When to Use a Parallel Stream in Java

When to Use a Parallel Stream in Java

Java Streams are a powerful tool used to process data in an efficient and organized manner. Streams allow developers to “walk through” sets of data, performing operations on each element as it passes through the stream. With Java 8, streams can now be used in parallel, allowing developers to process data more quickly than ever before.

Parallel streams can be incredibly useful for certain applications, however it is important to understand when and how to use them. Generally, parallel streams should be used when a large amount of data needs to be processed very quickly.

Parallel streams are best used when there are multiple cores available and the operations being performed on the data set can be broken down into independent pieces. This allows multiple processes to run at the same time in order to speed up the overall process.

It is important to keep in mind that parallel streams may be slower than non-parallel ones if the dataset is too small or the operations are too simple, as the overhead time needed to create multiple processes outweighs the benefit gained from their use.

In addition, parallel streams require more memory due to the need to duplicate the data in order to run the different processes. This makes them impractical for use with large datasets, as the extra memory usage can become a bottleneck.

Finally, it is important to remember that not all operations can be performed in parallel. Operations that modify shared state cannot be used with a parallel stream, as there is no guarantee that all the processes will be in sync with each other.

In summary, parallel streams can be a great way to speed up processing of large datasets. However, they should only be used when the dataset is large enough and the operations complex enough to warrant their use. And, of course, pay attention to operations that are unable to be done in parallel, as these will slow down your code significantly.