我的站点

一个系统软件工程师的随手涂鸦

Month: 五月 2015

使用Intellij搭建Scala开发环境

在网上找到使用Intellij搭建Scala开发环境的官方文档,发现老的已经掉牙。索性自己写了一篇:Getting Started with Scala in IntelliJ IDEA 14.1,以给需要的朋友一个参考。

搭建Scala开发环境

本文以CentOS 7为例,介绍如何搭建Scala开发环境:

(1)安装Scala :
执行“yum install scala”命令:

[root@localhost ~]# yum install scala
Loaded plugins: fastestmirror
Loading mirror speeds from cached hostfile
 * base: centos.mirrors.tds.net
 * extras: bay.uchicago.edu
 * updates: dallas.tx.mirror.xygenhosting.com
Nothing to do

提示找不到Scala安装包,所以采用另外方式。使用wget命令直接下载:

[root@localhost ~]# wget http://downloads.typesafe.com/scala/2.11.6/scala-2.11.6.rpm
--2015-05-27 22:07:32--  http://downloads.typesafe.com/scala/2.11.6/scala-2.11.6.rpm
......
Length: 111919675 (107M) [application/octet-stream]
Saving to: ‘scala-2.11.6.rpm’

100%[=========================================================================>] 111,919,675  298KB/s   in 6m 15s

2015-05-27 22:13:48 (291 KB/s) - ‘scala-2.11.6.rpm’ saved [111919675/111919675]

接下来安装Scala

[root@localhost ~]# rpm -ivh scala-2.11.6.rpm
Preparing...                          ################################# [100%]
Updating / installing...
   1:scala-2.11.6-0                   ################################# [100%]

安装成功,执行Scala

[root@localhost ~]# scala
/usr/bin/scala: line 23: java: command not found

运行Scala需要JRE支持,所以下一步安装Java环境。

(2)执行yum install java

[root@localhost ~]# yum install java
......
Complete!

(3)运行scala,打印“Hello world!”:

[root@localhost ~]# scala
Welcome to Scala version 2.11.6 (OpenJDK 64-Bit Server VM, Java 1.8.0_45).
Type in expressions to have them evaluated.
Type :help for more information.

scala> print("Hello world!")
Hello world!
scala> :quit

安装成功!

利用Spark API写一个单独的程序

本文参考Spark网站的Self-Contained Applications一节,使用Scala语言开发一个单独的小程序。

(1)首先安装sbt,参考官方文档。我使用的是RPM包格式:

curl https://bintray.com/sbt/rpm/rpm | sudo tee /etc/yum.repos.d/bintray-sbt-rpm.repo
sudo yum install sbt

(2)接下来在/home文件夹下建立一个SparkApp的文件夹,文件夹布局如下:

bash-4.1# find /home/SparkApp/
/home/SparkApp/
/home/SparkApp/simple.sbt
/home/SparkApp/src
/home/SparkApp/src/main
/home/SparkApp/src/main/scala
/home/SparkApp/src/main/scala/SimpleApp.scala

其中simple.sbt文件内容如下所示:

name := "Simple Project"

version := "1.0"

scalaVersion := "2.10.4"

libraryDependencies += "org.apache.spark" %% "spark-core" % "1.3.0"

SimpleApp.scala程序如下:

import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._
import org.apache.spark.SparkConf

object SimpleApp {
  def main(args: Array[String]) {
    val logFile = "file:///usr/local/spark/README.md" // Should be some file on your system
    val conf = new SparkConf().setAppName("Simple Application")
    val sc = new SparkContext(conf)
    val logData = sc.textFile(logFile, 2).cache()
    val numAs = logData.filter(line => line.contains("a")).count()
    val numBs = logData.filter(line => line.contains("b")).count()
    println("Lines with a: %s, Lines with b: %s".format(numAs, numBs))
  }
}

(3)执行sbt package命令打包jar文件:

bash-4.1# sbt package
......
[success] Total time: 89 s, completed May 25, 2015 10:16:51 PM

(4)调用spark-submit脚本执行程序:

bash-4.1# /usr/local/spark/bin/spark-submit --class "SimpleApp" --master local[4] target/scala-2.10/simple-project_2.10-1.0.jar
......
Lines with a: 60, Lines with b: 29

可以看到,输出正确结果。

搭建Spark开发环境

本文使用docker搭建Spark环境,使用的image文件是sequenceiq提供的1.3.0版本

首先pull Spark image文件:

docker pull sequenceiq/spark:1.3.0

pull成功后,运行Spark

docker run -i -t -h sandbox sequenceiq/spark:1.3.0 bash

测试Spark是否工作正常:

bash-4.1# spark-shell --master yarn-client --driver-memory 1g --executor-memory 1g --executor-cores 1
......
scala> sc.parallelize(1 to 1000).count()
......
res0: Long = 1000

输出1000,OK!

(1)启动spark-shell,输出log很多,解决方法如下:
a)把/usr/local/spark/conf文件夹下的log4j.properties.template文件复制生成一份log4j.properties文件:

bash-4.1# cd /usr/local/spark/conf
bash-4.1# cp log4j.properties.template log4j.properties

b)把log4j.properties文件里的“log4j.rootCategory=INFO, console”改成“log4j.rootCategory=WARN, console”即可。

(2)启动spark-shell会有以下warning

15/05/25 04:49:28 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable

提示找不到hadoop的库文件,解决办法如下:

export LD_LIBRARY_PATH=/usr/local/hadoop/lib/native/:$LD_LIBRARY_PATH

请参考stackoverflow的相关讨论:
a)Hadoop “Unable to load native-hadoop library for your platform” error on CentOS
b)Hadoop “Unable to load native-hadoop library for your platform” error on docker-spark?

(3)在Quick Start中提到如下例子:

scala> val textFile = sc.textFile("README.md")
......
scala> textFile.count() // Number of items in this RDD

执行会有错误:

scala> textFile.count()
org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: hdfs://sandbox:9000/user/root/README.md
        at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:285)
        at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:228)
        at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:304)
        at org.apache.spark.rdd.HadoopRDD.getPartitions(HadoopRDD.scala:203)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:219)
        at org.apache.spark.rdd.RDD$$anonfun$partitions$2.apply(RDD.scala:217)
        at scala.Option.getOrElse(Option.scala:120)
        at org.apache.spark.rdd.RDD.partitions(RDD.scala:217)

可以看到程序尝试从hdfs中寻找文件,所以报错。

解决方法有两种:
a) 指定本地文件系统:

scala> val textFile = sc.textFile("file:///usr/local/spark/README.md")
textFile: org.apache.spark.rdd.RDD[String] = file:///usr/local/spark/README.md MapPartitionsRDD[3] at textFile at <console>:21

scala> textFile.count()
res1: Long = 98

b)上传文件到hdfs上:

bash-4.1# hadoop fs -put /usr/local/spark/README.md README.md

接着运行spark-shell:

bash-4.1# spark-shell --master yarn-client --driver-memory 1g --executor-memory 1g --executor-cores 1
Spark assembly has been built with Hive, including Datanucleus jars on classpath
Welcome to
      ____              __
     / __/__  ___ _____/ /__
    _\ \/ _ \/ _ `/ __/  '_/
   /___/ .__/\_,_/_/ /_/\_\   version 1.3.0
      /_/

Using Scala version 2.10.4 (Java HotSpot(TM) 64-Bit Server VM, Java 1.7.0_51)
Type in expressions to have them evaluated.
Type :help for more information.
15/05/25 05:22:15 WARN Client: SPARK_JAR detected in the system environment. This variable has been deprecated in favor of the spark.yarn.jar configuration variable.
15/05/25 05:22:15 WARN Client: SPARK_JAR detected in the system environment. This variable has been deprecated in favor of the spark.yarn.jar configuration variable.
Spark context available as sc.
SQL context available as sqlContext.

scala> val textFile = sc.textFile("README.md")
textFile: org.apache.spark.rdd.RDD[String] = README.md MapPartitionsRDD[1] at textFile at <console>:21

scala> textFile.count()
res0: Long = 98

参考邮件:
Spark Quick Start – call to open README.md needs explicit fs prefix

P.S.在主机(非docker环境)下载sparkhttps://spark.apache.org/downloads.html)运行时,会有以下warning

log4j:WARN No appenders could be found for logger (org.apache.hadoop.metrics2.lib.MutableMetricsFactory).
log4j:WARN Please initialize the log4j system properly.
log4j:WARN See http://logging.apache.org/log4j/1.2/faq.html#noconfig for more info.

解决办法是把/path/to/spark/conf文件夹下的log4j.properties.template文件复制生成一份log4j.properties文件即可。

参考stackoverflow的讨论:
log4j:WARN No appenders could be found for logger (running jar file, not web app)

不要招聘“性价比”高的工程师

以前在论坛看到一个帖子,发帖者抱怨自己招不到“性价比”高的工程师。当时没想什么,不过我后来仔细琢磨一下,感觉有点奇怪。为什么一个公司非要招聘“性价比”高的工程师呢?

所谓“性价比”,顾名思义,就是“性能”和“价格”的比值。“性能”越高,“价格”越低,性价比就越高。如果一个人每月工资是5000元,但他每个月为公司创造的价值相当于工资是800010000元的人创造的,那么这个人“性价比”就很高了。但是且慢,这样是不是对这个人不公平呢?当然,人就应该拿到和他能力匹配的工资。为什么公司非要招聘“性价比”高的工程师呢?“性价比”是1,或者性能和价格匹配就好了。谁都不是傻子,都知道自己有几斤几两。当他发现工资与自己的能力和价值相差太远时,或是降低工作效率,或是准备拍屁股走人,这样对公司有什么好处呢?开始以为招聘“性价比”高的工程师占了便宜,其实长远来看,还是吃亏的。据说有些公司还把招聘时压价格作为对招聘者的一个考评指标,想想真是可笑。 

不要考虑招聘“性价比”高的工程师的了,招聘一个“性价比”合适的工程师。

docker笔记(4)—— 如何进入一个正在运行的“docker container”?

docker attach [container-id]”命令有时会hang住,执行Ctrl+C命令也不起作用:

[root@localhost ~]# docker attach a972e69ab444
^C^C^C^C^C^C^C^C^C^C

使用pstack命令查看函数调用栈:

[root@localhost ~]# pstack 29744
Thread 5 (Thread 0x7f9079bd8700 (LWP 29745)):
#0  runtime.futex () at /usr/lib/golang/src/pkg/runtime/sys_linux_amd64.s:269
#1  0x0000000000417717 in runtime.futexsleep () at /usr/lib/golang/src/pkg/runtime/os_linux.c:49
#2  0x0000000001161c58 in runtime.sched ()
#3  0x0000000000000000 in ?? ()
Thread 4 (Thread 0x7f90792d7700 (LWP 29746)):
#0  runtime.futex () at /usr/lib/golang/src/pkg/runtime/sys_linux_amd64.s:269
#1  0x0000000000417782 in runtime.futexsleep () at /usr/lib/golang/src/pkg/runtime/os_linux.c:55
#2  0x00007f907b830f60 in ?? ()
#3  0x0000000000000000 in ?? ()
Thread 3 (Thread 0x7f9078ad6700 (LWP 29747)):
#0  runtime.futex () at /usr/lib/golang/src/pkg/runtime/sys_linux_amd64.s:269
#1  0x0000000000417717 in runtime.futexsleep () at /usr/lib/golang/src/pkg/runtime/os_linux.c:49
#2  0x00000000011618a0 in text/template.zero ()
#3  0x0000000000000000 in ?? ()
Thread 2 (Thread 0x7f9073fff700 (LWP 29748)):
#0  runtime.futex () at /usr/lib/golang/src/pkg/runtime/sys_linux_amd64.s:269
#1  0x0000000000417717 in runtime.futexsleep () at /usr/lib/golang/src/pkg/runtime/os_linux.c:49
#2  0x000000c2080952f0 in ?? ()
#3  0x0000000000000000 in ?? ()
Thread 1 (Thread 0x7f907b9e1800 (LWP 29744)):
#0  runtime.epollwait () at /usr/lib/golang/src/pkg/runtime/sys_linux_amd64.s:385
#1  0x00000000004175dd in runtime.netpoll () at /usr/lib/golang/src/pkg/runtime/netpoll_epoll.c:78
#2  0x00007fff00000004 in ?? ()
#3  0x00007fff58720fd0 in ?? ()
#4  0xffffffff00000080 in ?? ()
#5  0x0000000000000000 in ?? ()

可以使用“docker exec -it [container-id] bash”命令进入正在运行的container

[root@localhost ~]# docker exec -it a972e69ab444 bash
bash-4.1# ls
bin   dev  home  lib64  mnt  pam-1.1.1-17.el6.src.rpm  root      sbin     srv  tmp  var
boot  etc  lib   media  opt  proc                      rpmbuild  selinux  sys  usr
bash-4.1#

docker attach相当于复用了container当前使用的tty,因此在docker attach内执行exit,会导致正在运行的container退出。而docker exec会新建立一个tty,在docker exec中执行exit不会导致container退出。

 

参考资料:
(1)Docker – Enter Running Container with new TTY

如何杀死一个已经detached的screen会话?

如果想杀死一个已经detachedscreen会话,可以使用以下命令:

screen -X -S [session # you want to kill] quit

举例如下:

[root@localhost ~]# screen -ls
There are screens on:
        9975.pts-0.localhost    (Detached)
        4588.pts-3.localhost    (Detached)
2 Sockets in /var/run/screen/S-root.

[root@localhost ~]# screen -X -S 4588 quit
[root@localhost ~]# screen -ls
There is a screen on:
        9975.pts-0.localhost    (Detached)
1 Socket in /var/run/screen/S-root.

可以看到,4588会话已经没有了。

参考资料:
(1)Kill detached screen session

《若为自由故》读后感

整整花了一个月的周末时间,阅读了RMS自传的中文版《若为自由故》。这本书也是在上次RMS访华时的活动上买的,它这讲述了RMS个人以及他所领导的GNU运动的成长经历,时间跨度从上世纪50年代一直到本世纪初左右。我本人很尊敬RMS先生,他那种不妥协,近乎偏执的精神在现代人看来似乎有些迂腐,但也正是这一点使他得到了别人的认可和尊敬。此外,我也有些羡慕RMS的生活,因为他会在全世界各地不停地游走和演讲,而“边旅行边工作”也是我向往的生活状态。
RMS所提倡的“自由软件”运动远远超出了计算机领域本身,而更是一场关乎人类自由的政治运动。其实支持RMS也很容易,最简单的办法就是请用GNU/Linux(发音:GNU plus Linux)来代替Linux就好了。如果想了解RMS,我推荐可以读一读这本书,或者找到它的英文版,它会告诉你一个真实的RMS

docker笔记(3)—— selinux导致docker工作不正常

最近几天在研究docker备份文件(操作系统是RHEL7docker版本是1.5.0)。仿照docker文档,执行如下命令:

[root@localhost data]#docker create -v /dbdata --name dbdata training/postgres /bin/true
[root@localhost data]#docker run -d --volumes-from dbdata --name db1 training/postgres
[root@localhost data]# docker run --volumes-from dbdata -v $(pwd):/backup ubuntu tar cvf /backup/backup.tar /dbdata
tar: /backup/backup.tar: Cannot open: Permission denied
tar: Error is not recoverable: exiting now

看到Permission denied这个提示,自然首先怀疑用户没有写权限的问题。检查一下当前目录的权限:

[root@localhost data]# ls -alt
total 4
drwxrwxrwx.  2 root root    6 May  7 21:33 .
drwxrwx-w-. 15 root root 4096 May  7 21:33 ..

应该是没问题的。经过在stackoverflow上的一番讨论,得到的建议是有可能是selinux捣的鬼。查看了一下selinux状态:

[root@localhost root]# sestatus
SELinux status:                 enabled
SELinuxfs mount:                /sys/fs/selinux
SELinux root directory:         /etc/selinux
Loaded policy name:             targeted
Current mode:                   enforcing
Mode from config file:          enforcing
Policy MLS status:              enabled
Policy deny_unknown status:     allowed
Max kernel policy version:      28

果断把模式改为permissive:

[root@localhost data]# setenforce 0
[root@localhost data]# sestatus
SELinux status:                 enabled
SELinuxfs mount:                /sys/fs/selinux
SELinux root directory:         /etc/selinux
Loaded policy name:             targeted
Current mode:                   permissive
Mode from config file:          enforcing
Policy MLS status:              enabled
Policy deny_unknown status:     allowed
Max kernel policy version:      28

马上工作正常:

[root@localhost data]# docker run --volumes-from dbdata -v $(pwd):/backup ubuntu tar cvf /backup/backup.tar /dbdata
tar: Removing leading `/' from member names
/dbdata/

因为时间原因,没有往下深究。总之,在使用docker时,要留意一下selinux,有可能会引起很奇怪的问题。

更新:

最近又碰到这个问题,可以参考这篇总结

参考资料:
(1)Why does docker prompt “Permission denied” when backing up the data volume?
(2)How to disable SELinux without restart?
(3)Quick-Tip: Turning off or disabling SELinux

“五一”逛市场随笔

“五一”小长假没有离开北京。一是时间短,车票不好买;二是哪里都是人,看着就很烦。

昨天去了赵公口附近的一个服装批发市场,算起来应该是连续三年小长假来这里了。尽管现在电商网购已经占据了大量的消费市场,但我发现这里还是人来人往,车水马龙,不像有些商城已经变得门可罗雀。坦率地讲,这里有些工厂店,还是很实惠的,可以买到性价比不错的衣服。我前年在这里买的两件运动T恤,质量相当好,穿到今年还没破。

我想互联网电商给大家带来便利的同时,可能也剥夺了人们逛商场淘宝的乐趣了。花几个小时,逛逛商场,既能够锻炼身体,又有淘宝的乐趣。岂不很好?

Powered by WordPress & Theme by Anders Norén