Spark入门--初学者_warn utils:66 - your hostname, hisense.algo1 resol

作者：Monodyee | 2024-05-30 23:16:40

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warn utils:66 - your hostname, hisense.algo1 resolves to a loopback address:

Step1：下载sparkhttp://mirrors.shu.edu.cn/apache/spark/spark-2.3.0/spark-2.3.0-bin-hadoop2.7.tgz
Step2：将下载好的spark通过命令传输到linux环境下(rz命令，最好创建一个file，放到file中 mkdir opt)
Step3：cd /opt中通过命令解压压缩包
```
tar -zxvf spark-2.3.0-bin-hadoop2.7.tgz
```
Step4：cd /etc中，vi profile文件, 将如下代码复制到文件中(注：目录有出处请修改)

#Spark enviroment


export SPARK_HOME=/opt/spark/spark-2.3.0-bin-hadoop2.7/
export PATH="$SPARK_HOME/bin:$PATH"

Step5：在/opt/spark/中新建一个spark_file_test文件夹
```
mkdir spark_file_test
```
Step6：在/opt/spark/spark_file_test中创建一个文件
```
touch hello_spark
```
Step7编辑hello_spark文件，输入一些测试数据


vi hello_spark
hello spark!
hello spark!
hello spark!
hello spark!

Step8：回到cd /opt/spark/spark-2.3.0-bin-hadoop2.7/bin目录中
Step9：输入spark-shell，出现下图中的info表示成功


2018-04-30 09:35:53 WARN  Utils:66 - Your hostname, localhost.localdomain resolves to a loopback address: 127.0.0.1; using 192.168.159.128 instead (on interface eth0)
2018-04-30 09:35:53 WARN  Utils:66 - Set SPARK_LOCAL_IP if you need to bind to another address
2018-04-30 09:35:57 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".Spark context Web UI available at http://192.168.159.128:4040
Spark context available as 'sc' (master = local[*], app id = local-1524847005612).
Spark session available as 'spark'.
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 2.3.0
      /_/
         
Using Scala version 2.11.8 (Java HotSpot(TM) Client VM, Java 1.8.0_171)
Type in expressions to have them evaluated.
Type :help for more information

Step10：读取文件，返回一个RDD


scala> var lines = sc.textFile("../../spark_file_test/hello_spark")
2018-04-27 09:40:53 WARN  SizeEstimator:66 - Failed to check whether UseCompressedOops is set; assuming yes
lines: org.apache.spark.rdd.RDD[String] = ../../spark_file_test/hello_spark MapPartitionsRDD[1] at textFile at <console>:24

Step11：测试，读取文件的行数和第一行的信息


scala> lines.count()
res0: Long = 5                                                                  
 
scala> lines.first
res1: String = Hello Spark!

！！！！！！！！！！！！！！！！！！！！！！！！SUCCESSFUL！！！！！！！！！！！！！！！！！！！！！！！！

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