I stopped the two data nodes and it had no effect.

Thanks,

On Wed, Mar 15, 2023 at 6:53 PM Vincent Russell <vincent.russ...@gmail.com>
wrote:

> Yes.  We have the hdfs rack-aware set up to divide the blocks equally.
> And according to the name node http page it doesn't look like those nodes
> have a much higher number of blocks that nother nodes.
>
> I can try temporarily shutting down one of the data nodes to see what that
> does.
>
> We did already lose a node on the cluster a few days ago.  I'm currently
> waiting for the system administrators to replace a disk.
>
> Thanks,
>
> On Wed, Mar 15, 2023 at 5:59 PM Dave Marion <dmario...@gmail.com> wrote:
>
>> sounds like you have a hot-spot on those two datanode hosts. Either
>> because
>> the blocks that it's writing to are all (or a majority) located there, or
>> there is some type of issue with the host. Stopping the DN processes on
>> those two hosts should confirm this, unless the hot spot moves. Do you
>> have
>> the HDFS rack script set up appropriately to distribute the blocks for
>> files across the hosts?
>>
>> On Wed, Mar 15, 2023 at 5:52 PM Vincent Russell <
>> vincent.russ...@gmail.com>
>> wrote:
>>
>> > Hello,
>> >
>> > I am using accumulo 2.0.1 with hadoop 3.3.1.
>> >
>> > I have two identical clusters with 28 tservers.
>> >
>> > I have writers on both clusters which are set with 10 batch writers
>> with a
>> > max memory of 50m.
>> >
>> > However, one server is ingesting 10x faster than the other.
>> >
>> > Is there anything I should check for?
>> >
>> > I don't see any errors, but one thing that I noticed is that the slow
>> site
>> > has a lot of "Slow sync cost" info log messages from the tservers.
>> >
>> > I see these messages on the fast cluster as well, but they are far less.
>> > It also appears that on the slow cluster these messages are occurring on
>> > only two of the nodes in the cluster, where these messages appear to be
>> > more spread out on the fast cluster.
>> >
>> > Thank you in advance for your help,
>> > Vincent
>> >
>>
>

Reply via email to