Spliterator.DISTINCT | Spliterator.SIZED,
        size());
  }

  @Override
  public Map<C, V> row(R rowKey) {
    return new Row(rowKey);
  }

  class Row extends IteratorBasedAbstractMap<C, V> {
    final R rowKey;

    Row(R rowKey) {
      this.rowKey = checkNotNull(rowKey);
    }

    @Nullable Map<C, V> backingRowMap;

    final void updateBackingRowMapField() {

  /**
   * {@inheritDoc}
   *
   * @throws NullPointerException if {@code rowKey} is {@code null}
   */
  @Override
  public ImmutableMap<C, V> row(R rowKey) {
    checkNotNull(rowKey, "rowKey");
    return MoreObjects.firstNonNull(
        (ImmutableMap<C, V>) rowMap().get(rowKey), ImmutableMap.<C, V>of());
  }

  @Override
  public ImmutableSet<R> rowKeySet() {

   *
   * @param rowKey key of row to search for
   * @param columnKey key of column to search for
   */
  boolean contains(
      @CompatibleWith("R") @Nullable Object rowKey,
      @CompatibleWith("C") @Nullable Object columnKey);

  /**
   * Returns {@code true} if the table contains a mapping with the specified row key.
   *
   * @param rowKey key of row to search for
   */

      R rowKey = cell.getRowKey();
      C columnKey = cell.getColumnKey();
      V value = cell.getValue();

      /*
       * These requireNonNull calls are safe because we construct the maps to hold all the provided
       * cells.
       */
      cellRowIndices[i] = requireNonNull(rowIndex.get(rowKey));
      Map<C, V> thisRow = requireNonNull(rows.get(rowKey));

@GwtCompatible
final class SingletonImmutableTable<R, C, V> extends ImmutableTable<R, C, V> {
  final R singleRowKey;
  final C singleColumnKey;
  final V singleValue;

  SingletonImmutableTable(R rowKey, C columnKey, V value) {
    this.singleRowKey = checkNotNull(rowKey);
    this.singleColumnKey = checkNotNull(columnKey);
    this.singleValue = checkNotNull(value);
  }

  SingletonImmutableTable(Cell<R, C, V> cell) {

   * referencing the type variables seem worthwhile.
   */
  final void checkNoDuplicate(R rowKey, C columnKey, @Nullable V existingValue, V newValue) {
    checkArgument(
        existingValue == null,
        "Duplicate key: (row=%s, column=%s), values: [%s, %s].",
        rowKey,
        columnKey,
        newValue,
        existingValue);
  }

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

 *
 * <p>Lookups by row key are often faster than lookups by column key, because the data is stored in
 * a {@code Map<R, Map<C, V>>}. A method call like {@code column(columnKey).get(rowKey)} still runs
 * quickly, since the row key is provided. However, {@code column(columnKey).size()} takes longer,
 * since an iteration across all row keys occurs.
 *

   * by applying the given {@code AsyncFunction} to the result of the original {@code Future}.
   * Example usage:
   *
   * {@snippet :
   * FluentFuture<RowKey> rowKeyFuture = FluentFuture.from(indexService.lookUp(query));
   * ListenableFuture<QueryResult> queryFuture =
   *     rowKeyFuture.transformAsync(dataService::readFuture, executor);
   * }
   *

   * by applying the given {@code AsyncFunction} to the result of the original {@code Future}.
   * Example usage:
   *
   * {@snippet :
   * ListenableFuture<RowKey> rowKeyFuture = indexService.lookUp(query);
   * ListenableFuture<QueryResult> queryFuture =
   *     transformAsync(rowKeyFuture, dataService::readFuture, executor);
   * }
   *