我尝试运行文档中给出的非常简单的Word2Vec示例，文档链接如下：

https://spark.apache.org/docs/1.4.1/api/python/_modules/pyspark/ml/feature.html#Word2Vec

from pyspark import SparkContext, SQLContextfrom pyspark.mllib.feature import Word2VecsqlContext = SQLContext(sc)sent = ("a b " * 100 + "a c " * 10).split(" ")doc = sqlContext.createDataFrame([(sent,), (sent,)], ["sentence"])model = Word2Vec(vectorSize=5, seed=42, inputCol="sentence", outputCol="model").fit(doc)model.getVectors().show()model.findSynonyms("a", 2).show()

TypeError                                 Traceback (most recent call last)<ipython-input-4-e57e9f694961> in <module>()      5 sent = ("a b " * 100 + "a c " * 10).split(" ")      6 doc = sqlContext.createDataFrame([(sent,), (sent,)], ["sentence"])----> 7 model = Word2Vec(vectorSize=5, seed=42, inputCol="sentence", outputCol="model").fit(doc)      8 model.getVectors().show()      9 model.findSynonyms("a", 2).show()TypeError: __init__() got an unexpected keyword argument 'vectorSize'

为什么会失败，有什么想法吗？

回答：

您参考的是ml包的文档，但却从mllib包中导入。在mllib中，Word2Vec的__init__方法不接受任何参数。
您是否意图使用以下导入方式：

from pyspark.ml.feature import Word2Vec

输出结果如下：

+----+--------------------+|word|              vector|+----+--------------------+|   a|[-0.3511952459812...||   b|[0.29077222943305...||   c|[0.02315592765808...|+----+--------------------++----+-------------------+|word|         similarity|+----+-------------------+|   b|0.29255685145799626||   c|-0.5414068302988307|+----+-------------------+