JdbcStreams.java

public <T> T streamQuery(String sql, Function<Stream<SqlRowSet>, ? extends T> streamer, Object... args) {
  return jdbcTemplate.query(sql, resultSet -> {
    final SqlRowSet rowSet = new ResultSetWrappingSqlRowSet(resultSet);
    final boolean parallel = false;

    // The ResultSet API has a slight impedance mismatch with Iterators, so this conditional
    // simply returns an empty iterator if there are no results
    if (!rowSet.next()) {
      return streamer.apply(StreamSupport.stream(Spliterators.emptySpliterator(), parallel));
    }

    Spliterator<SqlRowSet> spliterator = Spliterators.spliteratorUnknownSize(new Iterator<SqlRowSet>() {
      private boolean first = true;
  
      @Override
      public boolean hasNext() {
        return !rowSet.isLast();
      }

      @Override
      public SqlRowSet next() {
        if (!first || !rowSet.next()) {
          throw new NoSuchElementException();
        }
        first = false; // iterators can be unwieldy sometimes
        return rowSet;
      }
    }, Spliterator.IMMUTABLE);
    return streamer.apply(StreamSupport.stream(spliterator, parallel));
  }, args);
}

Fortunately, there is JdbcTemplate.queryForStream() method since Spring 5.3
Thus, this approach is not useful anymore

Meh, that's totally missing the point! The idea is lazy consumption (on the fly row processing), but with JdbcTemplate::queryForRowSet you're just aggregating results in memory! For that to workJdbcTemplate would have to keep the db connection open after making that call and it just doesn't do that.

@sabirove It's been a while since I looked at this. This actually does work lazily. RowSet fetches on demand using a database cursor. That is the whole point of this approach. You have to indeed keep the connection open and process everything in a single connection for this to work because otherwise the database closes the cursor.

I used this to stream export tables that definitely would not fit in memory on the small vm I used to run this on. You need some additional Spring hackery to be able to write to the response directly of course (it normally would buffer everything in memory and then write to the response). Not that trivial with Spring Flux but I managed to do that. Basically, this allows you stream many gigabytes of data to a file with a simple curl command. It starts streaming data right away while it is still fetching data from the database and it writes at the speed it can fetch data from the database. Nice if you want your data in csv or ndjson format via a rest api, which was in fact my use case.

@wakedeer Nice that Spring added proper support for this. Makes this a bit easier.