Running spark examples on Cloudera VM 5.7 and
<p>I am learning hadoop, machine learning and spark. I have downloaded Cloudera 5.7 Quick Start VM. I have also downloaded the examples from <a href="https://github.com/apache/spark" rel="nofollow">https://github.com/apache/spark</a> as  a zip file and copied them to the Cloudera VM. I have a challenge running the machine learning and any examples from  <a href="https://github.com/apache/spark" rel="nofollow">https://github.com/apache/spark</a>. I tried running the simple word count example but failed. Below are my steps and the error  i get</p>

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

<p>All examples I try to run fail with the below error.</p>

<p>Traceback (most recent call last):
  File "/home/cloudera/training/spark-master/examples/src/main/python/ml/word2vec_example.py", line 23, in 
    from pyspark.sql import SparkSession</p>

<p>I did a search for the file pyspark.sql  but I could only find the below file
cd /spark-master
find . -name <em>pyspark.sql</em>
./python/docs/pyspark.sql.rst</p>

<p>Please advise on how i can resolve these errors so that i can run this example in order speed up my machine learning and big data.</p>

<p>the code for the word count example is below</p>

<p>cat word2vec_example.py</p>

<pre><code>#
# 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()
</code></pre>