Home | About | Sematext search-lucene.com search-hadoop.com
 Search Hadoop and all its subprojects:

Switch to Threaded View
HDFS >> mail # dev >> HDFS read/write data throttling


Copy link to this message
-
Re: HDFS read/write data throttling
this is interesting -I've moved my comments over to the JIRA and it would
be good for yours to go there too.

is there a URL for your paper?
On 13 November 2013 06:27, Andrew Wang <[EMAIL PROTECTED]> wrote:

> Hey Steve,
>
> My research project (Cake, published at SoCC '12) was trying to provide
> SLAs for mixed workloads of latency-sensitive and throughput-bound
> applications, e.g. HBase running alongside MR. This was challenging because
> seeks are a real killer. Basically, we had to strongly limit MR I/O to keep
> worst-case seek latency down, and did so by putting schedulers on the RPC
> queues in HBase and HDFS to restrict queuing in the OS and disk where we
> lacked preemption.
>
> Regarding citations of note, most academics consider throughput-sharing to
> be a solved problem. It's not dissimilar from normal time slicing, you try
> to ensure fairness over some coarse timescale. I think cgroups [1] and
> ioprio_set [2] essentially provide this.
>
> Mixing throughput and latency though is difficult, and my conclusion is
> that there isn't a really great solution for spinning disks besides
> physical isolation. As we all know, you can get either IOPS or bandwidth,
> but not both, and it's not a linear tradeoff between the two. If you're
> interested in this though, I can dig up some related work from my Cake
> paper.
>
> However, since it seems that we're more concerned with throughput-bound
> apps, we might be okay just using cgroups and ioprio_set to do
> time-slicing. I actually hacked up some code a while ago which passed a
> client-provided priority byte to the DN, which used it to set the I/O
> priority of the handling DataXceiver accordingly. This isn't the most
> outlandish idea, since we've put QoS fields in our RPC protocol for
> instance; this would just be another byte. Short-circuit reads are outside
> this paradigm, but then you can use cgroup controls instead.
>
> My casual conversations with Googlers indicate that there isn't any special
> Borg/Omega sauce either, just that they heavily prioritize DFS I/O over
> non-DFS. Maybe that's another approach: if we can separate block management
> in HDFS, MR tasks could just write their output to a raw HDFS block, thus
> bringing a lot of I/O back into the fold of "datanode as I/O manager" for a
> machine.
>
> Overall, I strongly agree with you that it's important to first define what
> our goals are regarding I/O QoS. The general case is a tarpit, so it'd be
> good to carve off useful things that can be done now (like Lohit's
> direction of per-stream/FS throughput throttling with trusted clients) and
> then carefully grow the scope as we find more usecases we can confidently
> solve.
>
> Best,
> Andrew
>
> [1] cgroups blkio controller
> https://www.kernel.org/doc/Documentation/cgroups/blkio-controller.txt
> [2] ioprio_set http://man7.org/linux/man-pages/man2/ioprio_set.2.html
>
>
> On Tue, Nov 12, 2013 at 1:38 AM, Steve Loughran <[EMAIL PROTECTED]
> >wrote:
>
> > I've looked at it a bit within the context of YARN.
> >
> > YARN containers are where this would be ideal, as then you'd be able to
> > request IO capacity as well as CPU and RAM. For that to work, the
> > throttling would have to be outside the App, as you are trying to limit
> > code whether or not it wants to be, and because you probably (*) want to
> > give it more bandwidth if the system is otherwise idle. Self-throttling
> > doesn't pick up spare IO
> >
> >
> >    1. you can use cgroups in YARN to throttle local disk IO through the
> >    file:// URLs or the java filesystem APIs -such as for MR temp data
> >    2. you can't c-group throttle HDFS per YARN container, which would be
> >    the ideal use case for it. The IO is taking place in the DN, and
> cgroups
> >    only limits IO in the throttled process group.
> >    3. implementing it in the DN would require a lot more complex code
> there
> >    to prioritise work based on block ID (sole identifier that goes around
> >    everywhere) or input source (local sockets for HBase IO vs TCP stack)

CONFIDENTIALITY NOTICE
NOTICE: This message is intended for the use of the individual or entity to
which it is addressed and may contain information that is confidential,
privileged and exempt from disclosure under applicable law. If the reader
of this message is not the intended recipient, you are hereby notified that
any printing, copying, dissemination, distribution, disclosure or
forwarding of this communication is strictly prohibited. If you have
received this communication in error, please contact the sender immediately
and delete it from your system. Thank You.