This article discusses their difference and helps you understand which is the best choice for you depending on the situation. Let’s see how we can code the execution of these two parallel threads as a continuation of the previous one: We create (using supplyAsync) a CompletableFuture that gets the safety box number and then combine it with the CompletableFuture that brings the result of the previous chain (thenCombineAsync). Aggregate operations iterate over and process these substreams in parallel and then combine the results. When a stream executes in parallel, the Java runtime partitions the stream into multiple substreams. They look quite similar and it’s easy to get lost when you are not familiar with the API. parallel foreach() Works on multithreading concept: The only difference between stream().forEacch() and parrllel foreach() is the multithreading feature given in the parllel forEach().This is way more faster that foreach() and stream.forEach().Like stream().forEach() it also uses lambda symbol to perform functions. The static factory methods in this class are the starting points for executing tasks. Sequential stream’s objects are pipelined in a single stream on the same processing system hence it never takes the advantage of the multi-core system even though the underlying system supports parallel execution. CompletableFuture provides three methods to handle them: handle(), whenComplete(), and exceptionally(). CompletableFuture has an advantage over parallel streams that we can define our own Executor with the size of thread pool which better suites the need of our application. For normal stream, it takes 27-29 seconds. CompletableFuture implements CompletionStage and Future. Currently, JDK IO-based Stream sources (for example BufferedReader.lines()) are mainly geared for sequential use, processing elements one-by-one as they arrive. For parallel stream, it takes 7-8 seconds. This clearly shows that in sequential stream, each iteration waits for currently running one to finish, whereas, in parallel stream, eight threads are spawn simultaneously, remaining two, wait for others. This Java code will generate 10,000 random employees and save into 10,000 files, each employee save into a file. In parallel stream, Fork and Join framework is used in the background to create multiple threads. Java 8 brought us tools like CompletableFuture and Stream API… let’s try to combine them both and create a Stream that returns values from a collection of CompletableFutures as they arrive. Also notice the name of threads. This approach was also employed when developing 1.0.0 of parallel-collectors. CompletableFuture class. In these cases, parallel streams are not usually a good choice, but good alternatives are available, for example async-IO and CompletableFuture designs. The tasks which return a result. Streaming CompletableFutures Any stream operation without explicitly specified as parallel is treated as a sequential stream. This approach was used when developing 1.0.0 of parallel-collectors. Streaming CompletableFutures. The example providing its multithreading nature which is given as follows. On basic level, the tasks started by CompletableFuture can be divided in two categories: The tasks which do not return any result. Specifically for our task execution application, if there are 50 tasks we can have better performance, with the following Executor : What if my source is based on IO? When you create a stream, it is always a serial stream unless otherwise specified. 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