Ying Zheng created KAFKA-6431:
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Summary: Lock contention in Purgatory
Key: KAFKA-6431
URL: https://issues.apache.org/jira/browse/KAFKA-6431
Project: Kafka
Issue Type: Improvement
Components: core
Reporter: Ying Zheng
Priority: Minor
Purgatory is the data structure in Kafka broker that manages delayed
operations. There is a ConcurrentHashMap (Kafka Pool) maps each operation key
to the operations (in a ConcurrentLinkedQueue) that are interested in the key.
When an operation is done or expired, it's removed from the list
(ConcurrentLinkedQueue). When the list is empty, it's removed from the
ConcurrentHashMap. The 2nd operation has to be protected by a lock, to avoid
adding new operations into a list that is being removed. This is currently done
by a globally shared ReentrantReadWriteLock. All the read operations on
purgatory have to acquire the read permission of this lock. The list removing
operations needs the write permission of this lock.
Our profiling result shows that Kafka broker is spending a nontrivial time on
this read write lock.
The problem is exacerbated when there are a large amount of short operations.
For example, when we are doing sync produce operations (acks=all), a
DelayedProduce operation is added and then removed for each message. If the QPS
of the topic is not high, it's very likely that, when the operation is done and
removed, the list of that key (topic partitions) becomes empty, and has to be
removed when holding the write lock. This operation blocks all the read / write
operations on purgatory for awhile. As there are tens of IO threads accessing
purgatory concurrently, this shared lock can easily become a bottleneck.
Actually, we only want to avoid concurrent read / write on the same key. The
operations on different keys do not conflict with each other.
I suggest to shard purgatory into smaller partitions, and lock each individual
partition independently.
Assuming there are 10 io threads actively accessing purgatory, sharding
purgatory into 512 partitions will make the probability for 2 threads accessing
the same partition at the same time to about 2%. We also can use ReentrantLock
instead of ReentrantReadWriteLock. When the read operations are not much more
than write operations, ReentrantLock has lower overhead than
ReentrantReadWriteLock.
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