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From "Yi Liu (JIRA)" <j...@apache.org>
Subject [jira] [Created] (HDFS-9053) Support large directories efficiently using B-Tree
Date Fri, 11 Sep 2015 07:23:46 GMT
Yi Liu created HDFS-9053:

             Summary: 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

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
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

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