n wherein I train the model using a
>>>>>> receiver input
>>>>>> stream in 4 sec batches
>>>>>>
>>>>>> val stream = ssc.receiverStream(receiver) //receiver gets new
am = ssc.receiverStream(receiver) //receiver gets new data
>>>>> every
>>>>> batch
>>>>> model.trainOn(stream.map(Vectors.parse))
>>>>> If I use
>>>>> model.latestModel.clusterCenters.foreach(println)
>>>>>
>>>
tion (when the streaming app started)
>>>>
>>>> when I use the model to predict cluster assignment with a labeled input
>>>> the
>>>> assignments change over time as expected
>>>>
>>>> testData.transform {rdd =>
>
)
>>>
>>> when I use the model to predict cluster assignment with a labeled input
>>> the
>>> assignments change over time as expected
>>>
>>> testData.transform {rdd =>
>>> rdd.map(lp => (lp.label,
>&
e over time as expected
>>
>> testData.transform {rdd =>
>> rdd.map(lp => (lp.label,
>> model.latestModel().predict(lp.features)))
>> }.print()
>>
>>
>>
>>
>>
>>
>>
>>
&
>
>
>
>
>
>
>
>
> --
> View this message in context:
> http://apache-spark-user-list.1001560.n3.nabble.com/StreamingKMeans-does-not-update-cluster-centroid-locations-tp26275.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
> --
(lp => (lp.label, model.latestModel().predict(lp.features)))
}.print()
--
View this message in context:
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