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Spring Boot 4 Complete Guide · Lesson

Pagination, Sorting, and Slice Streaming

Return paged, sorted, and streamed result sets efficiently for large datasets and infinite scroll UIs.

Pagination, Sorting, and Slice Streaming is a free Spring Boot 4 Complete Guide lesson on CoddyKit — lesson 4 of 4. You can read the complete lesson below for free — then practise it hands-on in the browser with a built-in code editor and a 24/7 AI tutor. It is part of the Spring Boot 4 Complete Guide learning path, one of 4 lessons in the course, and your progress syncs across the web and the CoddyKit app.

Why Pagination Matters

Loading an entire table into memory is one of the fastest ways to crash a service. A findAll() on a million-row table builds a giant list, exhausts the heap, and blocks the request thread.

Pagination solves this by fetching results in small chunks (pages). Spring Data JPA gives you first-class support through the Pageable abstraction.

  • Page — knows the total element count and total page count.
  • Slice — only knows whether a next chunk exists (cheaper).
  • Stream — processes rows one-by-one without materializing a list.

In this lesson you will learn when to reach for each one.

The Pageable Parameter

Add a Pageable parameter to any repository method and Spring Data appends LIMIT and OFFSET (or the dialect equivalent) to the generated query automatically.

The method returns a Page<T>, which wraps the content list plus paging metadata.

public interface ProductRepository extends JpaRepository<Product, Long> {

    Page<Product> findByCategory(String category, Pageable pageable);
}

Building a PageRequest

The concrete implementation of Pageable is PageRequest. You create one with a zero-based page number and a page size.

  • PageRequest.of(0, 20) — first page, 20 items.
  • PageRequest.of(2, 20) — third page (rows 40-59).

In a controller you usually let Spring resolve it from the request automatically, but you can also build it by hand in a service.

@Service
public class ProductService {

    private final ProductRepository repository;

    public ProductService(ProductRepository repository) {
        this.repository = repository;
    }

    public Page<Product> firstPage(String category) {
        Pageable pageable = PageRequest.of(0, 20);
        return repository.findByCategory(category, pageable);
    }
}

Reading Page Metadata

A Page<T> exposes everything a UI needs to render pagination controls.

  • getContent() — the rows on this page.
  • getTotalElements() — total matching rows in the table.
  • getTotalPages() — total number of pages.
  • getNumber() — current zero-based page index.
  • hasNext() / hasPrevious() — navigation flags.

Important: computing getTotalElements() requires an extra COUNT(*) query on every call.

Page<Product> page = repository.findByCategory("books", PageRequest.of(0, 20));

List<Product> rows = page.getContent();
long total = page.getTotalElements();
int totalPages = page.getTotalPages();
boolean more = page.hasNext();

Sorting with Sort

Sorting is part of Pageable. Pass a Sort object into PageRequest.of(page, size, sort) and Spring Data adds an ORDER BY clause.

  • Sort.by("price") — ascending by price.
  • Sort.by("price").descending() — descending.
  • Chain multiple orders for tie-breaking.
Sort sort = Sort.by("price").descending()
                .and(Sort.by("name").ascending());

Pageable pageable = PageRequest.of(0, 20, sort);
Page<Product> page = repository.findByCategory("books", pageable);

Multi-Field Sort with Order

For finer control over null handling and direction per field, build the Sort from Sort.Order objects.

This is the clearest way to express something like "newest first, then alphabetical, nulls last".

Sort sort = Sort.by(
    Sort.Order.desc("createdAt"),
    Sort.Order.asc("name").nullsLast()
);

Pageable pageable = PageRequest.of(0, 25, sort);
Page<Product> page = repository.findAll(pageable);

Slice vs Page

A Page always runs an extra COUNT(*) to know the total. For an infinite-scroll UI you rarely need the total — you only need to know if there is a next chunk.

Return Slice<T> instead. Spring fetches size + 1 rows internally: if the extra row exists, hasNext() is true. No count query runs, so it is noticeably cheaper on large tables.

  • Slice.getContent() and Slice.hasNext() work just like Page.
  • Slice.getTotalElements() does not exist.
public interface FeedRepository extends JpaRepository<Post, Long> {

    Slice<Post> findByAuthorId(Long authorId, Pageable pageable);
}

Consuming a Slice for Infinite Scroll

On the client you keep incrementing the page number while hasNext() stays true. The service stays clean because the repository handles the size + 1 trick.

public Slice<Post> nextChunk(Long authorId, int pageNumber) {
    Pageable pageable = PageRequest.of(
        pageNumber, 15, Sort.by("createdAt").descending());

    Slice<Post> slice = feedRepository.findByAuthorId(authorId, pageable);

    if (slice.hasNext()) {
        // tell the UI to request pageNumber + 1
    }
    return slice;
}

The Offset Problem

Offset pagination has a hidden cost: to return page 10000 with size 20, the database must scan and discard 200000 rows before returning yours. Deep pages get slower and slower.

Keyset (cursor) pagination avoids this. Instead of OFFSET, you filter on the last seen value. The query stays fast at any depth because it can use an index seek.

public interface PostRepository extends JpaRepository<Post, Long> {

    @Query("SELECT p FROM Post p WHERE p.id < :lastId ORDER BY p.id DESC")
    Slice<Post> findOlderThan(@Param("lastId") Long lastId, Pageable pageable);
}

Streaming Large Result Sets

When you must process every row (export, batch job, report) but cannot hold them all in memory, return a Stream<T>. JPA reads rows lazily from a forward-only cursor.

Two rules are non-negotiable:

  • The method must run inside a transaction (@Transactional) so the cursor stays open.
  • You must close the stream — use try-with-resources — to release the DB cursor.
public interface OrderRepository extends JpaRepository<Order, Long> {

    @QueryHints(@QueryHint(name = HINT_FETCH_SIZE, value = "100"))
    @Query("SELECT o FROM Order o WHERE o.status = :status")
    Stream<Order> streamByStatus(@Param("status") String status);
}

Draining a Stream Safely

Wrap the stream in try-with-resources and keep the whole consumption inside one transactional method. Detach or clear entities periodically if you mutate them, so the persistence context does not grow unbounded.

@Service
public class OrderExporter {

    private final OrderRepository repository;

    public OrderExporter(OrderRepository repository) {
        this.repository = repository;
    }

    @Transactional(readOnly = true)
    public long exportPending(Consumer<Order> writer) {
        long count = 0;
        try (Stream<Order> stream = repository.streamByStatus("PENDING")) {
            for (Order order : (Iterable<Order>) stream::iterator) {
                writer.accept(order);
                count++;
            }
        }
        return count;
    }
}

Quick Check: Choosing the Right Return Type

You are building an infinite-scroll feed over a 5-million-row table. The UI never shows a total count, only a "load more" button. Which repository return type is the best fit?

Recap

You now have a toolbox for handling large result sets in Spring Data JPA:

  • Page<T> — content plus total counts; pays for a COUNT(*) query. Use when the UI shows total pages.
  • Slice<T> — content plus hasNext(); no count query. Best for infinite scroll.
  • Sort — combine with PageRequest.of(page, size, sort) for ordered, deterministic pages.
  • Keyset pagination — filter on the last seen value to keep deep pages fast.
  • Stream<T> — lazy, forward-only processing inside @Transactional with try-with-resources for huge batch jobs.

Match the return type to the access pattern, and your queries stay fast and memory-safe at any scale.

Frequently asked questions

Is the “Pagination, Sorting, and Slice Streaming” lesson free?

Yes — the full text of “Pagination, Sorting, and Slice Streaming” is free to read here on the web, and the Spring Boot 4 Complete Guide course includes 4 lessons in total. To practise it interactively (a built-in code editor and a 24/7 AI tutor) and unlock the rest of the Spring Boot 4 Complete Guide course, upgrade to CoddyKit PRO.

What will I learn in “Pagination, Sorting, and Slice Streaming”?

Return paged, sorted, and streamed result sets efficiently for large datasets and infinite scroll UIs. You practise Spring Boot 4 Complete Guide with hands-on code you run directly in the browser, and a 24/7 AI tutor answers your questions as you work through the lesson.

Do I need any experience to start Spring Boot 4 Complete Guide?

No prior experience is required. Spring Boot 4 Complete Guide on CoddyKit is structured for beginners through advanced learners; this is — lesson 4 of 4, so you can start here or from the beginning and move at your own pace.

How long does the “Pagination, Sorting, and Slice Streaming” lesson take?

Most CoddyKit lessons take about 5–10 minutes. Each one is bite-sized and interactive, so you make steady progress and pick up exactly where you left off across the web and the app.

Can I write and run code in this Spring Boot 4 Complete Guide lesson?

Yes. Every Spring Boot 4 Complete Guide lesson includes a built-in code editor, so you write and run real code right in your browser and get instant AI feedback — no local setup required.

All lessons in this course

  1. Derived Query Methods and Keyword Resolution
  2. JPQL and Native Queries with @Query
  3. Specifications and Criteria-Based Dynamic Filtering
  4. Pagination, Sorting, and Slice Streaming
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