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From "Gopal V (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (HIVE-8038) Decouple ORC files split calculation logic from Filesystem's get file location implementation
Date Tue, 16 Sep 2014 03:18:34 GMT

     [ https://issues.apache.org/jira/browse/HIVE-8038?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Gopal V updated HIVE-8038:
--------------------------
    Status: Open  (was: Patch Available)

> Decouple ORC files split calculation logic from Filesystem's get file location implementation
> ---------------------------------------------------------------------------------------------
>
>                 Key: HIVE-8038
>                 URL: https://issues.apache.org/jira/browse/HIVE-8038
>             Project: Hive
>          Issue Type: Improvement
>          Components: File Formats
>    Affects Versions: 0.13.1
>            Reporter: Pankit Thapar
>            Assignee: Pankit Thapar
>             Fix For: 0.14.0
>
>         Attachments: HIVE-8038.2.patch, HIVE-8038.patch
>
>
> What is the Current Logic
> ======================
> 1.get the file blocks from FileSystem.getFileBlockLocations() which returns an array
of BlockLocation
> 2.In SplitGenerator.createSplit(), check if split only spans one block or multiple blocks.
> 3.If split spans just one block, then using the array index (index = offset/blockSize),
get the corresponding host having the blockLocation
> 4.If the split spans multiple blocks, then get all hosts that have at least 80% of the
max of total data in split hosted by any host.
> 5.add the split to a list of splits
> Issue with Current Logic
> =====================
> Dependency on FileSystem API’s logic for block location calculations. It returns an
array and we need to rely on FileSystem to  
> make all blocks of same size if we want to directly access a block from the array.
>  
> What is the Fix
> =============
> 1a.get the file blocks from FileSystem.getFileBlockLocations() which returns an array
of BlockLocation
> 1b.convert the array into a tree map <offset, BlockLocation> and return it through
getLocationsWithOffSet()
> 2.In SplitGenerator.createSplit(), check if split only spans one block or multiple blocks.
> 3.If split spans just one block, then using Tree.floorEntry(key), get the highest entry
smaller than offset for the split and get the corresponding host.
> 4a.If the split spans multiple blocks, get a submap, which contains all entries containing
blockLocations from the offset to offset + length
> 4b.get all hosts that have at least 80% of the max of total data in split hosted by any
host.
> 5.add the split to a list of splits
> What are the major changes in logic
> ==============================
> 1. store BlockLocations in a Map instead of an array
> 2. Call SHIMS.getLocationsWithOffSet() instead of getLocations()
> 3. one block case is checked by "if(offset + length <= start.getOffset() + start.getLength())"
 instead of "if((offset % blockSize) + length <= blockSize)"
> What is the affect on Complexity (Big O)
> =================================
> 1. We add a O(n) loop to build a TreeMap from an array but its a one time cost and would
not be called for each split
> 2. In case of one block case, we can get the block in O(logn) worst case which was O(1)
before
> 3. Getting the submap is O(logn)
> 4. In case of multiple block case, building the list of hosts is O(m) which was O(n)
& m < n as previously we were iterating 
>    over all the block locations but now we are only iterating only blocks that belong
to that range go offsets that we need. 
> What are the benefits of the change
> ==============================
> 1. With this fix, we do not depend on the blockLocations returned by FileSystem to figure
out the block corresponding to the offset and blockSize
> 2. Also, it is not necessary that block lengths is same for all blocks for all FileSystems
> 3. Previously we were using blockSize for one block case and block.length for multiple
block case, which is not the case now. We figure out the block
>    depending upon the actual length and offset of the block



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