cassandra-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Avi Kivity <...@scylladb.com>
Subject Re: scylladb
Date Sun, 12 Mar 2017 08:23:10 GMT


On 03/12/2017 12:19 AM, Kant Kodali wrote:
> My response is inline.
>
> On Sat, Mar 11, 2017 at 1:43 PM, Avi Kivity <avi@scylladb.com 
> <mailto:avi@scylladb.com>> wrote:
>
>     There are several issues at play here.
>
>     First, a database runs a large number of concurrent operations,
>     each of which only consumes a small amount of CPU. The high
>     concurrency is need to hide latency: disk latency, or the latency
>     of contacting a remote node.
>
> *Ok so you are talking about hiding I/O latency.  If all these I/O are 
> non-blocking system calls then a thread per core and callback 
> mechanism should suffice isn't it?*

Scylla uses a mix of user-level threads and callbacks. Most of the code 
uses callbacks (fronted by a future/promise API). SSTable writers  
(memtable flush, compaction) use a user-level thread (internally 
implemented using callbacks).  The important bit is multiplexing many 
concurrent operations onto a single kernel thread.


>     This means that the scheduler will need to switch contexts very
>     often. A kernel thread scheduler knows very little about the
>     application, so it has to switch a lot of context.  A user level
>     scheduler is tightly bound to the application, so it can perform
>     the switching faster.
>
>
> *sure but this applies in other direction as well. A user level 
> scheduler has no idea about kernel level scheduler either.  There is 
> literally no coordination between kernel level scheduler and user 
> level scheduler in linux or any major OS. It may be possible with OS's 
> that support scheduler activation(LWP's) and upcall mechanism. *

There is no need for coordination, because the kernel scheduler has no 
scheduling decisions to make.  With one thread per core, bound to its 
core, the kernel scheduler can't make the wrong decision because it has 
just one choice.


> *Even then it is hard to say if it is all worth it (The research shows 
> performance may not outweigh the complexity). Golang problem is 
> exactly this if one creates 1000 go routines/green threads where each 
> of them is making a blocking system call then it would create 1000 
> kernel threads underneath because it has no way to know that the 
> kernel thread is blocked (no upcall). *

All of the significant system calls we issue are through the main 
thread, either asynchronous or non-blocking.

> *And in non-blocking case I still don't even see a significant 
> performance when compared to few kernel threads with callback mechanism.*

We do.

> *  If you are saying user level scheduling is the Future (perhaps I 
> would just let the researchers argue about it) As of today that is not 
> case else languages would have had it natively instead of using third 
> party frameworks or libraries.
> *

User-level scheduling is great for high performance I/O intensive 
applications like databases and file systems.  It's not a general 
solution, and it involves a lot of effort to set up the infrastructure. 
However, for our use case, it was worth it.

>     There are also implications on the concurrency primitives in use
>     (locks etc.) -- they will be much faster for the user-level
>     scheduler, because they cooperate with the scheduler.  For
>     example, no atomic read-modify-write instructions need to be executed.
>
>
>      Second, how many (kernel) threads should you run?*This question 
> one will always have. If there are 10K user level threads that maps to 
> only one kernel thread then they cannot exploit parallelism. so there 
> is no right answer but a thread per core is a reasonable/good choice.
> *

Only if you can multiplex many operations on top of each of those 
threads.  Otherwise, the CPUs end up underutilized.

>     If you run too few threads, then you will not be able to saturate
>     the CPU resources.  This is a common problem with Cassandra --
>     it's very hard to get it to consume all of the CPU power on even a
>     moderately large machine. On the other hand, if you have too many
>     threads, you will see latency rise very quickly, because kernel
>     scheduling granularity is on the order of milliseconds. 
>     User-level scheduling, because it leaves control in the hand of
>     the application, allows you to both saturate the CPU and maintain
>     low latency.
>
>
>     F*or my workload and probably others I had seen Cassandra was 
> always been CPU bound.*
>
>


Yes, but does it consume 100% of all of the cores on your machine? 
Cassandra generally doesn't (on a larger machine), and when you profile 
it, you see it spending much of its time in atomic operations, or 
parking/unparking threads -- fighting with itself. It doesn't scale 
within the machine.  Scylla will happily utilize all of the cores that 
it is assigned (all of them by default in most configurations), and the 
bigger the machine you give it, the happier it will be.

>     There are other factors, like NUMA-friendliness, but in the end it
>     all boils down to efficiency and control.
>
>     None of this is new btw, it's pretty common in the storage world.
>
>     Avi
>
>
>     On 03/11/2017 11:18 PM, Kant Kodali wrote:
>>     Here is the Java version http://docs.paralleluniverse.co/quasar/
>>     <http://docs.paralleluniverse.co/quasar/> but I still don't see
>>     how user level scheduling can be beneficial (This is a well
>>     debated problem)? How can this add to the performance? or say why
>>     is user level scheduling necessary Given the Thread per core
>>     design and the callback mechanism?
>>
>>     On Sat, Mar 11, 2017 at 12:51 PM, Avi Kivity <avi@scylladb.com
>>     <mailto:avi@scylladb.com>> wrote:
>>
>>         Scylla uses a the seastar framework, which provides for both
>>         user-level thread scheduling and simple run-to-completion tasks.
>>
>>         Huge pages are limited to 2MB (and 1GB, but these aren't
>>         available as transparent hugepages).
>>
>>
>>         On 03/11/2017 10:26 PM, Kant Kodali wrote:
>>>         @Dor
>>>
>>>         1) You guys have a CPU scheduler? you mean user level thread
>>>         Scheduler that maps user level threads to kernel level
>>>         threads? I thought C++ by default creates native kernel
>>>         threads but sure nothing will stop someone to create a user
>>>         level scheduling library if that's what you are talking about?
>>>         2) How can one create THP of size 1KB? According to this
>>>         post
>>>         <https://access.redhat.com/documentation/en-US/Red_Hat_Enterprise_Linux/6/html/Performance_Tuning_Guide/s-memory-transhuge.html>
it
>>>         looks like the valid values 2MB and 1GB.
>>>
>>>         Thanks,
>>>         kant
>>>
>>>         On Sat, Mar 11, 2017 at 11:41 AM, Avi Kivity
>>>         <avi@scylladb.com <mailto:avi@scylladb.com>> wrote:
>>>
>>>             Agreed, I'd recommend to treat benchmarks as a rough
>>>             guide to see where there is potential, and follow
>>>             through with your own tests.
>>>
>>>             On 03/11/2017 09:37 PM, Edward Capriolo wrote:
>>>>
>>>>             Benchmarks are great for FUDly blog posts. Real world
>>>>             work loads matter more. Every NoSQL vendor wins their
>>>>             benchmarks.
>>>
>>>
>>>
>>
>>
>>
>>
>
>


Mime
View raw message