spark单机搭建

说明：单机版的Spark的机器上只需要安装Scala和JDK即可，其他诸如Hadoop、Zookeeper之类的东西可以一概不安装

只需下载如下三个包

1.安装jdk

配置环境变量

vim /etc/profile

路径根据自己的解压路径配置

之后将其生效

source    /etc/profile

2安装scala

配置环境变量

同样执行命令source    /etc/profile

3,最后安装spark

同样配置环境变量，执行命令使其生效,ps,path中的$PATH必须要加，否则bash脚本失效

那么现在看spark是否能成功启动

cd之spark的bin目录，执行./bin/spark-shell

则进入scala交互环境,则成功启动

写个python脚本测试下

# _*_ coding:utf-8 _*_
from __future__ import print_function

from pyspark.sql import SparkSession
from pyspark.sql import Row

def json_dataset_example(spark):
    sc = spark.sparkContext

    #读取json串
    path = "/home/hadoop/spark-2.2.0-bin-hadoop2.7/mydemo/employees.json"
    peopleDF = spark.read.json(path)

    peopleDF.printSchema()

    peopleDF.createOrReplaceTempView("employees")

    teenagerNamesDF = spark.sql("SELECT name FROM employees WHERE salary BETWEEN 3500 AND 4500")
    teenagerNamesDF.show()

    #直接字符串
    jsonStrings = ['{"name":"Yin","address":{"city":"Columbus","state":"Ohio"}}']
    otherPeopleRDD = sc.parallelize(jsonStrings)
    otherPeople = spark.read.json(otherPeopleRDD)
    otherPeople.show()

if __name__ == "__main__":
    spark = SparkSession \
        .builder \
        .appName("myPeople demo") \
        .getOrCreate()
    json_dataset_example(spark)
    spark.stop()

提交测试脚本

输出

没毛病,收工