown/video/livevideo.gif HTTP/1.0" 200 0
205.212.115.106 - - [01/Jul/1995:00:00:12 -0400] "GET /shuttle/countdown/countdown.html HTTP/1.0" 200 3985
d104.aa.net - - [01/Jul/1995:00:00:13 -0400] "GET /shuttle/countdown/ HTTP/1.0" 200 3985
129.94.144.152 - - [01/Jul/1995:00:00:13 -0400] "GET / HTTP/1.0" 200 7074
unicomp6.unicomp.net - - [01/Jul/1995:00:00:14 -0400] "GET /shuttle/countdown/count.gif HTTP/1.0" 200 40310
unicomp6.unicomp.net - - [01/Jul/1995:00:00:14 -0400] "GET /images/NASA-logosmall.gif HTTP/1.0" 200 786
unicomp6.unicomp.net - - [01/Jul/1995:00:00:14 -0400] "GET /images/KSC-logosmall.gif HTTP/1.0" 200 1204
d104.aa.net - - [01/Jul/1995:00:00:15 -0400] "GET /shuttle/countdown/count.gif HTTP/1.0" 200 40310
d104.aa.net - - [01/Jul/1995:00:00:15 -0400] "GET /images/NASA-logosmall.gif HTTP/1.0" 200 786
d104.aa.net - - [01/Jul/1995:00:00:15 -0400] "GET /images/KSC-logosmall.gif HTTP/1.0" 200 1204
129.94.144.152 - - [01/Jul/1995:00:00:17 -0400] "GET /images/ksclogo-medium.gif HTTP/1.0" 304 0
199.120.110.21 - - [01/Jul/1995:00:00:17 -0400] "GET /images/launch-logo.gif HTTP/1.0" 200 1713
ppptky391.asahi-net.or.jp - - [01/Jul/1995:00:00:18 -0400] "GET /facts/about_ksc.html HTTP/1.0" 200 3977
ppptky391.asahi-net.or.jp - - [01/Jul/1995:00:00:19 -0400] "GET /images/launchpalms-small.gif HTTP/1.0" 200 11473
205.189.154.54 - - [01/Jul/1995:00:00:24 -0400] "GET /shuttle/countdown/ HTTP/1.0" 200 3985
…
...
129.94.144.152 - - [01/Jul/1995:00:00:13 -0400] "GET / HTTP/1.0" 200 7074
…
...
129.94.144.152 - - [01/Jul/1995:00:00:13 -0400] "GET / HTTP/1.0" 200 7074
…
...

69
Requirements
● Answer the following:
– Are there any errors ?
– Are there any empty-body responses ?
– Find last 5 error
– Count statuses for each day
● Assumptions
– Analyze multiple logs in “logs” folder
– Logs files are big and can't fit into memory

70
Design
● LogEntry - Entity Class
– parse(String line) : LogEntry
● LogAnalyticService – Service Class
– streamLogs() : Stream<LogEntry>
● Stream log files in folder
● Per Each file Stream lines
● Map each line to LogEntry
● anyMatch – Reuse for different predicates
● groupBy – For grouping

71
Implementation
private Stream<LogEntry> streamLogs() {
try {
return
Files.list(Paths.get(loggingDir))
.filter(p -> p.getFileName().endsWith(LOG_EXT))
.flatMap(Files::lines)
.map(LogEntry::parse);
} catch (final Exception e) {
throw new RuntimeException(e);
}
}
Will not Compile

72
private Stream<LogEntry> streamLogs() {
try {
return
Files.list(Paths.get(loggingDir))
.filter(p -> p.getFileName().endsWith(LOG_EXT))
.flatMap(this::lines)
.map(LogEntry::parse);
} catch (final Exception e) {
throw new RuntimeException(e);
}
}
private Stream<String> lines(final Path path) {
try {
return Files.lines(path);
} catch (IOException e) {
logger.error("Failed to process "+path,e);
return Stream.empty();
}
}

73
Last Err Logs
return streamLogs()
.filter((le) -> le.getResponse() >= 500)
.sorted(comparing(LogEntry::getDateTime).reversed())
.limit(5)
.collect(toList());

74
Sending Predicates
public boolean isAnyWithResponse(int response) {
return anyMatch((le) -> le.getResponse() == response);
}
public boolean isAnyEmptyResponse() {
return anyMatch((le) -> le.getByteSent() == 0);
}
boolean anyMatch(Predicate<? super LogEntry> predicate) {
return streamLogs().anyMatch(predicate);
}

75
Grouping Results
Map<LocalDate, Map<Integer, Long>> groupingByDatesThenResponse() {
return
streamLogs()
.collect(groupingBy(
LogEntry::getDate,
TreeMap::new,
groupingBy(LogEntry::getResponse, counting()))
);
}
Ordered Keys
Nested Grouping

77
FP Summary
● Functions are first-class citizens
– Can be declared as variables, pass as arguments
or be returned by other functions
● Declarative instead of imperative
– We tell what to do, instead of how
● Data Immutability
– Reduce Side Effect
– Easier path to parallel code
● Java 8 Lambda & Streams enable FP style

Fp java8

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