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Practice on Java Streams

Streams Vs Loop

Both Java streams and loops can iterate over collections of data, but they vary significantly in terms of how they operate and what they can provide.

Imperative loops, like the for loop, demand that you define the steps to iterate over a set of data. This implies that you are responsible for overseeing each iteration, including managing edge cases, indexing, and other issues. While loops can be useful for small data sets, they can quickly become verbose and challenging to read and comprehend for larger databases.

Java Streams, on the other hand, provide a declarative and functional method for handling data collection. With just a small amount of boilerplate code, you can perform complicated transformations and computations on collections of data using the high-level operations provided by streams, such as map(), filter(), reduce(), and others. As a result, it is simpler to create code that is clear and expressive and is also simpler to read and comprehend.

The ability to use parallel processing, which can greatly boost performance on large datasets, is another benefit of streams. You can take advantage of contemporary multi-core CPUs and accelerate the speed of your code by using parallel streams, which can automatically partition and spread the data across multiple threads.

Java Streams is a feature that was added to Java 8 and gives users a way to handle collections of data in a declarative and functional manner. You can use it to create code that is clear, expressive, and simple to comprehend.

A stream is a collection of components that can be handled sequentially or in parallel. Various types of data, including lists, arrays, sets, maps, and even I/O channels, can be used to make streams.

Data transformation, filtering, and sorting are all possible with the help of the intermediate processes that streams offer. Due to their laziness, these operations wait until a terminal operation is called before performing anything. Filter(), map(), flatMap(), distinct(), sorted(), and limit are a few of the frequently used intermediate procedures.().

Terminal operations are operations that consume the stream and produce a result or a side-effect. Some of the common terminal operations are forEach(), count(), collect(), reduce(), and min()/max(). These operations are eager and trigger the processing of the stream.

Streams also provide support for parallel processing, which can significantly improve performance on large datasets. Parallel streams are created by simply invoking the parallel() method on a stream.

Overall, Java Streams provide a powerful and flexible way to process collections of data in a concise and expressive manner.

Java Streams provide a rich set of methods for performing various operations on collections of data. Here are some of the most commonly used methods:

These methods can be combined to perform complex operations on collections of data in a concise and expressive manner.

ER Diagram

Setting up above Entities

Order Class

Product Class

Customer Class

To Perform stream operation create a new Class OrderApplication and setup the values of Entities.

OrderApplication Class

2. Obtain a list of product with category = “Toys” and then apply 10% discount

3. Get the cheapest product of “Books” category

4. Obtain a list of order with products belong to category “Books”

5. Get a list of orders which were ordered on 20-Feb-2023, log the order records to the console and then return its product list

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