Clarification on Hardware Requirements and Performance

[Joseph Grasser]

It is written in the docs that "On a fast machine with very high speed networking, memcached can easily handle 200,000+ requests per second." How fast does a machine have to be in order to server that load easily? What are the hardware requirements for such a server?

https://github.com/memcached/memcached/wiki/Performance

[Henrik Schröder]

Anecdotal datapoint: I have a machine with 2xE5520 (Xeon server processor from 2009) which does ~300k requests/s, and handles ~400Mbps of network traffic, but only using ~5% of the CPU.

It's been my experience that you will saturate your network way before you'll saturate your CPU on pretty much any current hardware.

On Thu, Aug 25, 2016 at 10:12 PM, Joseph Grasser <jgrass...@gmail.com> wrote:

It is written in the docs that "On a fast machine with very high speed networking, memcached can easily handle 200,000+ requests per second." How fast does a machine have to be in order to server that load easily? What are the hardware requirements for such a server?

https://github.com/memcached/memcached/wiki/Performance

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[Ripduman Sohan]

Some more numbers:https://www.solarflare.com/Media/Default/PDFs/Solutions/Solarflare-Accelerating-Memcached-Using-Flareon-Ultra-server-IO-adapter.pdf

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--rip

[dormando]

Is that still using a modified codebase?

On Fri, 26 Aug 2016, Ripduman Sohan wrote:

> Some more numbers:https://www.solarflare.com/Media/Default/PDFs/Solutions/Solarflare-Accelerating-Memcached-Using-Flareon-Ultra-server-IO-adapter.pdf
>
> On 26 August 2016 at 07:08, Henrik Schröder <skr...@gmail.com> wrote:
> Anecdotal datapoint: I have a machine with 2xE5520 (Xeon server processor from 2009) which does ~300k requests/s, and handles ~400Mbps of network traffic, but only
> using ~5% of the CPU.
>
> It's been my experience that you will saturate your network way before you'll saturate your CPU on pretty much any current hardware.
>
>
>
> On Thu, Aug 25, 2016 at 10:12 PM, Joseph Grasser <jgrass...@gmail.com> wrote:
> It is written in the docs that "On a fast machine with very high speed networking, memcached can easily handle 200,000+ requests per second." How fast does a
> machine have to be in order to server that load easily? What are the hardware requirements for such a server?
>
> https://github.com/memcached/memcached/wiki/Performance
>
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[Ripduman Sohan]

I believe it's standard memcached compared on kernel and OpenOnload TCP stacks.  I have had no involvement with this though so it's just conjecture on my part.  I guess sa...@solarflare.com knows more, I can find out if it helps. 

On 26 August 2016 at 23:37, dormando <dorm...@rydia.net> wrote:

Is that still using a modified codebase?

On Fri, 26 Aug 2016, Ripduman Sohan wrote:

> Some more numbers:https://www.solarflare.com/Media/Default/PDFs/Solutions/Solarflare-Accelerating-Memcached-Using-Flareon-Ultra-server-IO-adapter.pdf
>
> On 26 August 2016 at 07:08, Henrik Schröder <skr...@gmail.com> wrote:
>       Anecdotal datapoint: I have a machine with 2xE5520 (Xeon server processor from 2009) which does ~300k requests/s, and handles ~400Mbps of network traffic, but only
>       using ~5% of the CPU.
>
> It's been my experience that you will saturate your network way before you'll saturate your CPU on pretty much any current hardware.
>
>
>
> On Thu, Aug 25, 2016 at 10:12 PM, Joseph Grasser <jgrass...@gmail.com> wrote:
>       It is written in the docs that "On a fast machine with very high speed networking, memcached can easily handle 200,000+ requests per second." How fast does a
>       machine have to be in order to server that load easily? What are the hardware requirements for such a server?
>
> https://github.com/memcached/memcached/wiki/Performance
>
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[Joseph Grasser]

Thank you for the tips guys!

The limiting factor for us is actually memory utilization. We are using the default configuration on sizable ec2 nodes and pulling only like 20k qps per node. Which is fine because we need to shard the key set over x servers to handle the mem req (30G) per server.

I should have looked into that before posting.

I am really curious about network saturation though. 200k gets at 1mb per get is a lot of traffic... how can you hit that mark without saturation?

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[dormando]

>
> Thank you for the tips guys!
>
> The limiting factor for us is actually memory utilization. We are using the default configuration on sizable ec2 nodes and pulling only like 20k qps per node. Which is fine
> because we need to shard the key set over x servers to handle the mem req (30G) per server.
>
> I should have looked into that before posting.
>
> I am really curious about network saturation though. 200k gets at 1mb per get is a lot of traffic... how can you hit that mark without saturation?

Most people's keys are a lot smaller. In multiget tests with 40 byte keys
I can pull 20 million+ keys/sec out of the server. probably less than
10gbps at that rate too. Tends to cap between 600k and 800k/s if you need
to do a full roundtrip per key fetch. limited by the NIC. Lots of tuning
required to get around that.

In pure throughput over localhost I've gotten it past 78 gigabits.. using
16k keys.

it's pretty snappy.

>
> On Aug 26, 2016 3:41 PM, "Ripduman Sohan" <ripduma...@gmail.com> wrote:
> I believe it's standard memcached compared on kernel and OpenOnload TCP stacks.  I have had no involvement with this though so it's just conjecture on my part.  I
> guess sa...@solarflare.com knows more, I can find out if it helps. 
>
>
> On 26 August 2016 at 23:37, dormando <dorm...@rydia.net> wrote:
> Is that still using a modified codebase?
>
> On Fri, 26 Aug 2016, Ripduman Sohan wrote:
>
> > Some more numbers:https://www.solarflare.com/Media/Default/PDFs/Solutions/Solarflare-Accelerating-Memcached-Using-Flareon-Ultra-server-IO-adapter.pdf
> >
> > On 26 August 2016 at 07:08, Henrik Schröder <skr...@gmail.com> wrote:
> >       Anecdotal datapoint: I have a machine with 2xE5520 (Xeon server processor from 2009) which does ~300k requests/s, and handles ~400Mbps of network
> traffic, but only
> >       using ~5% of the CPU.
> >
> > It's been my experience that you will saturate your network way before you'll saturate your CPU on pretty much any current hardware.
> >
> >
> >
> > On Thu, Aug 25, 2016 at 10:12 PM, Joseph Grasser <jgrass...@gmail.com> wrote:
> >       It is written in the docs that "On a fast machine with very high speed networking, memcached can easily handle 200,000+ requests per second." How fast
> does a
> >       machine have to be in order to server that load easily? What are the hardware requirements for such a server?
> >
> > https://github.com/memcached/memcached/wiki/Performance
> >
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[Joseph Grasser]

I don't really have high visibility into the average item size but I see what you mean.

Stats should give us good info on that right?

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[Ripduman Sohan]

On Aug 27, 2016 1:46 AM, "dormando" <dorm...@rydia.net> wrote:

>
> Thank you for the tips guys!
>
> The limiting factor for us is actually memory utilization. We are using the default configuration on sizable ec2 nodes and pulling only like 20k qps per node. Which is fine
> because we need to shard the key set over x servers to handle the mem req (30G) per server.
>
> I should have looked into that before posting.
>
> I am really curious about network saturation though. 200k gets at 1mb per get is a lot of traffic... how can you hit that mark without saturation?

Most people's keys are a lot smaller. In multiget tests with 40 byte keys
I can pull 20 million+ keys/sec out of the server. probably less than
10gbps at that rate too. Tends to cap between 600k and 800k/s if you need
to do a full roundtrip per key fetch. limited by the NIC. Lots of tuning
required to get around that.

I think (but may be wrong) the 200K TPS result is based on 1K values.  Dormando should be able to correct me. 

20K TPS does seem a little low though.  If you're bound by memory set size have you thought of the cost/tradeoff benefits of using dedicated servers for your memcache?  

I'm quite interested to find out more about what you're trying to optimise.  Is it minimising number of servers, maximising query rate, both, none, etc? 

Feel free to reach out directly if you can't share this publicly. 

 

[Joseph Grasser]

No problem, I'm trying cut down on cost. We're currently using a dedicated model which works for us on a technical level but is expensive (within budget but still expensive).

We are experiencing weird spikes in evictions but I think that is the result of developers abusing the service.

Tbh I don't know what to make of the evictions yet. I'm gong to dig into it on Monday though.

--

[Ripduman Sohan]

On 27 August 2016 at 10:05, Joseph Grasser <jgrass...@gmail.com> wrote:

No problem, I'm trying cut down on cost. We're currently using a dedicated model which works for us on a technical level but is expensive (within budget but still expensive).

We are experiencing weird spikes in evictions but I think that is the result of developers abusing the service.

Tbh I don't know what to make of the evictions yet. I'm gong to dig into it on Monday though.

So if it's cost I'd assume you want to minimise the number of dedicated servers which means that you want to maximise the capacity (in memory) per server _and_ the performance (throughput) per server.  I'd start by looking at the distribution of request sizes and then working out, through a combination of empirical measurement and theoretical analysis -- what is the peak performance you can expect from a server and comparing it with what you get now.  It'll quickly tell you if this is an exercise worth pursuing. 

If it turns out you're near optimum performance there are a bunch of secondary tricks (caching flash, compression, alternate cache replacement algorithms etc) that you can pursue.  These techniques are not on-topic for this list but, again, reach out offline if you want pointers. 

With respect to LRU eviction, stats should give you an idea.  I'd start by looking at the put:get ratio and the LRU times of evicted entries to get an idea of whether abuse is the case or whether it's a capacity issue. 

Rip

[dormando]

What version are you on and what're your startup options, out of
curiosity?

A lot of the more recent features can help with memory efficiency, for
what it's worth.

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[Joseph Grasser]

We are running 1.4.13 on wheezy. 

In the environment I am looking at there is positive correlation between gets and puts. The ration is something like 10 Gets : 15 Puts. The eviction spikes are also occurring at peak put times ( which kind of makes senses with the mem pressure ). I think the application is some kind of report generation tool - it's hard to say, my visibility into the team stuff is pretty low right now as I am a new hire. 

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[dormando]

You could comb through stats looking for things like evicted_unfetched,
unbalanced slab classes, etc.

1.4.31 with `-o modern` can either make a huge improvement in memory
efficiency or a marginal one. I'm unaware of it being worse.

Just something to consider if cost is your concern.

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[Joseph Grasser]

echo "stats" shows the following : 

cmd_set 3,000,000,000

evicted_unfetched 2,800,000,000

evictions 2,900,000,000

This looks super abusive to me. What, is that 6% utilization of data in cache? 

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[dormando]

Probably.

Look through `stats slabs` and `stats items` to see if evictions skew
toward slabs without enough pages in it, that sort of thing. That's all
fixed (or improved) in more recent versions (with enough feature flags
enabled)

you can also telnet in and run `watch evictions` to get a stream of what's
being evicted. Look for patterns or bug developers about it.

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[Joseph Grasser]

So, when I compare the total pages with the unfetched evictions I do notice skew. We should probably reallocate the pages to better fit our usage pattern. 

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[Joseph Grasser]

Hey Guys, thank you so much for everything

This community is awesome; the product is awesome; everyone here is awesome; and most of all everyone on this thread is awesome! 

[dormando]

Thanks!

You can reallocate pages in newer versions. as I said before the `-o
modern` on the latest ones does that automatically so long as you have
some free space for it to work with (the lru_crawler and using sane TTL's
helps there). Otherwise you can use manual controls as listed in
doc/protocol.txt and your own external process.

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[Joseph Grasser]

I just left my client so this is not a pressing concern anymore, but my curiosity is peaked. What kind of compression would you recommend? How much strain does that but on compute resources? Would that lower qps?