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kmeansをpysparkでストリーミングするときは、ローカルディレクトリからの読み方に助けが必要です。このトピックには良い答えはここstackoverflowのローカルディレクトリからの読み込み方法、kmeans streaming pyspark
ではありません私のコードは
if __name__ == "__main__":
ssc = StreamingContext(sc, 1)
training_data_raw, training_data_df = prepare_data(TRAINING_DATA_SET)
trainingData = parse2(training_data_raw)
testing_data_raw, testing_data_df = prepare_data(TEST_DATA_SET)
testingData = testing_data_raw.map(parse1)
#print(testingData)
trainingQueue = [trainingData]
testingQueue = [testingData]
trainingStream = ssc.queueStream(trainingQueue)
testingStream = ssc.queueStream(testingQueue)
# We create a model with random clusters and specify the number of clusters to find
model = StreamingKMeans(k=2, decayFactor=1.0).setRandomCenters(3, 1.0, 0)
# Now register the streams for training and testing and start the job,
# printing the predicted cluster assignments on new data points as they arrive.
model.trainOn(trainingStream)
result = model.predictOnValues(testingStream.map(lambda lp: (lp.label, lp.features)))
result.pprint()
ssc.textFileStream('file:///Users/userrname/PycharmProjects/MLtest/training/data/')
ssc.start()
ssc.awaitTermination()
感謝です!試験例について