A talk in JUG Hyderabad about Java 8 Streams

1. Java SE 8 :Streams
Streams Part 1
1. Overview of Streams
2. Standard Data Structures Into and Out of Streams
3. Core Stream Methods:
3.1 forEach(), map(), filter(), findFirst()
3.2 reduce(), collect(), min(), max(), sorted(), distinct(), limit(), skip(),
noneMatch(), allMatch(), anyMatch(), count()
4. Lazy Evaluation
5. Wrap Up
1Lars Lemos, MCA, OCPJP SE 6

2. Streams Overview
Stream Idea
 Streams are wrappers around data sources such as arrays or lists. They provide
many high performance operations that can be expressed with lambdas,
executed sequentially or in parallel.
Example: StreamSamples.java
 Note: Streams are not collections. This appear to be an interactive process for n elements over
each method operation. But due to Lazy evaluation there are less iterations performed over each
condition being met.
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Lars Lemos, MCA, OCPJP SE 6

3. Streams Overview
Stream Idea
 Streams are “Not data structures”, they have no storage. They carry values
from a source through a pipeline of operations.
 Streams are “Designed for Lambdas”, streams operations take lambdas as
arguments.
 Streams don’t have “Indexed access”, you can access the first element, but
not the second or third.
 Streams output “Arrays or Lists” easily with simple syntax.
 Streams are “Lazy”, the operations are postponed until it is known how much
data is eventually needed.
Example: A operation that takes 10 s/item on a 100 element Stream, selecting the 1st
element takes 10s not 10000s
 Streams are “Parallelizable”, once a stream is designated as parallel, then
operations will automatically be done in parallel without having to write
explicit multi-threading code.
 Streams can “Ubounded”, once a generator function is designated, clients
can consume entries as long as they want, with values being generated on the
fly.
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Lars Lemos, MCA, OCPJP SE 6

4. Streams Overview
Creating Stream
 It’s known that streams are not collections: they do not manage their own
data (wrappers around data structures).
 Thus a stream does not copy the underlying data, only builds a pipeline of
operations. And it can be invoked when desired.
Syntax:
• Individual values - Stream.of(val1, val2, …);
• Array - Stream.of(objectArray);
• Lists - someList.stream();
• StreamBuilder – someBuilder.build();
• String - Stream.of(somestring.split());
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Lars Lemos, MCA, OCPJP SE 6

5. Streams Overview
Stream from Primitives
– Alternatives
• int[] nums = { 1, 2, 3, 4 };
• Arrays.stream(nums)… // IntStream
• Integer[] nums = { 1, 2, 3, 4 };
• Arrays.stream(nums)… or Stream.of(nums)… // Stream<Integer>
• Making 1-item stream by accident
– Mistake
• int[] nums = { 1, 2, 3, 4 };
• Stream.of(nums)… // 1-item Stream containing array
– Correct
• Integer[] nums = { 1, 2, 3, 4 };
• Stream.of(nums)… // 4-item Stream containing Integers 5
Lars Lemos, MCA, OCPJP SE 6

6. Streams Overview
Streams to Pre-Java 8 Data Structures
 Array
– strm.toArray(EntryType[]::new)
Examples: employeeStream.toArray(Employee[]::new)
– The argument to toArray is normally EntryType[]::new, but in general is a
Supplier that takes an int (size) as an argument and returns an empty array that
can be filled in.
 List
– strm.collect(Collectors.toList())
• Common to do “import static java.util.stream.Collectors.*;”
then to do strm.collect(toList())
 Other collections
– strm.collect(Collectors.toSet()), – strm.collect(Collectors.groupingBy(…)),
etc.
 String
– strm.collect(Collectors.toStringJoiner(delim)).toString()
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Lars Lemos, MCA, OCPJP SE 6

7. Streams Overview
Core Streams Methods
 forEach(Consumer) : employees.forEach(e -> e.setSalary(e.getSalary() * 11/10))
Example: forEachExamples();
 map(Function) : ids.map(EmployeeUtils::findEmployeeById)
Example: mapExamples()
 filter(Predicate) : employees.filter(e -> e.getSalary() > 500000)
Example: filterExamples();
 findFirst() : employees.filter(…).findFirst().get()
Example: combinedExamples();
 collect(Collectors.toList()) : List<Employee> empList = employees.collect(Collectors.toList());
Example: lazyEvaluationExample();
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Lars Lemos, MCA, OCPJP SE 6

8. Streams Overview
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Lars Lemos, MCA, OCPJP SE 6
End of part II
Part III – JavaScript in JVM, Nashorn
…………
larslemos@gmail.com
Lars Lemos
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