Michael Griggs created IGNITE-4828: -------------------------------------- Summary: Improve the distribution of keys within partitions Key: IGNITE-4828 URL: https://issues.apache.org/jira/browse/IGNITE-4828 Project: Ignite Issue Type: Improvement Affects Versions: 1.9 Reporter: Michael Griggs Fix For: 2.0
An issue has been found when inserting several million string keys in to a cache. Each string key was approximately 22-characters in length. When I exported the partition counts (via GG Visor) I was able to see an unusual periodicity in the number of keys allocated to partitions. I charted this in Excel (1). After further investigation, it appears that there is a relationship between the number of keys being inserted, the number of partitions assigned to the cache and amount of apparent periodicity: a small number ofpartitions will cause periodicity to appear with a lower number of keys. The {{RendezvousAffinityFunction#partition}} function performs a simple calculation of key hashcode modulo partition-count: {{U.safeAbs(key.hashCode() % parts)}} Digging further I was led to the fact that this is how the Java HashMap *used* to behave (2), but was upgraded around Java 1.4 to perform the following: {{key.hashCode() & (parts - 1)}} which performs more efficiently. It was then updated further to do the following: {{(h = key.hashCode()) ^ (h >>> 16);}} with the bit-shift performed to bq. incorporate impact of the highest bits that would otherwise never be used in index calculations because of table bounds When using this function, rather than our {{RendezvousAffinityFunction#partition}} implementation, I also saw a significant decrease in the periodicity and a better distribution of keys amongst partitions (3). (1): https://i.imgur.com/0FtCZ2A.png (2): https://www.quora.com/Why-does-Java-use-a-mediocre-hashCode-implementation-for-strings (3): https://i.imgur.com/8ZuCSA3.png -- This message was sent by Atlassian JIRA (v6.3.15#6346)