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Windows Azure Service Bus (2) 队列(Queue)入门

《Windows Azure Platform 系列文章目录》 Service Bus 队列(Queue) Service Bus的Queue非常适合分布式应用。

2017-10-10

Hadoop on Windows with Eclipse -04- Setup SSH daemon

Setup SSH daemon Both Hadoop scripts and Eclipse plug-in need password-less SSH to operate. This section describes how to set it up in the Cygwin environment. Configure ssh daemon Open the Cygwin command prompt. Execute the following command: ssh-host-config When asked if privilege separation should be used, answerno. When asked if sshd should be installed as a service, answeryes. When asked about the value of CYGWIN environment variable, enterntsec. Here is an example session of this command. Note that the input typed by the user is shown in pink and output from the system is shown in gray. Example of using ssh-host-config Start SSH daemon here FindMy Computericon either on your desktop or in the start-up menu, right-click on it and selectManagefrom the context menu. OpenServices and Applicationsin the left-hand panel then select theServicesitem. Find theCYGWIN sshditem in the main section and right-click on it. SelectStartfrom the context menu. Start SSHD service A small window should pop-up indicating the progress of the service start-up. After that window disappears the status of CYGWIN sshd service should change toStarted. Setup authorization keys Eclipse plug-in and Hadoop scripts require ssh authentication to be performed through authorization keys rather than passwords. The following steps describe how authorization keys are set up. here Open cygwin command prompt Execute the following command to generate keys ssh-keygen When prompted for filenames and pass phrases press ENTER to accept default values. After the command has finished generating keys, enter the following command to change into your .ssh directory: cd ~/.ssh Check if the keys were indeed generated by executing the following command: ls -l You should see two filesid_rsa.pubandid_rsawith recent creation dates.These files contain authorization keys. To register the new authorization keys enter the following command (note the sharply-angled double brackets -- they are very important): cat id_rsa.pub >> authorized_keys Setting up authorization keys Now check if the keys were set up correctly by executing the following command: ssh localhost Since it is a new ssh installation, you will be warned that authenticity of the host could not be established and will be asked whether you really want to connect. Answeryesand press ENTER. You should see the Cygwin prompt again, which means that you have successfully connected. Now execute the command again: ssh localhost This time you should not be prompted for anything.

2017-10-09

Hadoop on Windows with Eclipse -06- Unpack Hadoop Installation

Unpack Hadoop Installation The next step is to unpack the downloaded and copied package. here To unpack the package follow these steps: Open a new Cygwin window. After the new Cygwin window appears, execute the following command: tar -xzf hadoop-0.19.1.tar.gz This will start unpacking the Hadoop distribution. After several minutes you should see a new Cygwin prompt again as shown in the screenshot below: When you see the new prompt, execute the following command: ls -l This command will list the contents of your home directory. You should see a newly created directory calledhadoop-0.19.1 Next execute the following commands: cd hadoop-0.19.1 ls -l If you get output similar to the following, everything was unpacked correctly and you can go to the next step.

2017-10-09

Windows phone 应用开发系列教程（更新中）

Windows phone 应用开发[1]-Text To Speech 作为开篇章节.第一篇将在如下介绍一些Windows phone比较有意思的东西-Text To Speech[文本到语音转换

2017-10-09

Hadoop on Windows with Eclipse -03- Set Environment Variables

Set Environment Variables The next step is to set up the PATH environment variable so that Eclipse IDE can access Cygwin commands here To set environment variables follow these steps: Find "My Computer" icon either on the desktop or in the start menu, right-click on it and selectPropertiesitem from the menu. When you see the Properties dialog box, click on theEnvironment Variablesbutton as shown below WhenEnvironment Variablesdialog shows up, click on thePathvariable located in theSystem Variablesbox and then click theEditbutton. WhenEditdialog appears append the following text to the end of theVariable valuefield: ;c:\cygwin64\bin;c:\cygwin64\usr\sbin Note: If you installed cygwin in the non-standard location, correct the above value accordingly. Close all three dialog boxes by pressing OK button of each dialog box.

2017-10-08

.NET Core多平台开发体验[1]: Windows

Windows、Mac OS以及各种Linux Distribution（RHEL、Ubuntu、Debian、Fedora、CentOS和SUSE等）平台上。

2017-10-08

Windows Mobile程序员玩转Android开发

现在的智能手机操作系统已经进入战国时代，老牌的Symbian、Windows Mobile和BREW面临着iPhone和Android等新势力的巨大挑战。

2017-09-12

Windows Server 2016：腾飞助力还是锁定客户？

将Windows Server 2016中最有用的部分同Software Assurance授权协议捆绑在一起，用这种做法锁定客户。

2017-09-03

Windows赢了桌面，而Linux赢得整个世界

最坚决推行 Linux 桌面系统项目的城市正在转回 Windows 阵营，但 Linux 的命运已经不再与 PC 休戚相关。

2017-08-14

Windows 10如何重置本地组策略设置

「组策略」不论对企业管理员还是高级点的个人用户来说，都是对 Windows 功能和系统设置进行管理和微调的利器。

2017-08-14

微软：Windows 7已过时不安全

虽然微软一直在推荐Windows 7用户尽快升级到Windows 10，但从目前的情况来看这一速度非常缓慢。据第三方统计，目前Windows 7的市场份额已经接近50%，是当之无愧的第一大操作系统。

2017-07-10

IDC:2020年Windows Phone系统将消失

IDC:2020年Android和iOS将统治手机行业（图片来源gsmarena） Android系统和iOS系统的总市场占比已经超过99%，而Windows Phone和其它系统的占比已经被压缩到不到

2017-07-09

Skype Translator面向所有Skype for Windows用户开放

这项根据整合了语音识别和机器学习技术能够在聊天和视频聊天过程中提供实时的语言翻译，在经过数月的公开测试之后今天Skype团队正式宣布该工具面向所有Skype for Windows用户开放。

2017-07-05

微软Windows 10在企业市场仍然如鱼得水

毫无疑问，微软积极促销Windows 10以及不断出现的各种问题已经激怒了许多消费者，而其他人也对Windows 10 Mobile一再延期感到失望。

2017-07-05

Windows Phone系统也有值得借鉴的地方

说到Windows系统，大多数人都啧啧赞叹，认为是操作系统领域无可系统的霸主，事实也却是如此，在PC领域，Windows可谓是呼风唤雨般的存在。

2017-07-03

数据显示：Windows Phone销售份额继续下降

根据Kantar提供的数据显示，Windows Phone在在截至2016年8月三个月期间保持同样的下降趋势。首先，Windows Phone份额在欧洲市场大幅下降，尽管欧洲一直是该平台最成功的地区。

2017-07-02

王者归来 Windows 10用户达到2.7亿

3月31日消息，据路透社报道，在发布8个月之后，微软的Windows 10操作系统已经拥有2.7亿活跃用户。

2017-07-02

微软这是要彻底放弃 Windows Phone 吗？

据国外媒体报道, 显然Windows Phone遇到麻烦了。

2017-06-07

Windows上搭建Standalone模式的Spark环境

Java 安装Java8，设置JAVA_HOME，并添加 %JAVA_HOME%\bin 到环境变量PATH中 E:\java -version java version "1.8.0_60" Java(TM) SE Runtime Environment (build 1.8.0_60-b27) Java HotSpot(TM) 64-Bit Server VM (build 25.60-b23, mixed mode) Scala 下载解压Scala 2.11，设置SCALA_HOME，并添加 %SCALA_HOME%\bin 到PATH中 E:\ scala -verion Scala code runner version 2.11.7 -- Copyright 2002-2013, LAMP/EPFL Spark 下载解压Spark 2.1, 设置SPARK_HOME，并添加 %SPARK_HOME%\bin 到PATH中，此时尝试在控制台运行spark-shell，出现如下错误提示无法定位winutils.exe。 E:\>spark-shell Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties Setting default log level to "WARN". To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel). 17/06/05 21:34:43 ERROR Shell: Failed to locate the winutils binary in the hadoop binary path java.io.IOException: Could not locate executable null\bin\winutils.exe in the Hadoop binaries. at org.apache.hadoop.util.Shell.getQualifiedBinPath(Shell.java:379) at org.apache.hadoop.util.Shell.getWinUtilsPath(Shell.java:394) at org.apache.hadoop.util.Shell.<clinit>(Shell.java:387) at org.apache.hadoop.hive.conf.HiveConf$ConfVars.findHadoopBinary(HiveConf.java:2327) at org.apache.hadoop.hive.conf.HiveConf$ConfVars.<clinit>(HiveConf.java:365) at org.apache.hadoop.hive.conf.HiveConf.<clinit>(HiveConf.java:105) at java.lang.Class.forName0(Native Method) at java.lang.Class.forName(Class.java:348) at org.apache.spark.util.Utils$.classForName(Utils.scala:229) at org.apache.spark.sql.SparkSession$.hiveClassesArePresent(SparkSession.scala:991) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:92) at $line3.$read $$ iw $$ iw.<init>(<console>:15) at $line3.$read $$ iw.<init>(<console>:42) at $line3.$read.<init>(<console>:44) at $line3.$read$.<init>(<console>:48) at $line3.$read$.<clinit>(<console>) at $line3.$eval$.$print$lzycompute(<console>:7) at $line3.$eval$.$print(<console>:6) at $line3.$eval.$print(<console>) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at scala.tools.nsc.interpreter.IMain$ReadEvalPrint.call(IMain.scala:786) at scala.tools.nsc.interpreter.IMain$Request.loadAndRun(IMain.scala:1047) at scala.tools.nsc.interpreter.IMain$WrappedRequest $$ anonfun$loadAndRunReq$1.apply(IMain.scala:638) at scala.tools.nsc.interpreter.IMain$WrappedRequest $$ anonfun$loadAndRunReq$1.apply(IMain.scala:637) at scala.reflect.internal.util.ScalaClassLoader$class.asContext(ScalaClassLoader.scala:31) at scala.reflect.internal.util.AbstractFileClassLoader.asContext(AbstractFileClassLoader.scala:19) at scala.tools.nsc.interpreter.IMain$WrappedRequest.loadAndRunReq(IMain.scala:637) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:569) at scala.tools.nsc.interpreter.IMain.interpret(IMain.scala:565) at scala.tools.nsc.interpreter.ILoop.interpretStartingWith(ILoop.scala:807) at scala.tools.nsc.interpreter.ILoop.command(ILoop.scala:681) at scala.tools.nsc.interpreter.ILoop.processLine(ILoop.scala:395) at org.apache.spark.repl.SparkILoop $$ anonfun$initializeSpark$1.apply$mcV$sp(SparkILoop.scala:38) at org.apache.spark.repl.SparkILoop $$ anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop $$ anonfun$initializeSpark$1.apply(SparkILoop.scala:37) at scala.tools.nsc.interpreter.IMain.beQuietDuring(IMain.scala:214) at org.apache.spark.repl.SparkILoop.initializeSpark(SparkILoop.scala:37) at org.apache.spark.repl.SparkILoop.loadFiles(SparkILoop.scala:105) at scala.tools.nsc.interpreter.ILoop $$ anonfun$process$1.apply$mcZ$sp(ILoop.scala:920) at scala.tools.nsc.interpreter.ILoop $$ anonfun$process$1.apply(ILoop.scala:909) at scala.tools.nsc.interpreter.ILoop $$ anonfun$process$1.apply(ILoop.scala:909) at scala.reflect.internal.util.ScalaClassLoader$.savingContextLoader(ScalaClassLoader.scala:97) at scala.tools.nsc.interpreter.ILoop.process(ILoop.scala:909) at org.apache.spark.repl.Main$.doMain(Main.scala:69) at org.apache.spark.repl.Main$.main(Main.scala:52) at org.apache.spark.repl.Main.main(Main.scala) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:497) at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit $$ runMain(SparkSubmit.scala:743) at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:187) at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:212) at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:126) at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala) 从错误消息中可以看出Spark需要用到Hadoop中的一些类库(通过HADOOP_HOME环境变量，因为我们之前并未设置过，所以文件路径null\bin\winutils.exe里面出现了null)，但这并不意味这我们一定要安装Hadoop，我们可以直接下载所需要的winutils.exe到磁盘上的任何位置，比如C:\winutils\bin\winutils.exe，同时设置 HADOOP_HOME=C:winutils 。现在我们再次运行spark-shell，又有一个新的错误： java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveSessionState': at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession $$ reflect(SparkSession.scala:981) at org.apache.spark.sql.SparkSession.sessionState$lzycompute(SparkSession.scala:110) at org.apache.spark.sql.SparkSession.sessionState(SparkSession.scala:109) at org.apache.spark.sql.SparkSession$Builder $$ anonfun$getOrCreate$5.apply(SparkSession.scala:878) at org.apache.spark.sql.SparkSession$Builder $$ anonfun$getOrCreate$5.apply(SparkSession.scala:878) at scala.collection.mutable.HashMap $$ anonfun$foreach$1.apply(HashMap.scala:99) at scala.collection.mutable.HashMap $$ anonfun$foreach$1.apply(HashMap.scala:99) at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230) at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40) at scala.collection.mutable.HashMap.foreach(HashMap.scala:99) at org.apache.spark.sql.SparkSession$Builder.getOrCreate(SparkSession.scala:878) at org.apache.spark.repl.Main$.createSparkSession(Main.scala:96) ... 47 elided Caused by: java.lang.reflect.InvocationTargetException: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveExternalCatalog': at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:422) at org.apache.spark.sql.SparkSession$.org$apache$spark$sql$SparkSession $$ reflect(SparkSession.scala:978) ... 58 more Caused by: java.lang.IllegalArgumentException: Error while instantiating 'org.apache.spark.sql.hive.HiveExternalCatalog': at org.apache.spark.sql.internal.SharedState$.org$apache$spark$sql$internal$SharedState $$ reflect(SharedState.scala:169) at org.apache.spark.sql.internal.SharedState.<init>(SharedState.scala:86) at org.apache.spark.sql.SparkSession $$ anonfun$sharedState$1.apply(SparkSession.scala:101) at org.apache.spark.sql.SparkSession $$ anonfun$sharedState$1.apply(SparkSession.scala:101) at scala.Option.getOrElse(Option.scala:121) at org.apache.spark.sql.SparkSession.sharedState$lzycompute(SparkSession.scala:101) at org.apache.spark.sql.SparkSession.sharedState(SparkSession.scala:100) at org.apache.spark.sql.internal.SessionState.<init>(SessionState.scala:157) at org.apache.spark.sql.hive.HiveSessionState.<init>(HiveSessionState.scala:32) ... 63 more Caused by: java.lang.reflect.InvocationTargetException: java.lang.reflect.InvocationTargetException: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: --------- at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:422) at org.apache.spark.sql.internal.SharedState$.org$apache$spark$sql$internal$SharedState $$ reflect(SharedState.scala:166) ... 71 more Caused by: java.lang.reflect.InvocationTargetException: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: --------- at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method) at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62) at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45) at java.lang.reflect.Constructor.newInstance(Constructor.java:422) at org.apache.spark.sql.hive.client.IsolatedClientLoader.createClient(IsolatedClientLoader.scala:264) at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:358) at org.apache.spark.sql.hive.HiveUtils$.newClientForMetadata(HiveUtils.scala:262) at org.apache.spark.sql.hive.HiveExternalCatalog.<init>(HiveExternalCatalog.scala:66) ... 76 more Caused by: java.lang.RuntimeException: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: --------- at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:522) at org.apache.spark.sql.hive.client.HiveClientImpl.<init>(HiveClientImpl.scala:188) ... 84 more Caused by: java.lang.RuntimeException: The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: --------- at org.apache.hadoop.hive.ql.session.SessionState.createRootHDFSDir(SessionState.java:612) at org.apache.hadoop.hive.ql.session.SessionState.createSessionDirs(SessionState.java:554) at org.apache.hadoop.hive.ql.session.SessionState.start(SessionState.java:508) ... 85 more <console>:14: error: not found: value spark import spark.implicits._ ^ <console>:14: error: not found: value spark import spark.sql ^ Welcome to ____ __ / __/__ ___ _____/ /__ _\ \/ _ \/ _ `/ __/ '_/ /___/ .__/\_,_/_/ /_/\_\ version 2.1.1 /_/ Using Scala version 2.11.8 (Java HotSpot(TM) 64-Bit Server VM, Java 1.8.0_60) Type in expressions to have them evaluated. Type :help for more information. scala> 错误消息中提示零时目录 /tmp/hive 没有写的权限： The root scratch dir: /tmp/hive on HDFS should be writable. Current permissions are: --------- 所以我们需要更新E:/tmp/hive的权限(我在E盘下运行的spark-shell命令，如果在其他盘运行，就改成对应的盘符+/tmp/hive)。运行如下命令： E:\>C:\winutils\bin\winutils.exe chmod 777 E:\tmp\hive 再次运行spark-shell，spark启动成功。此时可以通过 http://localhost:4040 来访问Spark UI

2017-06-06

Windows Edge 使用 Google 的 Brotli 压缩算法

在最新的Edge构建包中默认是启用Brotli的，用户可以通过Windows Insider Program预览。Microsoft透露，该版本将在明年年初达到稳定状态。

2017-06-05

精选列表

Windows Azure Service Bus (2) 队列(Queue)入门

Hadoop on Windows with Eclipse -04- Setup SSH daemon