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我正在学习 hadoop、机器学习和 spark。我已经下载了 Cloudera 5.7 快速启动 VM。我还从https://github.com/apache/spark下载了示例作为 zip 文件并将它们复制到 Cloudera VM。我在运行机器学习和 https://github.com/apache/spark中的任何示例时遇到了挑战。我尝试运行简单的字数统计示例，但失败了。以下是我的步骤和我得到的错误

[cloudera@quickstart.cloudera] cd /spark-master/examples/src/main/python/ml [cloudera@quickstart.cloudera] spark-submit word2vec_example.py

我尝试运行的所有示例都失败并出现以下错误。

Traceback（最近一次调用最后一次）：文件“/home/cloudera/training/spark-master/examples/src/main/python/ml/word2vec_example.py”，第 23 行，从 pyspark.sql 导入 SparkSession

我搜索了文件 pyspark.sql 但我只能找到以下文件 cd /spark-master find 。-name pyspark.sql ./python/docs/pyspark.sql.rst

请告知我如何解决这些错误，以便我可以运行此示例以加速我的机器学习和大数据。

字数统计示例的代码如下

猫 word2vec_example.py

#
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#

from __future__ import print_function

# $example on$
from pyspark.ml.feature import Word2Vec
# $example off$
from pyspark.sql import SparkSession

if __name__ == "__main__":
    spark = SparkSession\
        .builder\
        .appName("Word2VecExample")\
        .getOrCreate()

    # $example on$
    # Input data: Each row is a bag of words from a sentence or document.
    documentDF = spark.createDataFrame([
        ("Hi I heard about Spark".split(" "), ),
        ("I wish Java could use case classes".split(" "), ),
        ("Logistic regression models are neat".split(" "), )
    ], ["text"])
    # Learn a mapping from words to Vectors.
    word2Vec = Word2Vec(vectorSize=3, minCount=0, inputCol="text", outputCol="result")
    model = word2Vec.fit(documentDF)
    result = model.transform(documentDF)
    for feature in result.select("result").take(3):
        print(feature)
    # $example off$

    spark.stop()
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1 回答 1

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第 23 行：spark = SparkSession\

SparkSession 是 Spark 2.0 中的新功能，Cloudera 默认只附带 Spark 1.6。您可以从 Spark 1.6 下载示例或在 Cloudera 上安装 Spark 2.0。

于 2016-12-21T11:36:55.430 回答