*/
  public static <T extends @Nullable Object> List<List<T>> partition(List<T> list, int size) {
    checkNotNull(list);
    checkArgument(size > 0);
    return (list instanceof RandomAccess)
        ? new RandomAccessPartition<>(list, size)
        : new Partition<>(list, size);
  }

  private static class Partition<T extends @Nullable Object> extends AbstractList<List<T>> {
    final List<T> list;

   * @param size the desired size of each partition (the last may be smaller)
   * @return an iterator of immutable lists containing the elements of {@code iterator} divided into
   *     partitions
   * @throws IllegalArgumentException if {@code size} is nonpositive
   */
  public static <T extends @Nullable Object> UnmodifiableIterator<List<T>> partition(
      Iterator<T> iterator, int size) {

	fivs, err := getAllFileInfoVersions(xlMetaBuf, volume, path, true)
	if err != nil {
		return fivs, err
	}

	// If inclFreeVersions is false, partition the versions in fivs.Versions
	// such that finally fivs.Versions has
	// all the non-free versions and fivs.FreeVersions has all the free
	// versions.
	n := 0
	for _, fi := range fivs.Versions {

        swap(array, min, from);
      }
      return;
    }

    // Let's play quickselect! We'll repeatedly partition the range [from, to] containing the
    // required element, as long as it has more than one element.
    while (to > from) {
      int partitionPoint = partition(array, from, to);
      if (partitionPoint >= required) {
        to = partitionPoint - 1;
      }

					}

					rnnColumn := clause.Column{Name: "gorm_preload_rnn"}
					sql := "ROW_NUMBER() OVER (PARTITION BY ? ?)"
					vars := []interface{}{partitionBy}
					if orderBy, ok := q.db.Statement.Clauses["ORDER BY"]; ok {
						vars = append(vars, orderBy)
					} else {

```
cat ${HADOOP_CONF_DIR}/core-site.xml | kv-pairify | grep "mapred"

mapred.maxthreads.generate.mapoutput=2 # Num threads to write map outputs
mapred.maxthreads.partition.closer=0 # Asynchronous map flushers
mapreduce.fileoutputcommitter.algorithm.version=2 # Use the latest committer version
mapreduce.job.reduce.slowstart.completedmaps=0.99 # 99% map, then reduce

	resp, err := getNetInfoRPC.Call(ctx, client.gridConn(), grid.NewMSS())
	return resp.ValueOrZero(), err
}

// GetPartitions - fetch disk partition information for a remote node.
func (client *peerRESTClient) GetPartitions(ctx context.Context) (info madmin.Partitions, err error) {
	resp, err := getPartitionsRPC.Call(ctx, client.gridConn(), grid.NewMSS())
	return resp.ValueOrZero(), err
}

	info := madmin.GetNetInfo(globalLocalNodeName, globalInternodeInterface)
	return madminNetInfo.NewJSONWith(&info), nil
}

// GetPartitionsHandler - returns disk partition information.
func (s *peerRESTServer) GetPartitionsHandler(_ *grid.MSS) (*grid.JSON[madmin.Partitions], *grid.RemoteErr) {
	info := madmin.GetPartitions(context.Background(), globalLocalNodeName)
	return madminPartitions.NewJSONWith(&info), nil
}

		if err != nil {
			sys.addNodeErr(&reply[index], sys.peerClients[index], err)
		}
	}
	return reply
}

// GetPartitions - Disk partition information
func (sys *NotificationSys) GetPartitions(ctx context.Context) []madmin.Partitions {
	reply := make([]madmin.Partitions, len(sys.peerClients))

	g := errgroup.WithNErrs(len(sys.peerClients))
	for index, client := range sys.peerClients {
		if client == nil {

		// call will report top level prefixes in deleted state, whereas spark/hadoop interpret this as non-empty
		// and throw a 404 exception. This is especially a problem for spark jobs overwriting the same partition
		// repeatedly. This workaround recursively lists the top 3 entries including delete markers to reflect the
		// correct state of the directory in the list results.
		if strings.HasSuffix(opts.Prefix, SlashSeparator) {