The concurrency is fine. Should be easy for it to handle. Are you using
tags?

On Fri, Jan 27, 2017 at 10:39 AM, Jeffery K <
jeffery.k...@sightlinesystems.com> wrote:

> I checked the schema of one of the measurements (they should all be the
> same as we're inserting the same data into multiple measurements).
> There are 74 field keys. All float type. the field key names are just
> strings, some with spaces, and sometimes characters like % or parenthesis.
> (). But we've done the proper escaping to do the insert into influx
> correctly. The line feed protocol is correct as far as I know, since it's
> accepted, and the fields & data look correct.
> We are using a separate thread for each of the 230 (want to get to 1000,
> but only got this many) measurements for doing the insert. Is there a
> problem with this level of concurrency with influx? to elaborate, for each
> measurement, our client is creating a http writer (in java) and feeding in
> a batch of writes that have been read and put into line feed protocol in
> the last 100ms (we initially had this at 500ms, but to reduce load to
> influx, lowered it). After each batch "commit", we re-create the http
> connection, for the next batch insert.
>
> I initially had problems testing on the newer influx 1.2 since it seems
> the json of returns has changed to have a statement_id, and my jackson
> converter to java object didn't like that, but I've since fixed that and
> re-tested this scenario with Influx 1.2, and it behaves the same way. gets
> killed very quickly by the OOM killer, using around 22GB of RAM.
>
>
>
> On Friday, January 27, 2017 at 10:06:04 AM UTC-5, Paul Dix wrote:
>>
>> My guess is there's an issue with your schema. What does the data look
>> like?
>>
>> On Thu, Jan 26, 2017 at 6:34 PM, Jeffery K <jeffer...@sightlinesystems.
>> com> wrote:
>>
>>> We are using http to write inserts to the /write endpoint and after a
>>> very short duration, influx is being kill by the linux OS for out of
>>> memory.
>>> We've increased the memory 4 fold from the initial value, and influx now
>>> has 20GB, but still it is crashing fairly quickly. We are performing about
>>> only 230,000 inserts. 1000 inserts into 230 measurements. We are using
>>> batching and flushing every 100 milliseconds.
>>>
>>> We don't believe the data is more than 1GB, but yet, 20 GB of memory
>>> isn't enough to write this?!
>>>
>>> This was done with 1.1.0 version.
>>>
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