Quick overview

How the server splits large result sets into multiple network responses.

  • in the configuration.
  • transparent in the synchronous API (session.execute): the driver fetches new pages in the background as you iterate.
  • explicit in the asynchronous API (session.executeAsync): AsyncResultSet.hasMorePages() and AsyncResultSet.fetchNextPage().
  • paging state: record the current position and reuse it later (forward only).
  • offset queries: emulated client-side with OffsetPager (this comes with important performance trade-offs, make sure you read and understand the full documentation below).

When a query returns many rows, it would be inefficient to return them as a single response message. Instead, the driver breaks the results into pages which get returned as they are needed.

Setting the page size

The page size specifies how many rows the server will return in each network frame. You can set it in the configuration: = 5000

It can be changed at runtime (the new value will be used for requests issued after the change). If you have categories of queries that require different page sizes, use configuration profiles.

Note that the page size is merely a hint; the server will not always return the exact number of rows, it might decide to return slightly more or less.

Synchronous paging

The fetch size limits the number of results that are returned in one page; if you iterate past that, the driver uses background queries to fetch subsequent pages. Here’s an example with a fetch size of 20:

ResultSet rs = session.execute("SELECT * FROM my_table WHERE k = 1");
for (Row row : rs) {
  // process the row
Text Diagram

Asynchronous paging

In previous versions of the driver, the synchronous and asynchronous APIs returned the same ResultSet type. This made asynchronous paging very tricky, because it was very easy to accidentally trigger background synchronous queries (which would defeat the whole purpose of async, and potentially introduce deadlocks).

To avoid this problem, the driver’s asynchronous API now returns a dedicated AsyncResultSet; iteration only yields the current page, and the next page must be fetched explicitly. To iterate a result set in a fully asynchronous manner, you need to compose page futures using the methods of CompletionStage. Here’s an example that prints each row on the command line:

CompletionStage<AsyncResultSet> resultSetFuture =
    session.executeAsync("SELECT * FROM myTable WHERE id = 1");
// The returned stage will complete once all the rows have been printed:
CompletionStage<Void> printRowsFuture = resultSetFuture.thenCompose(this::printRows);

private CompletionStage<Void> printRows(AsyncResultSet resultSet) {
  for (Row row : resultSet.currentPage()) {
  if (resultSet.hasMorePages()) {
    return resultSet.fetchNextPage().thenCompose(this::printRows);
  } else {
    return CompletableFuture.completedFuture(null);

If you need to propagate state throughout the iteration, add parameters to the callback. Here’s an example that counts the number of rows (obviously this is contrived, you would use SELECT COUNT(*) instead of doing this client-side, but it illustrates the basic principle):

CompletionStage<AsyncResultSet> resultSetFuture =
    session.executeAsync("SELECT * FROM myTable WHERE id = 1");
CompletionStage<Integer> countFuture = resultSetFuture.thenCompose(rs -> countRows(rs, 0));

private CompletionStage<Integer> countRows(AsyncResultSet resultSet, int previousPagesCount) {
  int count = previousPagesCount;
  for (Row row : resultSet.currentPage()) {
    count += 1;
  if (resultSet.hasMorePages()) {
    int finalCount = count; // need a final variable to use in the lambda below
    return resultSet.fetchNextPage().thenCompose(rs -> countRows(rs, finalCount));
  } else {
    return CompletableFuture.completedFuture(count);

See Asynchronous programming for more tips about the async API.

Saving and reusing the paging state

Sometimes it is convenient to interrupt paging and resume it later. For example, this could be used for a stateless web service that displays a list of results with a link to the next page. When the user clicks that link, we want to run the exact same query, except that the iteration should start where we stopped the last time.

The driver exposes a paging state for that:

ResultSet rs = session.execute("your query");
ByteBuffer pagingState = rs.getExecutionInfo().getPagingState();

// Finish processing the current page
while (rs.getAvailableWithoutFetching() > 0) {
  Row row =;
  // process the row

// Later:
SimpleStatement statement =
    SimpleStatement.builder("your query").setPagingState(pagingState).build();

Note the loop to finish the current page after we extract the state. The new statement will start at the beginning of the next page, so we want to make sure we don’t leave a gap of unprocessed rows.

The paging state can only be reused with the exact same statement (same query string, same parameters). It is an opaque value that is only meant to be collected, stored and re-used. If you try to modify its contents or reuse it with a different statement, the results are unpredictable.

If you want additional safety, the driver also provides a “safe” wrapper around the raw value: PagingState.

PagingState pagingState = rs.getExecutionInfo().getSafePagingState();

It works in the exact same manner, except that it will throw an IllegalStateException if you try to reinject it in the wrong statement. This allows you to detect the error early, without a roundtrip to the server.

Note that, if you use a simple statement and one of the bound values requires a custom codec, you have to provide a reference to the session when reinjecting the paging state:

CustomType value = ...
SimpleStatement statement = SimpleStatement.newInstance("query", value);
// session required here, otherwise you will get a CodecNotFoundException:
statement = statement.setPagingState(pagingState, session);

This is a small corner case because checking the state requires encoding the values, and a simple statement doesn’t have a reference to the codec registry. If you don’t use custom codecs, or if the statement is a bound statement, you can use the regular setPagingState(pagingState).

Offset queries

Saving the paging state works well when you only let the user move from one page to the next. But in most Web UIs and REST services, you need paginated results with random access, for example: “given a page size of 20 elements, fetch page 5”.

Cassandra does not support this natively (see CASSANDRA-6511), because such queries are inherently linear: the database would have to restart from the beginning every time, and skip unwanted rows until it reaches the desired offset.

However, random pagination is a real need for many applications, and linear performance can be a reasonable trade-off if the cardinality stays low. The driver provides a utility to emulate offset queries on the client side: OffsetPager.

Performance considerations

For each page that you want to retrieve:

  • you need to re-execute the query, in order to start with a fresh result set;
  • you then pass the result to OffsetPager, which starts iterating from the beginning, and skips rows until it reaches the desired offset.
String query = "SELECT ...";
OffsetPager pager = new OffsetPager(20);

// Get page 2: start from a fresh result set, throw away rows 1-20, then return rows 21-40
ResultSet rs = session.execute(query);
OffsetPager.Page<Row> page2 = pager.getPage(rs, 2);

// Get page 5: start from a fresh result set, throw away rows 1-80, then return rows 81-100
rs = session.execute(query);
OffsetPager.Page<Row> page5 = pager.getPage(rs, 5);

Note that getPage can also process the entity iterables returned by the mapper.

Establishing application-level guardrails

Linear performance should be fine for the values typically encountered in real-world applications: for example, if the page size is 25 and users never go past page 10, the worst case is only 250 rows, which is a very small result set. However, we strongly recommend that you implement hard limits in your application code: if the page number is exposed to the user (for example if it is passed as a URL parameter), make sure it is properly validated and enforce a maximum, so that an attacker can’t inject a large value that could potentially fetch millions of rows.

Relation with protocol-level paging

Offset paging has no direct relation to Protocol-level paging happens under the hood, and is completely transparent for offset paging: OffsetPager will work the same no matter how many network roundtrips were needed to fetch the result. You don’t need to set the protocol page size and the logical page size to the same value.

The driver examples include two complete web service implementations demonstrating forward-only and offset paging.