我正在将 CSV 作为 Spark DataFrame 读取并对其执行机器学习操作。我不断收到 Python 序列化 EOFError - 知道为什么吗?我认为这可能是一个内存问题 - 即文件超出了可用 RAM - 但大幅减少 DataFrame 的大小并不能防止 EOF 错误。
玩具代码和错误如下。
#set spark context
conf = SparkConf().setMaster("local").setAppName("MyApp")
sc = SparkContext(conf = conf)
sqlContext = SQLContext(sc)
#read in 500mb csv as DataFrame
df = sqlContext.read.format('com.databricks.spark.csv').options(header='true',
inferschema='true').load('myfile.csv')
#get dataframe into machine learning format
r_formula = RFormula(formula = "outcome ~ .")
mldf = r_formula.fit(df).transform(df)
#fit random forest model
rf = RandomForestClassifier(numTrees = 3, maxDepth = 2)
model = rf.fit(mldf)
result = model.transform(mldf).head()
在单个节点上重复运行上述代码spark-submit
会引发以下错误,即使在拟合模型之前 DataFrame 的大小已减小(例如tinydf = df.sample(False, 0.00001)
:
Traceback (most recent call last):
File "/home/hduser/spark1.6/python/lib/pyspark.zip/pyspark/daemon.py", line 157,
in manager
File "/home/hduser/spark1.6/python/lib/pyspark.zip/pyspark/daemon.py", line 61,
in worker
File "/home/hduser/spark1.6/python/lib/pyspark.zip/pyspark/worker.py", line 136,
in main if read_int(infile) == SpecialLengths.END_OF_STREAM:
File "/home/hduser/spark1.6/python/lib/pyspark.zip/pyspark/serializers.py", line 545,
in read_int
raise EOFError
EOFError