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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (DRILL-4237) Skew in hash distribution
Date Fri, 08 Apr 2016 00:01:34 GMT

    [ https://issues.apache.org/jira/browse/DRILL-4237?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15231370#comment-15231370
] 

ASF GitHub Bot commented on DRILL-4237:
---------------------------------------

Github user jacques-n commented on the pull request:

    https://github.com/apache/drill/pull/430#issuecomment-207142922
  
    @amansinha100, I trust your feedback on the code review. 
    
    I'm a little worried that we continue to reimplement things that exist externally and
then have to pay more maintenance than we can afford. It may make sense to have our own hash
implementations rather than use a shared library, I really don't know. I just want to make
sure we're evaluating the options rather than just building our own. For example, if we started
now, I would be inclined to leverage grpc rather than build our own rpc layer.


> Skew in hash distribution
> -------------------------
>
>                 Key: DRILL-4237
>                 URL: https://issues.apache.org/jira/browse/DRILL-4237
>             Project: Apache Drill
>          Issue Type: Bug
>          Components: Functions - Drill
>    Affects Versions: 1.4.0
>            Reporter: Aman Sinha
>            Assignee: Chunhui Shi
>
> Apparently, the fix in DRILL-4119 did not fully resolve the data skew issue.  It worked
fine on the smaller sample of the data set but on another sample of the same data set, it
still produces skewed values - see below the hash values which are all odd numbers. 
> {noformat}
> 0: jdbc:drill:zk=local> select columns[0], hash32(columns[0]) from `test.csv` limit
10;
> +-----------------------------------+--------------+
> |              EXPR$0               |    EXPR$1    |
> +-----------------------------------+--------------+
> | f71aaddec3316ae18d43cb1467e88a41  | 1506011089   |
> | 3f3a13bb45618542b5ac9d9536704d3a  | 1105719049   |
> | 6935afd0c693c67bba482cedb7a2919b  | -18137557    |
> | ca2a938d6d7e57bda40501578f98c2a8  | -1372666789  |
> | fab7f08402c8836563b0a5c94dbf0aec  | -1930778239  |
> | 9eb4620dcb68a84d17209da279236431  | -970026001   |
> | 16eed4a4e801b98550b4ff504242961e  | 356133757    |
> | a46f7935fea578ce61d8dd45bfbc2b3d  | -94010449    |
> | 7fdf5344536080c15deb2b5a2975a2b7  | -141361507   |
> | b82560a06e2e51b461c9fe134a8211bd  | -375376717   |
> +-----------------------------------+--------------+
> {noformat}
> This indicates an underlying issue with the XXHash64 java implementation, which is Drill's
implementation of the C version.  One of the key difference as pointed out by [~jnadeau] was
the use of unsigned int64 in the C version compared to the Java version which uses (signed)
long.  I created an XXHash version using com.google.common.primitives.UnsignedLong.  However,
UnsignedLong does not have bit-wise operations that are needed for XXHash such as rotateLeft(),
 XOR etc.  One could write wrappers for these but at this point, the question is: should we
think of an alternative hash function ? 
> The alternative approach could be the murmur hash for numeric data types that we were
using earlier and the Mahout version of hash function for string types (https://github.com/apache/drill/blob/master/exec/java-exec/src/main/java/org/apache/drill/exec/expr/fn/impl/HashHelper.java#L28).
 As a test, I reverted to this function and was getting good hash distribution for the test
data. 
> I could not find any performance comparisons of our perf tests (TPC-H or DS) with the
original and newer (XXHash) hash functions.  If performance is comparable, should we revert
to the original function ?  
> As an aside, I would like to remove the hash64 versions of the functions since these
are not used anywhere. 



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