如何从本地目录中读取，kmeans 流式传输 pyspark答案

【问题标题】：How to read from local directory, kmeans streaming pyspark如何从本地目录中读取，kmeans 流式传输 pyspark
【发布时间】：2017-11-02 04:28:47
【问题描述】：

在使用 pyspark 运行 kmeans 流式传输时，我需要从本地目录读取的帮助。 stackoverflow上没有关于这个话题的好答案

这是我的代码

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()

谢谢！！

【问题讨论】：

标签： python stream streaming pyspark k-means

【解决方案1】：

from pyspark.mllib.linalg import Vectors
trainingData = ssc.textFileStream("/training/data/dir").map(Vectors.parse)

用于测试示例

from pyspark.mllib.regression import LabeledPoint
def parse(lp):
    label = float(lp[lp.find('(') + 1: lp.find(',')])
    vec = Vectors.dense(lp[lp.find('[') + 1: lp.find(']')].split(','))
    return LabeledPoint(label, vec)
testData = ssc.textFileStream("/testing/data/dir").map(parse)

【讨论】：