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From "Ariel Weisberg (JIRA)" <>
Subject [jira] [Commented] (CASSANDRA-7438) Serializing Row cache alternative (Fully off heap)
Date Tue, 04 Nov 2014 00:06:35 GMT


Ariel Weisberg commented on CASSANDRA-7438:

RE refcount:

I think hazard pointers (never used them personally) are the no-gc no-refcount way of handling
this. It also won't be fetched twice if it is uncontended which in many cases it will be since
it should be decrefd as soon as the data is copied.

I think that with the right QA work this solves the problem of running arbitrarily large caches.
That means running a validating workload in continuous integration that demonstrates the cache
doesn't lock up, leak, or return the wrong answer. I would probably test directly against
the cache to get more iterations in.

RE Implementation as a library via JNI:

We give up something by using JNI so it only makes sense if we get something else in return.
The QA and release work created by JNI is pretty large. You really need a plan for running
something like Valgrind or similar against a comprehensive suite of tests. Valgrind doesn't
run well with Java AFAIK so you end up doing things like running the native code in a separate
process, and have to write an interface amenable to that. Valgrind is also slow enough that
if you try and run all your tests against a configuration using it a lot you end up with timeouts
and many hours to run all the tests plus time spent interpreting results.

Unsafe is worse in that respect because there is no Valgrind and I can attest that debugging
an off-heap red-black tree is not fun.

I am not clear on why the JNI is justified. It really seems like this could be written against
Unsafe and then it would work on any platform. There are no libraries or system calls in use
that are only accessible via JNI. I think JNI would make more sense if we were pulling in
existing code like memcached that already handles memory pooling, fragmentation, and concurrency.
If it were in Java you could use Disruptor for the queue and would only need to implement
a thread safe off heap hash table.

RE Performance and implementation:

What kind of hardware was the benchmark run on? Server class NUMA? I am just wondering if
there are enough cores to bring out any scalability issues in the cache implementation.

It would be nice to see a benchmark that showed the on heap cache falling over while the off
heap cache provides good performance.

Subsequent comments aren't particularly useful if performance is satisfactory under relevant

Given the use of a heap allocator and locking it might not make sense to have a background
thread do expiration. I think that splitting the cache into several instances with one lock
around each instance might result in less contention overall and it would scale up in a more
straightforward way.

It appears that some common operations will hit a global lock in may_expire() quite frequently?
It seems like there are other globally shared frequently mutated cache lines in the write
path like stats.

Is there something subtle in the locking that makes the use of the custom queue and maps necessary
or could you use stuff from Intel TBB and still make it work? It is hypothetically less code
to have to QA and maintain.

I still need to dig more, but I am also not clear on why locks are necessary for individual
items. It looks like there is a table for all of them? Random intuition is that it could be
done without a lock or at least a discrete lock. Striping against a padded pool of locks might
make sense if that isn't going to cause deadlocks. Apparently every pthread_mutex_t is 40
bytes according to a random stack overflow post. It might make sense to use the same cache
line as the refcount to store a lock field, or the bucket in the hash table?

Another implementation question is do we want to use C++11? It would remove a lot of platform
and compiler specific code.

> Serializing Row cache alternative (Fully off heap)
> --------------------------------------------------
>                 Key: CASSANDRA-7438
>                 URL:
>             Project: Cassandra
>          Issue Type: Improvement
>          Components: Core
>         Environment: Linux
>            Reporter: Vijay
>            Assignee: Vijay
>              Labels: performance
>             Fix For: 3.0
>         Attachments: 0001-CASSANDRA-7438.patch
> Currently SerializingCache is partially off heap, keys are still stored in JVM heap as
> * There is a higher GC costs for a reasonably big cache.
> * Some users have used the row cache efficiently in production for better results, but
this requires careful tunning.
> * Overhead in Memory for the cache entries are relatively high.
> So the proposal for this ticket is to move the LRU cache logic completely off heap and
use JNI to interact with cache. We might want to ensure that the new implementation match
the existing API's (ICache), and the implementation needs to have safe memory access, low
overhead in memory and less memcpy's (As much as possible).
> We might also want to make this cache configurable.

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