Very interesting approach. Thanks for sharing it!

On Thu, Jan 8, 2015 at 5:30 PM, Enno Shioji <eshi...@gmail.com> wrote:

> FYI I found this approach by Ooyala.
>
> /** Instrumentation for Spark based on accumulators.
>   *
>   * Usage:
>   * val instrumentation = new SparkInstrumentation("example.metrics")
>   * val numReqs = sc.accumulator(0L)
>   * instrumentation.source.registerDailyAccumulator(numReqs, "numReqs")
>   * instrumentation.register()
>   *
>   * Will create and report the following metrics:
>   * - Gauge with total number of requests (daily)
>   * - Meter with rate of requests
>   *
>   * @param prefix prefix for all metrics that will be reported by this 
> Instrumentation
>   */
>
> https://gist.github.com/ibuenros/9b94736c2bad2f4b8e23
> ᐧ
>
> On Mon, Jan 5, 2015 at 2:56 PM, Enno Shioji <eshi...@gmail.com> wrote:
>
>> Hi Gerard,
>>
>> Thanks for the answer! I had a good look at it, but I couldn't figure out
>> whether one can use that to emit metrics from your application code.
>>
>> Suppose I wanted to monitor the rate of bytes I produce, like so:
>>
>>     stream
>>         .map { input =>
>>           val bytes = produce(input)
>>           // metricRegistry.meter("some.metrics").mark(bytes.length)
>>           bytes
>>         }
>>         .saveAsTextFile("text")
>>
>> Is there a way to achieve this with the MetricSystem?
>>
>>
>> ᐧ
>>
>> On Mon, Jan 5, 2015 at 10:24 AM, Gerard Maas <gerard.m...@gmail.com>
>> wrote:
>>
>>> Hi,
>>>
>>> Yes, I managed to create a register custom metrics by creating an
>>>  implementation  of org.apache.spark.metrics.source.Source and
>>> registering it to the metrics subsystem.
>>> Source is [Spark] private, so you need to create it under a org.apache.spark
>>> package. In my case, I'm dealing with Spark Streaming metrics, and I
>>> created my CustomStreamingSource under org.apache.spark.streaming as I
>>> also needed access to some [Streaming] private components.
>>>
>>> Then, you register your new metric Source on the Spark's metric system,
>>> like so:
>>>
>>> SparkEnv.get.metricsSystem.registerSource(customStreamingSource)
>>>
>>> And it will get reported to the metrics Sync active on your system. By
>>> default, you can access them through the metric endpoint:
>>> http://<driver-host>:<ui-port>/metrics/json
>>>
>>> I hope this helps.
>>>
>>> -kr, Gerard.
>>>
>>>
>>>
>>>
>>>
>>>
>>> On Tue, Dec 30, 2014 at 3:32 PM, eshioji <eshi...@gmail.com> wrote:
>>>
>>>> Hi,
>>>>
>>>> Did you find a way to do this / working on this?
>>>> Am trying to find a way to do this as well, but haven't been able to
>>>> find a
>>>> way.
>>>>
>>>>
>>>>
>>>> --
>>>> View this message in context:
>>>> http://apache-spark-developers-list.1001551.n3.nabble.com/Registering-custom-metrics-tp9030p9968.html
>>>> Sent from the Apache Spark Developers List mailing list archive at
>>>> Nabble.com.
>>>>
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>>>>
>>>>
>>>
>>
>

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