It looks good to me as it provides a nice balance between reliability
It's certainly one possible solution to the issue, though I do believe
that the current one could be made more friendly towards single disk
access(e.g. batching writes to the disk may well be doable and would be
curious what someone with more familiarity with the implementation thinks).
On 07/04/2012 06:36 PM, Jarek Jarcec Cecho wrote:
> We had connected discussion about this "SpillableChannel" (working name) on FLUME-1045 and I believe that consensus is that we will create something like that. In fact, I'm planning to do it myself in near future - I just need to prioritize my todo list first.
> On Wed, Jul 04, 2012 at 06:13:43PM +0900, Juhani Connolly wrote:
>> Yes... I was actually poking around for that issue as I remembered
>> seeing it before. I had before also suggested a compound channel
>> that would have worked like the buffer store in scribe, but general
>> opinion was that it provided too many mixed configurations that
>> could make testings and verifying correctness difficult.
>> On 07/04/2012 04:33 PM, Jarek Jarcec Cecho wrote:
>>> Hi Juhally,
>>> while ago I've filled jira FLUME-1227 where I've suggested creating some sort of SpillableChannel that would behave similarly as scribe. It would be normally acting as memory channel and it would start spilling data to disk in case that it would get full (my primary goal here was to solve issue when remote goes down, for example in case of HDFS maintenance). Would it be helpful for your case?
>>> On Wed, Jul 04, 2012 at 04:07:48PM +0900, Juhani Connolly wrote:
>>>> Evaluating flume on some of our servers, the file channel seems very
>>>> slow, likely because like most typical web servers ours have a
>>>> single raided disk available for writing to.
>>>> Quoted below is a suggestion from a previous issue where our poor
>>>> throughput came up, where it turns out that on multiple disks, file
>>>> channel performance is great.
>>>> On 06/27/2012 11:01 AM, Mike Percy wrote:
>>>>> We are able to push > 8000 events/sec (2KB per event) through a single file channel if you put checkpoint on one disk and use 2 other disks for data dirs. Not sure what the limit is. This is using the latest trunk code. Other limitations may be you need to add additional sinks to your channel to drain it faster. This is because sinks are single threaded and sources are multithreaded.
>>>> For the case where the disks happen to be available on the server,
>>>> that's fantastic, but I suspect that most use cases are going to be
>>>> similar to ours, where multiple disks are not available. Our use
>>>> case isn't unusual as it's primarily aggregating logs from various
>>>> We originally ran our log servers with a exec(tail)->file->avro
>>>> setup where throughput was very bad(80mb in an hour). We then
>>>> switched this to a memory channel which was fine(the peak time 500mb
>>>> worth of hourly logs went through). Afterwards we switched back to
>>>> the file channel, but with 5 identical avro sinks. This did not
>>>> improve throughput(still 80mb). RecoverableMemoryChannel showed very
>>>> similar characteristics.
>>>> I presume this is due to the writes going to two separate places,
>>>> and being further compounded by also writing out and tailing the
>>>> normal web logs: checking top and iostat, we could confirm we have
>>>> significant iowait time, far more than we have during typical
>>>> As it is, we seem to be more or less guaranteeing no loss of logs
>>>> with the file channel. Perhaps we could look into batching
>>>> puts/takes for those that do not need 100% data retention but want
>>>> more reliability than with the MemoryChannel which can potentially
>>>> lose the entire capacity on a restart? Another possibility is
>>>> writing an implementation that writes primarily sequentially. I've
>>>> been meaning to get a deeper look at the implementation itself to