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From "Yi Liu (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HDFS-9053) Support large directories efficiently using B-Tree
Date Tue, 29 Sep 2015 05:15:05 GMT

    [ https://issues.apache.org/jira/browse/HDFS-9053?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14934634#comment-14934634

Yi Liu commented on HDFS-9053:

Thanks for the comments, Nicholas.

Where are the numbers, especially the 4s, from? Do we assume a 32-bit world?

public class BTree<K, E extends BTree.Element<K>> implements Iterable<E>
  private final int degree;
  private Node root;
  private int size;
  private transient int modCount = 0;

private final class Node {
    static final int DEFAULT_CAPACITY = 5;
    private Object[] elements;
    private int elementsSize; 
    private Object[] children;
    private int childrenSize;
Sorry, I should use 64-bits system/JVM, and details are:

Compared to ArrayList, we increases following things:
private final int degree;           <---------   4 bytes Integer
private Node root;                   <---------  reference, 4 bytes on 32-bits system/JVM,
8 bytes on 64-bits system/JVM
private int size;                        <---------  4 bytes Integer

{{Node}} object overhead       <----------  12 bytes
private Object[] children;         <---------  null reference, 4 bytes on 32-bits system/JVM,
8 bytes on 64-bits system/JVM
private int childrenSize;           <---------  4 bytes Integer.

So totally  12+4+4+4+4+4+4 = 32 bytes on 32-bits system/JVM, and 12+4+8+4+8+4 = 40 bytes on
64-bits system/JVM. (I have not counted object alignment)

> Support large directories efficiently using B-Tree
> --------------------------------------------------
>                 Key: HDFS-9053
>                 URL: https://issues.apache.org/jira/browse/HDFS-9053
>             Project: Hadoop HDFS
>          Issue Type: Improvement
>          Components: namenode
>            Reporter: Yi Liu
>            Assignee: Yi Liu
>            Priority: Critical
>         Attachments: HDFS-9053 (BTree with simple benchmark).patch, HDFS-9053 (BTree).patch,
HDFS-9053.001.patch, HDFS-9053.002.patch
> This is a long standing issue, we were trying to improve this in the past.  Currently
we use an ArrayList for the children under a directory, and the children are ordered in the
list, for insert/delete/search, the time complexity is O(log n), but insertion/deleting causes
re-allocations and copies of big arrays, so the operations are costly.  For example, if the
children grow to 1M size, the ArrayList will resize to > 1M capacity, so need > 1M *
4bytes = 4M continuous heap memory, it easily causes full GC in HDFS cluster where namenode
heap memory is already highly used.  I recap the 3 main issues:
> # Insertion/deletion operations in large directories are expensive because re-allocations
and copies of big arrays.
> # Dynamically allocate several MB continuous heap memory which will be long-lived can
easily cause full GC problem.
> # Even most children are removed later, but the directory INode still occupies same size
heap memory, since the ArrayList will never shrink.
> This JIRA is similar to HDFS-7174 created by [~kihwal], but use B-Tree to solve the problem
suggested by [~shv]. 
> So the target of this JIRA is to implement a low memory footprint B-Tree and use it to
replace ArrayList. 
> If the elements size is not large (less than the maximum degree of B-Tree node), the
B-Tree only has one root node which contains an array for the elements. And if the size grows
large enough, it will split automatically, and if elements are removed, then B-Tree nodes
can merge automatically (see more: https://en.wikipedia.org/wiki/B-tree).  It will solve the
above 3 issues.

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