daschl

Writing Resilient Reactive Applications

This guide is a first draft (that will end up in the official docs) on writing resilient code for production with the Couchbase Java SDK. At the end, the reader will be able to write code that withstands bugs, latency issues or anything else that can make their application fail.

Note that lots of concepts can be applied for both synchronous and asynchronous access. When necessary, both patterns are discussed separately. Also, the focus is on database interaction, but if you are using RxJava as part of your stack you can apply most of the principles there as well (and should!).

RxJava 101 Recap: Cold and Hot Observables

When working with Observables, it is important to understand the difference between cold and hot. Cold Observables will start to emit events once a Observer subscribes, and will do it "fresh" for each Observer. Hot Observables instead are starting to emit data as soon as it becomes available, and will return the same (or parts of the same)

jboner

Latency Comparison Numbers (~2012)
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L1 cache reference                           0.5 ns
Branch mispredict                            5   ns
L2 cache reference                           7   ns                      14x L1 cache
Mutex lock/unlock                           25   ns
Main memory reference                      100   ns                      20x L2 cache, 200x L1 cache
Compress 1K bytes with Zippy             3,000   ns        3 us
Send 1K bytes over 1 Gbps network       10,000   ns       10 us
Read 4K randomly from SSD*             150,000   ns      150 us          ~1GB/sec SSD