Jie Huang created ZOOKEEPER-3242:
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             Summary: Add server side connecting throttling
                 Key: ZOOKEEPER-3242
                 URL: https://issues.apache.org/jira/browse/ZOOKEEPER-3242
             Project: ZooKeeper
          Issue Type: Improvement
          Components: server
            Reporter: Jie Huang
             Fix For: 3.6.0


On-going performance investigation at Facebook has demonstrated that Zookeeper 
is easily overwhelmed by spikes in connection rates and/or write request rates. 
Zookeeper performance gets progressively worse, clients timeout and try to 
reconnect (exacerbating the problem) and things enter a death spiral. To solve 
this problem, we need to add load protection to Zookeeper via rate limiting and 
work shedding.
 
This Jira adds a new connection rate limiting mechanism to Zookeeper in hopes 
of preventing Zookeeper from becoming overwhelmed during connection spikes. 
The new throttle is focused on limiting connections per second. The throttle is 
implemented as a token-bucket with optional probabilistic dropping based on the 
BLUE queue management algorithm.
 
This token-bucket design allows the throttle to allow short bursts to pass, 
while still capping the total number of requests per second. However, an issue 
with a token bucket approach is that the wall clock arrival time of requests 
affects the probability of a request being allowed to pass or not. Under 
constant load this can lead to request starvation for requests that constantly 
arrive later than the majority. The optional probabilistic dropping mechanism 
is designed to combat this, making rejections a random event with little skew 
based on arrival time.
 
A more verbose description can be found in the comments in 
org.apache.zookeeper.server.BlueThrottle.
 
By default, both the token-bucket and probabilistic dropping mechanism are 
disabled. Enabling and tuning the throttles can be done both via Java system 
properties as well as against a running node via JMX.
 
The throttle has been tested and benchmarked at Facebook.



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