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Large HashMap overview: JDK, FastUtil, Goldman Sachs, HPPC, Koloboke, Trove - January 2015 version: a quick overview of all major libraries implementing hashmaps.

Tags: hash map, FastUtil, GS collections, HPPC, Koloboke, Trove.

• FastUtil 6.6.0 turned out to be consistently fast. It may become even faster if it would introduce any other storage structures except 2 arrays for keys and values.
• Koloboke is getting second in many tests, but it still outperforms FastUtil in int-int tests.
• GS implementation is good enough, but is slower than FastUtil and Koloboke.
• JDK maps are pretty good for Object-Object maps provided that you can tolerate the extra memory consumption and you will call HashMap constructor with required capacity =actual_capacity / fill_factor + 1 to avoid rehashing.
• Trove suffers from using mod operation for array index calculations and HPPC is too slow due to an extra underlying array (for cell states).

Large HashMap overview: JDK, FastUtil, Goldman Sachs, HPPC, Koloboke, Trove - January 2015 version:
http://java-performance.info/hashmap-overview-jdk-fastutil-goldman-sachs-hppc-koloboke-trove-january-2015/
实现了hashmap的主流库速览。
关键词： hash map, FastUtil, GS collections, HPPC, Koloboke, Trove.
1. FastUtil 6.6.0 还是一贯地快。如果不是使用2个数组储存键与值而采用其他存储结构，它还可能更快。
2. Koloboke 在很多测试中都排到第二，但是在键值类型为int-int测试时胜过FastUtil。
3. JDK 在对象-对象型（Object-Object）map中表现得相当不错。这需要你忍受额外的内存消耗，额外的消耗是在构造HashMap时会需要实际容量/填充因子 + 1 （capacity = actual_capacity / fill_factor + 1）以避免再次散列。
4. Trove 遭受着在数组下标计算中使用取模运算(mod)的诟病，而且为了保存数组元素状态使用了一个隐含的额外数组使得HPPC非常的慢。(HPPC http://labs.carrotsearch.com/hppc.html)

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原文地址：http://www.cnblogs.com/re1n/p/5689404.html