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ASF GitHub Bot commented on DRILL-4237: --------------------------------------- Github user chunhui-shi commented on the pull request: https://github.com/apache/drill/pull/430#issuecomment-206578634 @jacques-n The email response is not pushed here. So copy the sent email as below: Thanks for pointing to openHFT. Yes, I went through multiple Java implementations including this one. The reason I decided to use smhasher as the source of truth was, the smhasher implementation includes comprehensive tests to cover the attributes for measuring goodness of a non-cryptographic hash function. And these attributes are subtle and could be found out to be a problem maybe only on certain lengths of input. So when I looked at these implementations, I checked what tests they have done first. And since there is no such tests(test multiple attributes and lengths) in these Java implementations to prove the hash functions are correct or good. So I decided to start from smhasher implementations and used the results generated from smhasher to verify any other(including drill's) implementation. > 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. -- This message was sent by Atlassian JIRA (v6.3.4#6332)