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https://issues.apache.org/jira/browse/HADOOP-11152?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14247594#comment-14247594
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RJ Nowling commented on HADOOP-11152:
-------------------------------------
Hi all,
What about quasi-random numbers?
If you generate a large number of samples using a RNG, the set of numbers will
be approximately uniformly distributed. However, if you take a small number of
samples (say 50), you would see that they are not picked uniformly. E.g.,
samples may cluster. RNGs are not necessarily guaranteed to maintain the
uniform nature for small groups of samples. (Some may do that, however.)
Quasi-random sequences ensure that the set of numbers generated maintains a
uniform distribution regardless of whether you pick 100 or 10,000. You may
want to read this blog entry by John D. Cook for an example:
http://www.johndcook.com/blog/2009/03/16/quasi-random-sequences-in-art-and-integration/
.
Numerical Recipes discusses algorithms for generating sequences of quasi-random
numbers.
> Better random number generator
> ------------------------------
>
> Key: HADOOP-11152
> URL: https://issues.apache.org/jira/browse/HADOOP-11152
> Project: Hadoop Common
> Issue Type: Improvement
> Reporter: Luke Lu
> Labels: newbie++
>
> HDFS-7122 showed that naive ThreadLocal usage of simple LCG based j.u.Random
> creates unacceptable distribution of random numbers for block placement.
> Similarly, ThreadLocalRandom in java 7 (same static thread local with
> synchronized methods overridden) has the same problem.
> "Better" is defined as better quality and faster than j.u.Random (which is
> already much faster (20x) than SecureRandom).
> People (e.g. Numerical Recipes) have shown that by combining LCG and XORShift
> we can have a better fast RNG. It'd be worthwhile to investigate a thread
> local version of these "better" RNG.
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