[infinispan-dev] Implementing LIRS eviction policy [ISPN-299]

[Bryan Thompson]

Vladimir,

Sure.  I will keep you updated.  We have several of our own implementations and we have been evaluating an implementation based on the LRUDataContainer, which has a wicked hot spot as I am sure you know.  This batching approach sounds quite promising.  We will try it on our existing implementations and we can evaluate (or help on) the infinispan version.

Bryan

________________________________
From: infinispan-dev-bounces at lists.jboss.org [mailto:infinispan-dev-bounces at lists.jboss.org] On Behalf Of Vladimir Blagojevic
Sent: Friday, January 08, 2010 10:08 AM
To: infinispan -Dev List
Cc: Martyn Cutcher
Subject: Re: [infinispan-dev] Implementing LIRS eviction policy [ISPN-299]

Hey Bryan,

On 2010-01-08, at 1:35 PM, Bryan Thompson wrote:

Vladimir,

Reading the paper, it appears that my suggestion of segments is called "distributed locks" in this paper and the authors suggests:

> For example, the algorithms that need to detect sequence of accesses cannot retain their performance advantages when pages in the same sequence have been distributed into multiple partitions and cannot be identified as a sequence.

Indeed, but this sequence access seems to be important for subgroup of algorithms like SEQ. To be honest, when I first read the paper I was surprised by the authors claim that batching does not affect precision of LIRS and LRU. LIRS and LRU need order of access too by it seems that approximated access is not affecting precision significantly.

Along the same lines we have to figure out if segmenting and batching per segment is going to affect algorithm precision overall. If someone can prove that this is dead end please argue your point :) Otherwise, intuitively speaking, I cannot see how batching per segment would suddenly make LIRS imprecise if batching did not do so in the first place.


Overall, I like the approach outlined in the paper.  It takes the concept of batching further than what we did, but in much the same spirit.  In our implementation, we only batched evictions.  They are also batching the updates to the replacement policy ordering which is still a bottleneck for us.

Concerning the FIFO queue, the paper (page 372) considers both per-thread queues or global queues.  They dismiss global queues for batching updates primarily because certain cache replacement policies need to detect sequences of operations.  Can such sequences of operations be meaningfully detected within infinispan?  Is there any thread-affinity for a transaction?  If not, then segmented queues might be an alternative for infinispan.

Yes, they dismiss global queue over algorithms we do not plan to use and locking cost of a global queue. I am betting that global lock free queue per Infinispan DataContainer is less costly than shared BP-Wrapper objects that we have to maintain in a pool and share among threads (they are not shared in the paper but we have to). As I mentioned the problem for us is that we can potentially have spikes of up to hundreds of threads in a cache instance. Infinispan use case differs from PostgreSQL used in the paper but I agree that potential impact of global lock free queue should not be dismissed and I would switch to pooling approach if it is proven that lock free queue causes bottleneck.



Also, for java, if the hash map uses weak values then cache entries then any entries on the FIFO queues will remain pinned in the hash map even if they would have otherwise been evicted by the cache policy which is a nice touch.  That way you can continue to access an object which remains accessible to the JVM held even if the cache replacement policy would have discarded the cache entry.

The experiment in the paper compared several cache replacement policies, but the data were all hot in cache and the cache was large enough to avoid all cache misses, so I am not clear why they bothered to compare different cache replacement policies -- none of them did any evictions for their tests. While "prefetching" did reduce the lock contention slightly, it had no meaningful effect on either throughput or response time.  The authors posit that it might have more effect on machines with many more cores, depending on the CPU architecture.  It seems easily enough to ignore the prefetch dimension for now and just concentrate on batching.

Exactly the same sentiment here :)



So, I think that the batching approach per this paper makes sense and could be combined with LRU or LIRS easily since the cache replacement policy is encapsulated (which might not be true with prefetch) and seems overall like a good idea and an improvement on what we were already doing.  For our application, I think that we would use a hash map with weak values (per above) to gain the benefit of the actual retention time of the object by the JVM.  I would also like to explore the use of segmented queues as well as per-thread queues to control the #of queues in the system separately from the #of threads.  By batching updates to the access order, you are also effectively batching evictions since they are driven by updates.  When combined with a weak value caches, the thread running the updates should also clear entries from the cache on the weak reference queue, thereby batching the clearing of stale cache entries (those with cleared references) at the same time it is batching updates to the access order and inserts to the cache.

Bryan

Excellent, lets keep cooperating on this one. If you are already in implementation stage, and it seems that you are, let us know of the progress you make and performance increases you observe.


Regards,
Vladimir
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