When you want to process the data concurrently across multiple process, what will you do???
Java 8 offers you a concept…
That is “Parallel Streams”.
The common usage of parallel Streams is listed below.
Batch Processing: Reading sensor inputs and log files
can be done. These can be concurrently
processed
across multiple places.
Data Processing: It deals with large amount of data.
It collects large amount of data, process it by
streams.
Data Analysis:
This process Analyse the data collected.
Image and video processing: Image and video is
processed according to the standard format. It deals
with image filteration, video layout editing and so on.
Sorting, Searching and aggregation: These are
operations on data. It deals with arranging the data in
specified format for sorting. Searching is a process of finding an element. Aggregation deals with combining data together.
Machine learning: This deals with large sets of data
involving machine learning algorithms.
Real time data processing: Real time data is
processed concurrently.
How to create a Parallel Streams:
As
we know earlier, parallel streams are executed the process parallelly. So, it
uses stream to execute this.
- Here, there are three built in packages are used.
- Arrays, List and Stream collectors. There are the sub packages from java.util package.
- Create a class “StreamEg2” and save this file as “StreamEg2.java”.
- Inside the main function, create a list as Array
- Next, call Parallel Stream function and using ForEach method, print the value.
#Java Program to create Parallel streams
import java.util.Arrays;
import java.util.List;
import java.util.stream.Collectors;
public class
StreamEg2 {
public static
void main(String[] args) {
List<Integer> list = Arrays.asList(1, 2, 3, 4);
list.parallelStream().forEach(System.out::println);
}
}
Executing this, you will get the below output.
These are the ways of using ParallelStreams. These are useful in realtime applications and large data manipulation applications.
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