Copy a stream to avoid "stream has already been operated upon or closed" – Java

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Written By M Ibrahim
aws-lambda azure-java-sdk java-8 java-stream

Quick Fix: The question is about efficiency of iterating over a stream. The answer suggest using a Consumer and ConsumerB to operate over the same data repeatedly. Other solution include structuring operations as consumers and storing or buffering data.

The Problem:

Craft a method to duplicate a Java 8 stream such that it can be operated upon more than once without encountering the "stream has already been operated upon or closed" error. Avoid converting the stream into a collection as an intermediate step, such as using collect(Collectors.toList()).

The Solutions:

Solution 2: Using a local variable with a `Supplier`

You can use a local variable with a `Supplier` to set up common parts of the stream pipeline. This allows you to reuse the stream multiple times without having to recreate it each time.

Here’s an example:

“`java
Supplier> streamSupplier = () -> Stream.of(“d2”, “a2”, “b1”, “b3”, “c”)
.filter(s -> s.startsWith(“a”));

streamSupplier.get().anyMatch(s -> true); // ok
streamSupplier.get().noneMatch(s -> true); // ok

<p>
Each call to `get()` constructs a new stream on which you can call the desired terminal operation. This ensures that you won't get the `java.lang.IllegalStateException: stream has already been operated upon or closed` error.
</p>
<p>
This approach is especially useful when you have a long and complex stream pipeline that you need to reuse multiple times.
</p>

Solution 3: Use a `Supplier` to produce the stream for each termination operation

Use a Supplier to produce the stream for each termination operation.

Supplier&lt;Stream&lt;Integer&gt;&gt; streamSupplier = () -&gt; list.stream();

Whenever you need a stream of that collection, use streamSupplier.get() to get a new stream.

Examples:

  1. streamSupplier.get().anyMatch(predicate);

  2. streamSupplier.get().allMatch(predicate2);

Solution 4: jOOL duplicate() method

The jOOL library provides a duplicate() method for streams, which creates two streams that share the same underlying data. This allows you to process the same data in different ways, without having to create a collection as an intermediate step.

Internally, the duplicate() method uses a buffer to store the elements that have been consumed from one stream but not from the other. This buffer is then used to provide the elements for the second stream.

The duplicate() method is efficient if the two streams are consumed at about the same rate. However, it is not thread-safe, so it should not be used in a multithreaded environment.

Here is an example of how to use the duplicate() method:

Tuple2<Seq<A>, Seq<A>> duplicates = Seq.seq(doSomething()).duplicate();

duplicates.v1().forEach(a -> ...);
duplicates.v2().forEach(a -> ...);

In this example, the doSomething() method returns a stream of elements of type A. The duplicate() method is then used to create two streams from this stream. The v1() and v2() methods of the Tuple2 object return the two streams.

The forEach() method is then used to process the elements of each stream.

Solution 5: Run Stream Operations On Temporary Objects

You can create a stream of runnable objects for two operations, one for the failure case and one for the success case. This allows you to apply both operations to each element in the stream. Here’s an example:

results.stream()
    .flatMap(either -> Stream.of(
            () -> failure(either.left()),
            () -> success(either.right())))
    .forEach(Runnable::run);

In this example, `failure` and `success` are the operations you want to apply to the left and right projections of the `Either` objects, respectively. The `flatMap` operation creates a stream of runnable objects for each `Either` object, and the `forEach` operation executes each runnable object.

Note that this approach may not be more efficient than starting from a collection and streaming/iterating it twice. It creates a lot of temporary objects, which can add overhead. If efficiency is a concern, you may want to consider using the `toList()` approach instead.