Github user ben-manes commented on the issue:
https://github.com/apache/storm/pull/1783
I was a co-author of Guava's cache, too.
Guava had originally considered soft references an ideal caching scheme,
since they offer great concurrency and GC is for memory management. That
evolved from `ReferenceMap` to `MapMaker` to optimize space, especially in
regards to computations (no need for a `Future` wrapper). Unfortunately soft
references result in awful performance outside of a micro-benchmark due to
causing full GCs. In parallel, I had been experimenting with approaches for a
concurrent LRU cache
([CLHM](https://github.com/ben-manes/concurrentlinkedhashmap)) and when joining
Google helped to retrofitted its ideas onto Guava. There was a lot of good that
came out of that, but I left before working on optimizing for performance.
Java 8 provided an excuse to start from scratch. Caffeine is much faster
and packs in even more features. I also spent time exploring eviction policies,
which led to co-authoring a paper on a new technique called TinyLFU. That has a
near optimal hit rate, low memory footprint, and amortized O(1) overhead. This
is done by tracking frequency in a popularity sketch. The same concurrency
model in CLHM and Guava is used (inspired by a write-ahead log), which allows
for concurrent O(1) reads and writes.
The [HighScalability
article](http://highscalability.com/blog/2016/1/25/design-of-a-modern-cache.html)
provides an overview of the algorithms that I use.
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