Question

我试图在Apache Spark＆＃39; MLlib website上运行该示例。以下是我的代码：

import sys
import os

os.environ['SPARK_HOME'] = "/usr/local/Cellar/apache-spark/1.2.1"
sys.path.append("/usr/local/Cellar/apache-spark/1.2.1/libexec/python")
sys.path.append("/usr/local/Cellar/apache-spark/1.2.1/libexec/python/build")

try:
    from pyspark import SparkContext, SparkConf
    from pyspark.mllib.recommendation import ALS, MatrixFactorizationModel, Rating
    print ("Apache-Spark v1.2.1 >>> All modules found and imported successfully.")

except ImportError as e:
    print ("Couldn't import Spark Modules", e)
    sys.exit(1)

# SETTING CONFIGURATION PARAMETERS
config = (SparkConf()
        .setMaster("local")
        .setAppName("Music Recommender")
        .set("spark.executor.memory", "16G")
        .set("spark.driver.memory", "16G")
        .set("spark.executor.cores", "8"))
sc = SparkContext(conf=config)

# Load and parse the data
data = sc.textFile("data/1aa")
ratings = data.map(lambda l: l.split('\t')).map(lambda l: Rating(int(l[0]), int(l[1]), float(l[2])))

# Build the recommendation model using Alternating Least Squares
rank = 10
numIterations = 10
model = ALS.train(ratings, rank, numIterations)

# Evaluate the model on training data
testdata = ratings.map(lambda p: (p[0], p[1]))
predictions = model.predictAll(testdata).map(lambda r: ((r[0], r[1]), r[2]))
ratesAndPreds = ratings.map(lambda r: ((r[0], r[1]), r[2])).join(predictions)
MSE = ratesAndPreds.map(lambda r: (r[1][0] - r[1][1])**2).mean()
print("Mean Squared Error = " + str(MSE))

# Save and load model
model.save(sc, "/Users/kunal/Developer/MusicRecommender")
sameModel = MatrixFactorizationModel.load(sc, "/Users/kunal/Developer/MusicRecommender/data")

代码一直运行直到打印MSE。最后一步是将模型保存到目录中。我收到错误'MatrixFactorizationModel' object has no attribute 'save'（我已经粘贴了日志的最后几行）：

15/10/06 21:00:16 INFO DAGScheduler: Stage 200 (mean at /Users/kunal/Developer/MusicRecommender/collabfiltering.py:41) finished in 12.875 s
15/10/06 21:00:16 INFO DAGScheduler: Job 8 finished: mean at /Users/kunal/Developer/MusicRecommender/collabfiltering.py:41, took 53.290203 s
Mean Squared Error = 405.148403002
Traceback (most recent call last):
  File "/Users/kunal/Developer/MusicRecommender/collabfiltering.py", line 47, in <module>
    model.save(sc, path)
AttributeError: 'MatrixFactorizationModel' object has no attribute 'save'

Process finished with exit code 1

我已经重新安装并确保我拥有最新版本的Spark，但这并没有帮助它。我只在一个10MB的文件上运行它，这是较大文件的一小部分。

操作系统：OSX 10.11.1 Beta（15B22c）

Answer 1

之所以发生这种情况，是因为您使用Spark 1.2.1并在Spark 1.3.0中引入了Dim csvFilePath As String = "C:\Test.csv" 'Path to create or existing file Dim outFile As IO.StreamWriter = My.Computer.FileSystem.OpenTextFileWriter(csvFilePath, False) outFile.WriteLine("Field1, Field2") outFile.WriteLine("1, 2") outFile.WriteLine("3, 3") outFile.Close() Console.WriteLine(My.Computer.FileSystem.ReadAllText(csvFilePath))方法。此外，您使用的文档涵盖了当前版本（1.5.1）。

Spark文档网址如下所示：

MatrixFactorizationModel.save

所以在你的情况下你应该使用：

http://spark.apache.org/docs/SPARK_VERSION/some_topic.html

AttributeError：＆＃39; MatrixFactorizationModel＆＃39;对象没有属性＆＃39; save＆＃39;

1 个答案: