参考：配置本地单机pyspark
https://www.cnblogs.com/jackchen-Net/p/6667205.html#_label3
在sitepackages下新建pyspark.pth 文件，并添加D:\apps\spark\spark-2.2.1-bin-hadoop2.7\python
submit一个py文件报错
ERROR Shell: Failed to locate the winutils binary in the hadoop binary path
说明没有hadoop执行文件，因为我们并没安装hadoop：
另外参考此篇hadoop安装（记住，仅仅是hadoop）
http://blog.csdn.net/yaoqiwaimai/article/details/59114881
winutils.exe chmod 777 c:\tmp\hive（先创建文件夹后再执行）
后面不要执行spark-shell(这是基于scala的，我们目的是pyspark)
winutils.exe版本不对(现在版本hadoop2.7.3)，重新下载（需要的话留下你的email）。hadoop.dll-and-winutils.exe-for-hadoop2.7.3-on-windows_X64-master.zip解压并将所有子文件复制到hadoop的bin文件夹中
再次提交脚本还是error：
Py4JJavaError: An error occurred while calling z:org.apache.spark.api.python.PythonRDD.collectAndServe.
将自己jdk9改为jdk8就没有问题了（自己坑自己）
警示信息太多：spark home的conf文件中logXXX复制，去掉.template，修改log4j.rootCategory=WARN, console 这里INFO改为WARN
submit的测试脚本
# encoding: utf-8
import os
import sys
# os.environ['SPARK_HOME'] = r"D:\apps\spark\spark-2.2.1-bin-hadoop2.7"
# os.environ['HADOOP_HOME'] = r"D:\apps\spark\"
# You might need to enter your local IP
# os.environ['SPARK_LOCAL_IP']="192.168.2.138"
# Path for pyspark and py4j
sys.path.append(r"D:\apps\spark\spark-2.2.1-bin-hadoop2.7\python")
# sys.path.append(r"D:\apps\spark\spark-2.2.1-bin-hadoop2.7\python\lib\py4j-0.10.4-src.zip") #pip install py4j后即可不要这句
try:
from pyspark import SparkContext
from pyspark import SparkConf
print ("Successfully imported Spark Modules")
except ImportError as e:
print ("Can not import Spark Modules", e)
sys.exit(1)
sc = SparkContext(master='local')
words = sc.parallelize(["scala", "java", "hadoop", "spark", "akka"])
print("统计结果", words.count())
