一、抛出问题  

  Hadoop集群(全分布式)配置好后,运行wordcount程序测试,发现每次运行都会卡住在Running job处,然后程序就呈现出卡死的状态。

  wordcount运行命令:[hadoop@master hadoop-2.7.2]$ /opt/module/hadoop-2.7.2/bin/hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.2.jar  wordcount  /wc/mytemp/123 /wc/mytemp/output

  现象截图如下:卡死在红线部分:

      aaarticlea/png;base64,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" alt="" />

二、解决方法

  1、因为小白一枚,到网上找了很多教程,集中说法如下:

    (1)有的说,是防火墙或者selinux没关闭,然后,就去一一查看,发现全部关闭

    (2)有的说,是因为/etc/hosts文件中的127.0.0.1等多余的ip地址没删除或者没注释调

    (3)有的人说,查看日志(what?小白哪知道哪个日志),然后不了了之。

  2、解决办法:  

  小白解决问题总是会花费很多时间的,因此半天就这样没了,很对不起公司的工资啊,现将解决办法一一列出。

  (1)第一步:因为Running job发生的问题,在hadoop 中我们要想到mapreduce发生的问题,在Hadoop2.x系列中MapReduce是通过yarn进行管理的,因此我们查看yarn-hadoop-nodemanager-slave01.log 日志,该日志在slave节点的¥{HADOOP_HOME}/logs下面

终端执行shell指令:yarn-hadoop-nodemanager-slave01.log

查看到日志截图如下:

2016-07-27 03:30:51,041 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 4 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:30:52,043 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 5 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:30:53,046 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 6 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:30:54,047 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 7 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:30:55,048 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 8 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:30:56,050 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 9 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)
2016-07-27 03:31:27,053 INFO org.apache.hadoop.ipc.Client: Retrying connect to server: 0.0.0.0/0.0.0.0:8031. Already tried 0 time(s); retry policy is RetryUpToMaximumCountWithFixedSleep(maxRetries=10, sleepTime=1000 MILLISECONDS)

(2)大概的解释一下意思

  就是说每次Client试图连接0.0.0.0/0.0.0.0:8031失败,那么导致这个原因,应该能想到是配置问题,然后复制这段信息进行百度,尝试了几个,终于参考了此博客(解决Retrying connect to server: 0.0.0.0/0.0.0.0:8032. Already tried 0 time(s); retry policy is...)解决了本文的问题,将下述代码添加到yare-site.xml中:(注意我将master、slave01、slave02这个文件都修改了,是不是只修改master就可以,不清楚,但是初步判断应该全部修改)

  

<property>
<name>yarn.resourcemanager.address</name>
<value>master:8032</value>
</property>
<property>
<name>yarn.resourcemanager.scheduler.address</name>
<value>master:8030</value>
</property>
<property>
<name>yarn.resourcemanager.resource-tracker.address</name>
<value>master:8031</value>
</property>

然后插入后的效果如图:

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAjIAAAEdCAIAAACZvBpwAAAgAElEQVR4nO2dvW7cSLOGJ9jAyQIGjGHiyMkmStaBEueCT3huQMGXODiBBCjcC3A8C0iJrkDZhw1WwESyrkCRooFiA0oVGzwB/6q7q3uaw5/umXkeFGCbJtnNJlnvVJOsWvznP//5H4d//vnHXVgAAABMzAJZAgCAfECWAAAgI5AlAADICGQJAAAyAlkCAICMQJYAACAjkCUAAMgIZAkAADICWQIAgIxAlgAAICOQJQAAyAhkCQAAMgJZAgCAjECWAAAgI5AlAADIiPFlaXl2/duvze9ny0n73TT0693F5A0NRO3ncnn2++bX4tevxa9fv12fBdY8PDI89mMZ+eM4TNh39kCWqnup8mKL9YW1XN5jlb/L7a7TZelivdhcf1gut665ff/Ls983nX8viuLD9abd+fJibXj/5cW7djCb0yTXmWEMRzz23k17ju7A/PWRHCYcKiPI0ofrjaEWy4t3v9bvl+Nc+r1ELk9ZUrEGbSBylKwRe7/e/H5x/VurUsuLd83/tuq1vFgvNptqnRnGcNxj78UeXSFDyPAwP1xv5C8ngABDZen9+pf1y3ceWXq/rn/yt/feh+vNoosDRCgggq3wjSrXbEKHi3e/1r83e7ZmnNx9tr1aNCMQ0U/vmr59qrS+/v3ajI021x+WZ79vmtEQsrQ8u/7t1/p9LUvX76837y6iZMntkjsg6tD1OvYqhluIMyIvrbbz1ebvrtsO2Ptsd+u7QvTW445Iv5A8a6r9jG9IvercfQ48zEK7EUbB9RUAKrvLUjUd5F6148pS0XoTd9rHcaDaEuHIhEdWeb92nwBdvGtmDluB9O3z/fqXGgSojl6NGNw1ffvUWrl496vyUN3gLy/WrR4IobU7XM+qnV3/tr7YKktul9RYzRi6i7XU1JhjN+SzmfQLyFJ7eSgnUazpnd2yWu95ROq5sC4btZ/bG4q56pxjjz1M/z4nirQ+XG/Cv64Aip1lKTBJ7cqS/Nnb/fTTFgZwxSlKluRzKfHLMdSEZ0Ky3bm6z4Dm7SxLW3XU3vxibfzmFXtbnl3/1nn2pufy+dPm+sNy+X69+f0sJEtql6xjqR2uR0J2OPYYWVJcsBFs9ZOlvkekjZLSotvP7Q0FrzrvsfdQX2Wf7o3gY4dbe3mxDt+GAEOjpTkfEtQBgeZ2vUu0p+tbWqluquq3quog1Cf2OciS+YMgLJ/V/9YhVOv3L9aL9XUOslQYs3ByBjJKltS5SrUVtfUcZclzJQ+SpeDdIW+EsSBaghgmeLY02Qvi1p7Ve08+WSkcJevT0Pq99fO8mbdR91m/9DzqJF5gn3q3TVmymqjm8exXHsSzpeZ9h81vIVlSuuSfiRoQLZ11r2mYB1jtvHrF3C9L1tSZaN26Qryt9zmiwImQ033hfuoNBa86dZ89DnPb3RE+zL7wbAkimeBNvFFlyXruLafO3eVN695XHkK/Dc19iofPygSguk9zD5Ur8fbTeX1RX9PdZ2isPD/SxUiu38swonk6KH81WzOB2wZKes+oyCb+2OU7C21DH7oXAa7f+d293FyuWThXiHfk+xyRdiKUy2bbZKNxXiKvOp8sxR6ms0/1RhgOb+JBPGR5CDH66xsQifVOgfrbP1sGXjZcdXDkIEshcBCpkLK020xsQpAlgCEgSyFwEKmwppL2KFQqkCWAYSBLAACQEcgSAABkRC1L/2wDWQIAgBnoZMkNj6zgKXVXAQDg8DlSWVouz/74Xp5eXabuCAAAGMwnS1kpQXxnPl2Vp99vPvJaFADALMwkS8vl5clteXr78sefy6Ioln/efL4tT67Wp7fl6W0tD5VUfD4/+3j+cnpbnt6uP1WfrXxtVrstP5+f+TZvlxtravv8dFW2Ozyte3X2x3fRYiVa328+LpfNPuv/AgCASTFkyfeyw0BZqj27iDmkr69U5+TrspaQq/XJ+Vm1wmfxl6LRp5OvS8/mlyfumto+Cy1aajex/t6t3GgqAABMx+TRUh3rmNNlpkLUctJ4fyMu+Xj+IoKYZk11cxFUtQGTus9ClSWxRJ24q2KsVqsAAGAK5pjEc+fBDF1pAyPtec92WWo3N0OcuiHPM6RgW5cn5n6IlgAAZiPls6VKVz6ev1TLVamoxMZeU928Ej9r87AsmSFR00nvfOOQEQAAgBjSvIkn303onuh4JKR5W0GsqW3uLPdKXb1yN+nXhUHVTF0leN0S3sQDAJiLNFkeZLgz/+YB5JwhAADMT5qceHnKknyXDwAAkoAs1dQfM+XxtS8AwNEyhyz9+PFjxB4DAMABQ2ELAADICKIlAADICKKl/WB5dvNSri95RXBGlmc3L2W5vpxpzJdf13yyDVAQLe0LyNL8zClLWeXXB0hLjtHSDLfo3n0kiywdDHo2kyop/pQZF/fumoejJbtoKb4EhlXt4tNV+flq/fm2PP2+Pvmup4Ro3yl3Uwqd3byULzdnTWGL6l9FUVyuy5b2h/Plulzf3Lx0i5fLpbGs2tZ3gOqa1W9zqyG5sGxkyV3z7Obl5eZmXZZl/Ue93O28r3X1MJdyabOy2k93QHyH7+uSOLT1ZTWcxgrBIRVdCo+n20953qsVrPNuRUui/97T4etS4VzeLVIzZrvmAfIkr2gpXAKjTX8nN2kXfroqT2/Xn5pPmj5dladXl2q1i3rPZgLW5bLySIZzNPomFtZusvm79KNF7c29rllds/WOTUMvN2f1PmvX3Ppr6cSbPjezTXW/zm5eLCdubh7qp7lm06X6r3rr6oBsP9fqEYlBbrvXSoUPt8X4fhqHKbYqml8ncs9VjyIbcgfBvbzlcieH1uTXPECeZBQtbS+BIe4xmSivu0WvLpd/3nyW/9SqXcj9y3IVrfuTbt2MGDpZCvnB4ISbumb1Z7tOvUYjBnJNM36qfou3/9mpVB3ZOJ0PaoC7piNLWuvqgHjPcnSXqhNRloYSyM3bc6Ss1qef8rwbOzFlSQ7I1oaULmmXd4WV8mrOax4gQ7KMlrbdompa8cAtqt6B7i/H2p17fv9a0VIyWRILW1RZUjuvz5j5D9Pytmrr6oD4jz2qS+1xvbwYIxPa+eW6VYJe/WzGq/5D9DZCljwNuV0qPNNobsqrOa95gAzJKFqqCJTAsG7Rtvhs6BbVql0UHgdRFMXl+uXmZt35ETG31jzs6C1L8jGJb019Eq+bzat+fHezcFbruixpnd/aerdmI27OYeoBhypL9rF7u2QfZtF5/O4531asucrIftaHemkfryNL9VxpzIC4XWrXt54tudmBZ77mAXIjr2ipwi2BoZZCr6tanLv3ZPfPolCqXRT+t5IsN1qIiKHWq/6y1Pra8Jpieqr7Sd5OEa0vra3kut5JPLfzvtZ9h2lNuKmtqwOiHruvoXaXXT+bp0Btiz5lsiYW9bdFtvXT+elgz801L1/I5d4B8XWp3Xl3efvfypvtmgfIjeyipbSE52SOCuuFiK3vHcAO8AktgEuO0VIqtk7IHBVSlhgZAJgNZKmmmlwiIGixZqIYGQCYBybxAAAgI4iWAAAgI4iWAAAgIw4nWpJv0I5bT31m5s/KaiXdiVi/e+zUpcNwFvrSyvXuXv/X1Q7mYgA4Qg4tWpLffOwpeyBL2mv0+kInrVz/vu2eTv4ALgaAIyTHaCmVJ8rke8P8ZclKlRRY2EuWRq/4cAAXA8ARkl20JLOzNFMxdbqU+p/fbz5qSf7rzU1P5Mt6GV/tYnjBCLfiQ2QNi0DmCNGB0D71EXZqLtQNNTs1Frq5++zsB/rC5mzasuTr59aKD8kvBgCYh7yiJaWwheM+rB/OVub/GE8Un/l/x4IRVuY3pZKCnQp2ew0LK1FQXHkFFU/mJKfWRjid0k7Rkq+fsRUfkl4MADAPGUVLemELMbHz8fyl9Vxukv96/RhPFJ35f8eCEcIXKxqglULQk4Vvy/Yd3qdvnJWaC96GxpYl9djjKz4kvRh84wkA45JltGTOnDS+6eyP74ZPsZL8yz3EeKKYzP87FowIy9K29wV2kaX+qfyMMhCzyZKnn5EVH4qkFwMAzENG0VKF+4yhWnJyfvO5fa6gJfmvV/Z4ovaN4ZOvy/jM/zsWjBDZ5HwzZloIpdawcBfuUl5BH+o4/bPqTRRDJ/E8ObwjKj4USS8GAJiHvKKlCveNrGoipV2iJvk3k/l3Ey/1tvWaylPuQOb/ngUjlDk0b905cx6r8NSwcCs+FI2vt94vUPepjq1bc8EXGKmtF3Gy5K0N4e/n1ooPaS8GAJiH7KKlPaXvO9YQhooPAEdLjtHSPoIsAQCMArI0DrnJkjmpGPWGHgBADiBLAACQEcgSAABkBLIEAAAZkV6WeOcKAABaEsvSkGTho5NVZwAAjpP5ZGn0sgWjEy9LfGsJADARM8nS1rIFRStRV03qTPG1/+fzsyYdp5FyRubWVDcvCqVsgbrP9vt/8bW/r5LCksw0AAAT4ZUliyGyFFu2QPh6K9HZ56v1yflZl9NMzbmpb66ULVD3WWjRklFJgaoHAADTM3m01KNsgaEQtZxYxd/cDbs11c21sgXqPgtVlsQSdeKOqgcAAOMyxyReZNkCQ1esZM+mqm2XpXZzrWyB7xlSsK3LE3M/REsAAFOQ7NmSW7ZA6kpbOEd/UUIrsaNvrpUt2CJLZkjU9NysmcuzJQCAaUjzJl7grTyrEoFPQmRBUq08gfvIqitbEHjjTkz6dQpazdTJwI438QAAJiLNd0vqJ7RW0bbe+xy2eQC1Hh0AAExB+iwPLXnKklq6GwAAJgJZCmEVQgUAgKnpJ0uLctG7gb/+PVqb4HwBABw4yBKyBACQEbUsuWkd1CwPyBKyBAAwKZ0sueGRFTwVyBKyBAAwMUcrS4+r1/L+DlkCAMiLWWXpy8Nb+fyUWpD6ydKXh7fNwyOyBAAwD/PJ0rfnsnzdfKn/+XRf/lw9vJVlWZZl6/e/PZf3D5tNtbT8+a1a+e92SSsk+ubamso+vzQbNryt/v73y8Ob6N7j6tXolfgvZAkAYEIMWfK97DBYlp7upXg0S+rI6e/Npnxb/W0LwLfn8v7O+F/xd3Xzp/tWyf56ug/sU4+Wuk0Wf2823a6aOM9cgiwBAEzB9NHS35tN6U6XSQnpFELIhtADMe/XrKBtLkKlNgZS9+mbxPv2XGunPnF397PdJ7IEADAR80ziieBmOlm6+6lOtcXL0uLvzeZ188XYOdESAMCspHy29K2LQuq/KxLincRzN3+6V8Iynyx1sZG58G318NN6L4NnSwAAs5HqTbyne2e2zSshdz+dNfXNjXk85XmSK3jOHu5+lqa28SYeAMCcpMryoEyU9bGBm/vNMxOILAEAzEOqnHh5ypI+DYgsAQDMBrJU27dn8xMoZAkAIAU7ylIv7/zjx48RfT2GYdNZUncEUBTzyBKGYftiSd0RQFEQLWEYJi2pOwIoCqIl7PDNSSXlXZi2S3lYUncEUBRES9jhW36yNORjuKktqTsCKIpso6WpS2Dk7BewkS2pLGlXskgKPFmjfAMO+0uO0VJkCYyW6kujLw9vm4fNfVmWr5vVs6htoVW7cFrxFrZwG1roBTg8tTY8BxhXv8NYGKzfId6YFw5Xb8g4KG/rvvHUBiT2HC3+kjk7xMpxFUlCF0xw6NTDLMOjtNPpsM67nrbqTma3munyRpZgj8gtWgqWwBDZ8zprvHCTTbXeQ/ODUa920UmR+r/bfl9rxTK29dPjrbTks0ZVjt5JArf0899vz6X2+91u3TOe6oDEniNjkLuEGr0qkgTN7JJw3IGFw06Ht2/ulVzZ4+pVXoSzXd6xltQdARRFXtHS1hIYUi2MH93Nffv8JL3q5uHRV+2iM1GuQi9s4TTk8USefmrmERuln3XFQqEi21OqW9GS0k9nELTW9fHUByT2HOmy1K8iiWZuQzKJVNsldeGw06Ev1K9k86hnv7wjLak7AiiKPKMlbwkM9Ue3/Dnp3rfBHHf2z0mlsIUeQo0vS+FcfJWTen5aTCRLWuseWVIHJPYcLYzpKTds2jZK3mvGaWigLEWfDv9C90pW25rx8o6zpO4IoCjyipbErauXwGjvW6ugbeC+9ae5Uyff7cIWWkMej+mXJScruWfzoBfWjt2cxKv+8rh6DffzcfWqTuL5Kl25P8/dAYk9R43wRx27V5as8fQ15A6IunDg6QgutK8x5fBnvbxjLKk7AiiK/KIlyyd67lvxo3vzsLkP3bd6tQvvq0qahFgN+R2ZLkvVJM82WVL7WXnPGu2tgS7u+dI9Ng/309qt9i7A6+aLfzy1AYk9RwsjWgq17u+8Pp5uQ+2A3N89hRcOOx2ec6RcyWqJr3kv7whL6o4AiiLPaCmljVrYAlOG13wh8Ihe08/4E1ppSd0RQFFkGy0lspELW2C2GbLEaOdoSd0RQFEgS61NUdgCc8yY8mK0M7Sk7gigKJjEww7Skt5TADAIoiXsAC3pPQUAgyBawg7Qkt5TADCIg4qW2tdqeZA+su30FlnC05H0ngKAQRxetPS4es1Kliboj8xMY3z5a3/MpKRU8KwZtgHfwaQ5HUnvKQAYRKbR0oDCFrv7wWmqXYzul9XcSHoSUmM8u29Cxbel3pxDVos7F2JIczqS3lMAMIgcoyWZN8Vyne0HmHotA8UPepIvRFe7iC7uoBQ4aHMK2CFLrzoOduKJruhG9/Gv+ArYTYLgERslZfXWQgxpTweyBHAM5BYtqYUt2p/qMlCQYiAXxvjB2HIAfYo7hDL9eLNzxtRxcPIhdTIg1eL5qd3Jqsue8HRvpqXxa1V8IYZkpwNZAjgGcoqWPOUAZL2Jzo1q9SZi/WB0OYA+xR30qgeKLA2t49DlWm2VrOpnW0hJSerj1vKRS3oUYkh5OpAlgGMgx2jJ9ux13mX5sz1Qsi/CD0aXA+hT3EH6UHkIjiwNrONgtNg8Urr7WXaxjvo4x4hCtBAkshBDytOBLAEcAzlFS8IVmn7qcfX6troTRQE89SY8ftCtZRBbDqBPcQefcrixy2h1HLTCFp4ip/bDJ93RRxRiSHk6kCWAYyC3aMnSA49r1msZGPnW2vXVig+R5QD6FHfwFzhwX8juU8fBPXb5JoX2woUMYuxWnBmz0MsR3gzfiU4HsgRwDOQYLWFZ2J4UYlAt6T0FAIPINFrCsCGW9J4CgEEgS9gBWtJ7CgAGgSzhMQEAMgJZQpYAADICWUKWAAAyIgNZ2uc3vpAlAIBxSS9L0+Tt3s3mqMKQ9HQDAOTOrLI0dtGEZLLEl54AABMxnyxtLZpQJUxbdVkAHtsNlYoPSikEffPIKhJqEQqzjoOoKEFeHACAafDKksUwWYovmtBkC7XSrFkZerx54dzNe1WRUItQeLOykkUUAGB0po+WehRNkBLSKYSbLM6aDGxW0DbvV0VCmcSTdRwUZaXmAgDAqMwziRdZNGECWepXRUJ7tlRn0VZK3hEtAQCMTrpnS0rRBOH6RXUGveSPPonnbt6vioSaM/vb89vq4aclqzxbAgCYgmRv4mkCIAoxiJkxXUK6cqhaHQc5sdarioRSHkIvLcGbeAAAU5DouyX9E1ploqyPDdzcb8HyqcgSAMCIpP+cNntZ8tZORZYAAEYHWQpZVXR13CQUSU83AEDuZCVLh2ZJzywAwF6CLCFLAAAZUcuSm9Zh1CwPR2pJzywAwF7SyZIbHlnBU4EsIUsAABNztLJEDQsAgByZVZa0wha5yxJfzgIAzMl8smRm66GGBQAAKBiy5HvZYYLCFtSwAAAAhemjJb2wBTUsAABAYZ5JPLewBTUsAABAIeWzJWpYAACARao38ahhAQAACqmyPGSXlbWTJWpYAACkI1VOvDxliRoWAACJQZZqo4YFAEAOzCFLP378GNHXYxiGxVtSBwu7QGELDMMO2ZI6WNgFoiUMww7ZkjpY2AWiJex4bKdHkk4mKsuqp5LlqC/L7NKlbf1M0KU8LKmDhV0gWsKOxyaRpcVf/85TJ2VLl5IKw5DP+6a2pA4WdiHTaGnqEhg530XYZIYsjWDavSnSHE/WKF+1Hw85RkuRJTBaKnfw5eFt87C5L8vydbN6FpMqWrULpxVvYQu3oYVegMNTa8NzgHH1O4yFwfodwuEK96Q3ZByUt3XfeGoDEnuOFn/JnB1i5biKJN4hVUdJOcyn+/Lnt6YD4XooZuZfsbkzyO0FY8jSsCPSh07pkr5wxAvMupL1RFx3Ml/XTDdsvCV1sLALuUVLwRIYInueef+3VZR+fmv20Py80qtdVGYmYA0VtrAWasUytvXTc29ryWeNqhy9kwRu6ee/355L7deu3bpnPNUBiT1HxiB3CTV6VSTRx1PNhagdpttPtXXxYbXR+UhZGnpEvkHWuuQuHHaBefvm3pvtscvbarYbNtaSOljYhZyipa0lMKQvMH50N1f585P0qpuHR1+1i85EuQq9sIXTkOe+DfisiNve08+6YqFwr9tTqlvRktJPZxC01vXx1Ack9hzpstSvIoli7ih5ppW0fqqtyxxUO8jS4CNShk7tkt7PQReYvlC/N83zOPsNG2lJHSzsQo7RkrcEhvqjW/74cq/yYI47+8eXUthCD6HGl6VwLr7qln5+WkwkS1rrHllSByT2HC2MyRw3bNo2SmETo9RDltTWB8rS0CPShm6gLEVfYP6F7r2ptjXjDRtnSR0s7EJO0ZK40PUSGMYvXDExErjK/Wnu1Klqu7CF1pDHv/h9lpOV3LN50Gdpx25O4lV/eVy9hvv5uHrVZ7c8la7cH7PugMSeo0b4o47d68Sd8VRGyXuYqscMzJTK8dQHuR1VcxJvwBH5hs5tXe/nsAssuNC+a5QTOusNG2NJHSzsQm7RUm1mCQzPU5OyLMty87C5D13lerUL74s9moRYDflve12WqimRbbKk9rPyNTXaWwNdQPCle8gc7qe1W+3J+evmi388tQGJPUcLI1oKte7vvDuenlFSDtNzjjxXSLPDbittkI3WS+25ff8j0ocu3CW5cNgF5htP995Ui5bNe8NGWFIHC7uQY7SU0kYtbIEpwysEW63EiO2NZfwJrbSkDhZ2IdNoKZGNXNgCs82QJUYbm8OSOljYBWSptikKW2COGRNEjDY2gyV1sLALTOJhB2hJ7ykAGATREnaAlvSeAoBBEC1hB2hJ7ykAGMRBRUsJSgwcie30zlXC05H0ngKAQRxetDRvLuck/ZF5XIwvfyu6j5mUlAqeNcM24KuRNKcj6T0FAIPINFoaUNhidz84TbWL0f1yfGpRczy7vKjb1hyzbEGa05H0ngKAQeQYLcksI2a9ie4DTD3zv+IHt3/YH652EV3cQSkH0H6Bb4csvaoe2IknuqIb3ce/4itgN2WAITbBNbeWLUh7OpAlgGMgt2hJLWzR/lTXyrjFlxhQc24Gk+f3Ke4QyvTjzWUZU/VASwFXy4BUi+endierLnvC072TxCWwZlzZgmSnA1kCOAZyipY8yfNlvYlufkmrNxHrB6OT5/cp7qDXCAgXiJOtR6eX7pKQtkpW9bOtMKQk9WnSK+hr9ihbkPJ0IEsAx0CO0ZLt2essxfJne6BkX4QfjE6e36e4g/Sh8hAcWRpY9cBosXlQdPez7GId9XFO02fvmpFlC1KeDmQJ4BjIKVoSrtD0U4+r17fVnUih76k34fGDaoWCqOT5fYo7+JTDjV1Gq3qgFbbwlAQ1SsF614woW5DydCBLAMdAbtGSpQce16xn/tdLDKgVHyKT5/cp7uAvB+C+kN2n6oF77PJNCu2FCxnE2K141tRH3pvhO9HpQJYAjoEcoyUsC9uTsgWqJb2nAGAQmUZLGDbEkt5TADAIZAk7QEt6TwHAIJAlPCYAQEYgS8gSAEBGIEvIEgBARmQgS/v8xheyBAAwLullaZq83bvZHFUYkp5uAIDcmVWWxi6akEyW+NITAGAi5pOlrUUTqoRpqy4LwGO7oVLxQSmFoG8eWUVCLUJh1nEQFSXIiwMAMA1eWbIYJkvxRROabKFWmjUrQ483L5y7ea8qEmoRCm9WVrKIAgCMzvTRUo+iCVJCOoVwk8VZk4HNCtrm/apIKJN4so6DoqzUXAAAGJV5JvEiiyZMIEv9qkhoz5bqLNpKyTuiJQCA0Un3bEkpmiBcv6i5oJf80Sfx3M37VZFQc2Z/e35bPfy0ZJVnSwAAU5DsTTxNAEQhBjEzpktIVw5Vq+MgJ9Z6VZFQiz5opSV4Ew8AYAoSfbekf0KrTJT1sYGb+y1YPhVZAgAYkfSf02YvS97aqcgSAMDoIEshq4qujpuEIunpBgDInaxk6dAs6ZkFANhLkCVkCQAgI2pZctM6jJrl4Ugt6ZkFANhLOllywyMreCqQJWQJAGBijlaWqGEBAJAjs8qSVtgid1niy1kAgDmZT5bMbD3UsAAAAAVDlnwvO0xQ2IIaFgAAoDB9tKQXtqCGBQAAKMwziecWtqCGBQAAKKR8tkQNCwAAsEj1Jh41LAAAQCFVlofssrJ2skQNCwCAdKTKiZenLFHDAgAgMchSbdSwAADIgTlk6cePHyP6egzDsL22pD5/D6CwBYZh2KyW1OfvAURLGIZhs1pSn78HEC1h2IHZHNnxbXPydXkXpu1SHpbU5+8BREsYltZGVxFk6d/FsC8Op7akPn8PyDRamroERs6XLHZkhiwNNc1diMzLkzXKh/YTkWO0FFkCo6W6A788vG0eNvdlWb5uVs+itoVW7cJpxVvYwm1ooRfg8NTa8BxgXP0OY2Gwfod4Y174Ar0h46C8rfvGUxuQ2HO0+Evm7BArx1Uk2evx9Lm20kDkF3Ya0sdTab2TpWr/gRuh1yArrRv5kZVjL8NDt9M5sm4uPTfYnUwhNpMPibekPn8PyC1aCpbAENnzOmu8RpNNtd5D81tGr3YhnIL2v9t++mnFMrb103MjaclnjaocvZMEbunnv9+eS+2npd26ZzzVAYk9R8Ygdwk1elUk2dfx9EkXl58AAAgVSURBVF/zejL70LFbXbJbr3fozUK50yD7zrtw3IGFw86Rt2+uu2hHQI75bD4k1pL6/D0gp2hpawkMqRbGj+7mknp+kl518/Doq3bRmShXoRe2cBry3CSefmrmcTRKP+tf08LvbE+pbv26V/rpDILWuj6e+oDEniNdlvpVJNnX8bQGRDhTXZaCySG18ezscfVaWoc5fJCV1mWmrnaU1IXDzpG+UHcX5qUVvjcn8CGRltTn7wE5RkveEhjqj275S8e9pII57uxfOkphCz2EGl+Wwrn4qvvn+WkxkRvVWvfIkjogsedoYcycuGHTtlHa5/H0W6Qs+UZel6X7OzOT1tBB1lofKEvR58i/0HUXalsz+pA4S+rz94CcoiVxVemTD+0lZRW0DVxS/jR36rywXdhCa8jvNTyy5GQl92wedBDasZuTTtVfql/KgX4+rl7VSSdfpSv3l6M7ILHnqBH+qGP3esz9HM/wBe8+LwlMNoqRV1s3CmOKp2UDBtl3Nt1RUhcOPEfBhfaNrFxjs/qQGEvq8/eA3KKl2swSGJ5Z/noyZHMfuqT0ahfet2g0l2c15L/HdFkyHjsHfIHSz2Y2pixL65evM5/wpXuiG+6ntVvtMfXr5ot/PLUBiT1HcmG4dX/n93U8Qxe8U2PF93zF7ZLWugi/7n6W2nsluw2y23o7Svd3T+GFw86R58Qp7kKtozavD4mwpD5/D8gxWkppoxa2wJThFYKtVmLEsN0t409opSX1+XtAptFSIhu5sAVmmyFLjDZ2pJbU5+8ByFJtUxS2wBwzZmMYbew4LanP3wOYxMMO0JLeUwAwCKIl7AAt6T0FAIMgWsIO0JLeUwAwiIOKlto3PnmQPrLt9IJTwtOR9J4CgEEcXrSUIn3yzP2RSVOML3/tj2+UlApNl3qpxYBPNNKcjqT3FAAMItNoaUBhi9394DTVLkb3y2puJD0/pjGeXV7Ut9Xf3l6NXSMgzelIek8BwCByjJZkSg+z3kT3AaYvyb/jBz3JF6KrXUQXd1By7/vKFvQrMWAnnuiKbnQf/4qvgN3v8zWx0dVia42AtKcDWQI4BnKLltTCFu1PdRkoSDGQC2P8YGym+j7FHUKZabyJI2NKDDj5kDoZkGrx/NTuZNVlT3i6NzOmBHsVWSMg2elAlgCOgZyiJU+mellvovvJr9WbiPWD0Znq+xR30BPyKwIwtMRAl52zVbKqn23pHSWpj11mxuxVjxoBKU8HsgRwDOQYLdmevU4JLH+2B0r2RfjB6Ez1fYo7SB8qD8GRpYElBowWm0dKMiOnPkFnRSF6tBRRIyDl6UCWAI6BnKIl4QpNP/W4en1b3Yl89Z56Ex4/6KbZj81U36e4g0853NhltBIDWiEGT/1N2/XHPVvS61AkOx3IEsAxkFu0ZOmBxzXrafaNfGvt+mqFgshM9X2KO/hz77uvbvcpMeAeu3yTQnvhQgYxdivGQrer22sEpDwdyBLAMZBjtIRlYXtSI0C1pPcUAAwi02gJw4ZY0nsKAAaBLGEHaEnvKQAYBLI0oZX/vSn/e7P43//DMAzDYg1ZQpYwDMMyMmQJWcIwDMvI0svSPr/xhSxhGIaNbMllaZq83bvZyNm+kSUMw7DeNqcsjV00IZksRUopsoRhGNbbZpOlrUUTqoRpqy4LwGO7oVLxQSmFoG8eWUVCLUJh1nEQFSXi8uIgSxiGYb3NJ0sWw2QpvmhCky3USrNmZejx5oVzN+9VRUJNYOrNyro1iyiyhGEY1tsmj5Z6FE2QEtIphJsszpoMbFbQNu9XRUKZxJN1HBRlDdZcQJYwDMN62yyTeJFFEyaQpX5VJLRnS3UWbaXkHdEShmHY+Jbs2ZJSNEG4flGdQS/5o0/iuZv3qyKh5sz+9vy2evhpySrPljAMwyaxVG/iaQIgay50M2O6hHTlULU6DnJirVcVCaU8hF5agjfxMAzDJrE03y3pn9AqE2V9bODmfguWT0WWMAzDxrTkn9NmL0ve2qnIEoZh2PiGLAWsKrq6cxIKZAnDMKy39ZIlAACASUGWAAAgI5AlAADIiKlkafl1fXr78sefy7E6+umqPL0tT2/L06tL0UT5+fxsrCZ6kbZ1AIBDZRJZWi7P/vje6cdwPp6/uCI3jzD4jgVZAgCYgqGypHrt5Z83n2/Lk6/jhkrrT8vRdhjP6BJbVIfz/eZjisMBAMicQbK0XF6e3JZuHGO53dqzV1NwzcpVtFFZFXPUYna1tibrCkeW5A5lvCL3We2h2me9/6/r09vy5Ouy2vzz+dnH85fT23rPZifrTbqZQ9H5mNbDR1QtTyW0AAA506+whaT2rc6vfitUapy44YJ1tRDOup21a5TDVjVrJ0WjkdU/P56/1GITkKWr9cn5mbWTCjln6J3Es1qPPiJzWMZ8/AYAcADosqQiN6sjA21qq5WEek2v36/XaeVE9ezV+uok3kBZcndoSmA/Wep7ROK4xpztBADYd3aUpcIzEyW1Qa42gywV5pxbtW1IlqznYeIVhh2ipb5HRLQEAKCyuywV2rMlK1QqfJN4mgYMjZb+vPnsvq3XrNM+EArLkoilTFnyzFV2rfc5Ip4tAQD4GCRLhRlMeAOLWr2MyTE5YxaIbKo9OK88yB12ezDfUKjXbxeenNcPvXRZEi8ynJwbCifeZaheedBbjz8i3sQDAPAxVJYko39C2wvZeq0co77VDQAAMzCmLKXFeCCkPdACAID8ORxZUj88AgCA/eJwZAkAAA4AZAkAADLi/wGmACQDNlXGWAAAAABJRU5ErkJggg==" alt="" />

(3)问题解决

再次运行wordcount程序成功:

[hadoop@master hadoop-2.7.2]$ /opt/module/hadoop-2.7.2/bin/hadoop jar /opt/module/hadoop-2.7.2/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.7.2.jar  wordcount  /wc/mytemp/123 /wc/mytemp/output
16/07/27 03:33:29 INFO client.RMProxy: Connecting to ResourceManager at master/172.16.95.100:8032
16/07/27 03:33:31 INFO input.FileInputFormat: Total input paths to process : 1
16/07/27 03:33:31 INFO mapreduce.JobSubmitter: number of splits:1
16/07/27 03:33:32 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1469604761767_0001
16/07/27 03:33:32 INFO impl.YarnClientImpl: Submitted application application_1469604761767_0001
16/07/27 03:33:32 INFO mapreduce.Job: The url to track the job: http://master:8088/proxy/application_1469604761767_0001/
16/07/27 03:33:32 INFO mapreduce.Job: Running job: job_1469604761767_0001
16/07/27 03:33:47 INFO mapreduce.Job: Job job_1469604761767_0001 running in uber mode : false
16/07/27 03:33:47 INFO mapreduce.Job:  map 0% reduce 0%
16/07/27 03:33:55 INFO mapreduce.Job:  map 100% reduce 0%
16/07/27 03:34:08 INFO mapreduce.Job:  map 100% reduce 100%
16/07/27 03:34:08 INFO mapreduce.Job: Job job_1469604761767_0001 completed successfully
16/07/27 03:34:08 INFO mapreduce.Job: Counters: 49
        File System Counters
                FILE: Number of bytes read=1291
                FILE: Number of bytes written=237185
                FILE: Number of read operations=0
                FILE: Number of large read operations=0
                FILE: Number of write operations=0
                HDFS: Number of bytes read=1498
                HDFS: Number of bytes written=1035
                HDFS: Number of read operations=6
                HDFS: Number of large read operations=0
                HDFS: Number of write operations=2
        Job Counters
                Launched map tasks=1
                Launched reduce tasks=1
                Data-local map tasks=1
                Total time spent by all maps in occupied slots (ms)=6738
                Total time spent by all reduces in occupied slots (ms)=9139
                Total time spent by all map tasks (ms)=6738
                Total time spent by all reduce tasks (ms)=9139
                Total vcore-milliseconds taken by all map tasks=6738

用如下命令可以查看统计结果:

aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAwAAAAGqCAIAAAAz+7R4AAAgAElEQVR4nO3d25HquhYF0A7rFAFRdbIhhBMFyRDK/ej7QQOyrSVL4Cceo/bHbmNkYcCeyI/1899///3777+/iev5p+N8fU7++29v7tPldj2fLrfr+ed8/b2eT5dbezvh/HO3M63b5fTz9/pH9Pp/u5yef94up0E/ew0/Z++vhsff0fTeA5X9ffbo9cxOO0nvo/b7q/8nmZ55K6LXW/gcVrzein7uy2BtpJ+j3+h1Xc8/+Vcbfqn6Bu2OLHfYcK8P9+3I44Hh97Tc/u1yGrye4vc9eL9z7cQr4P31HHjNn3Skt6TRJroLDLfPI291vp3uhid5w7JvUnYRwXYgbH/ke5rpZ9t2oNTPaDvW0k7Qz9Lrym3/S43nH5pmvxl9zueevpSfYQAKFHZU58vldN/pni7X+3+b22k2VTsTatpURQHodjl1Q1s5AEV7mnAP1F1u21pMN+idZyZ/RO1HH+2JAlDd663o577kg8Xo64o+qXWrIfvs8nKHDffesNf+NFBq/75rrxZ+T1va+Wg9j/WsuwtMfi6MP7+3uHD7XNzVDNspBKBnU/33MLtSguVWBqDhVjPzepu2A1E/o1la2wn6WdxOZrb/7QEo0Lqlq1oPM0xfyMcB6C84PnbGp9PYT6ivDUCNP/eiAJQ2k34Z0v8n6zzz26E8/Xr+ybYZuF2v+d/xr/b/ttZp33Lt3y6n3AqK3sfo9ZbmL6+Hyn7uSmZtJCuiFDrz4x8VqyH6nBeXm3vXkoZqfviF7dcP2xT739rOW+v5/hmMhwkyXWsIUYNhht/C9rnQlUw7pQD01/FTv5/51ZLfDhQDUPQ9zb3e1u1A1M9oua3tRP2M2o+2/4X9XdOwSfN+M/qczz19GZ8HoPSBmi3otwag/gji2BsZBaC0pdPlmm6lng+cr52tYvp7MV0l2enX88/P+Xyu7GXvt+jgB97fxF7vo/ZzjY38shm83pENQWY9tPdz+8pDBK9PUO8TNvYxqVgNpc/5cLnlfiaPVn2Vw9fVsCEI+986WlPqT3Y9vx7sTC3O39KvzDDDo5PB9jl7rCXfTjkAlX7dZD4nme1AeQQo+z0NXm/jdiDqZ7zctnaifo63393+F/d3wXqOZm3db2Y/5wtMX0B9AOI7zB0c52l/9AjJOy1uKkDDR3LDDIu1M9+3qfDDe9ZfLZO9oqCftj+bIAAdzR4D0ByHqGyA+CKNp0FN286chy6C7+lUr7d1uW80k2/F9mcTBKCj2U0AGjs08CEbIPjU4+DFfN+ktb6nu9lO8okgAKU7n8HFju944wD7l7M+yzIfwf7jk66Ax0+1sfel8Vz35vbLFn7fx96EL7Dq0MkK9BOeCgGo9/Hb4IY7Ovl3Fza4PvPSs0bfOEl2tJtj7WdO/5l+cOgVp+YJQPXtj7az3Ed9hYsyljZVjJ46js9FP+f0xScLf6v9BqDOjmie/cKso5RbW5+h67VztVnLUqt6Odb+IADd19ykm8jkRMVZ3vTJ2l80AO3lKMD77ax64nDy7KX2aNvo53g785zgPO96/u7Lxb9VcwDKhNDOb/789bXny2eXbV+fy3h9BDo3Y3g+43r+OV0uf/e+uD+YXtiYW25nPCE54BcPZOQu333uluOxjA2vzzqNX7zmzVh0Q45BALpfgTrVxqzTVPQ+Ris5fh9L7W/8fc9cvZ5f7Lvb4ebvV/c662dULrcz4vW+5HLl7dK7ZU74itP3N7/9yXyw75Muresh3L5VvL/9r0zhc5LM8Txwm+9ntNzWdqJ+xq8r/33Jf3/bPydvbs8Hf809nY+0BaDB5/4+8y2540H3G9DJHvfZB6l2ZPr1nCz20eZj45TmoGT28/W1wXztP/P9LHyU8g+l4xRJQ/d+PntT9YXZzPqs1PS1e+Mgfrb94SGw+3t7mioAdXNa+j7m1k+/j/H7WGp/F+979HZMtelt+n4lD/TjxJtdSt+X54fstWYen9/gFjf5dsLtT+5jU/jMhOsh3L6Nv7/dz2HpczIMLnE/o+W2thP1M35d8fY82A63br5atue9PeazR3NP5zNvHwLLj8UnM3Xnf84ebbzCjdqwndOjrE13HCgZAYpv2DXsZ2H7lv3CdDvaWXDTVnhT67Omw23fufYBmqj97BvYzSmf6Hd0bP2U9mS/mfex3P6m3/fw8z/Rtrfp+/Va9qnmNtOjuu/LYznX8+l8PqXblrE11Xt/w+3PIHB00lf1egjbH3t/e/2s+5xUBqDcct8NQK3fx/5MzT9oA40fqmizMPd0PjNJAOoOmGd+iPbGQJve4IoAdLuc/7Za5QCU62fvFZT2Va+JXZkvfIVNrc/cC+vvxlv2ejVDYP0nRO3nA9Dv7XI6n9sGsPKtF0d4Pg5AI+1v4H2PxR/p/PclbiX/uWr6fiUL7nf8nZ2BoqE1n5PlA5CioUaAlvR5AEpHanvf8dyG+8Nfrsl2/vno4yD7z8/P+Vr8BZbp5+A19oazR36Zhetn1LbWZ1F+lKL82lrmL7dfCEDX6MGGJfcXPLZ+mgLQaPubft9HZ+p9X1o1fb8ej93LB4z/UCkavi+3i6Khw89JxYcmmqW1naCf4VOj7flKI0B162GG6Xzk8wCUbgTTD2X6/3tozmxQkpmi6ddkexfN3u1mvIHI9DMs9hkuIzgGMFUAWml9ljsaHyLMb7pb5h/bi/Z3F3+H/m+XU68kWvEVBIE3/z6W1k9LAIra38X7nv9Il74vrZq+X8nS+t1v/jmsaGjN5+f5o7LYz2i5re1E/Yzaj74vhc9k0+ek+bOdtD5Yt3NO5xNTHAJ7jQkuW7wzmr00BD3oZ9pIfnB9ZMnTHwJba33G/Uz1Rsgyu8gwlGTnL7T/nKEbgDorv2aVx0EtG4p+kotzxoNu/D6G7e/ifc+81H7bn58LVP/96u7T+6EkaCcv/76krzaXsIYfuWw75QBU+vVUtx7KI0CKhpa3ww2fk3fC/av57jPnns7b6gPQWgz2TWt367MfgP6Em/X6duf9ETV3+412977PRdHQZZbb3lAwKuRzy2zqS2GsxRdgWntZnzN/BK8z32l/7vab7eV9n9lU78tb7cx56CJ4f2f/HE70uQr76XPLjLZfDNUXYFrW5zF539f0OHgx3zuw1vs793J9bpnR9gMQAMDEwgB07d1q0PR9Tl9HeukGrOd///zjn3/Pf2t/HtmWKAA9TjHtn5lm+r6mL+1xyevZwDVbsPoe179N/Vv788i2xCdBP66t7OzGTN/X9NU4cs8mrL7H9W9T/9b+PLItwwDUvy9LcgMK03c0fV0CEJuw+h7Xv039W/vzyLZkR4C2No5h+nvTVyQAsQmr73H929S/tT+PbEs/AG1tHMP0PY7/CEBsxOp7XP829W/tzyPbkhsB+juRdnCrXdP3NX1NAhCbsPoe179N/Vv788i2ZALQ1i7kNv296asSgADYtGEAep1QMrjQ2vQdTV/HrVO+cTuH5ACgw52gAYDDEYAAgMMRgACAwxGAAIDDaSyGupcil3vpJwCwhtpiqHspcrmXfgIAK2oshrqb+7vspZ8AwArqi6G+Ht1DsNhLPwGAFTQVQ/3dT7DYSz8BgBXUFkNNH99DsNhLPwGAFbQUQ70/to9gsZd+AgAraCiG+nhwF8FiL/0EAFZQWwx1L0Uu99JPAGBF7gQNAByOAAQAHI4ABAAcjgAEABxO/iqw6ATi10O9K6zC4qNJYxUnI+faH9yZaOzirkL/W/uzmmB9husfAGiRC0DXx871djklu9rb5fQIDa//loqPdp8+Ktv+cJbRBqP+t/ZnFYX1WbF+AIAq5UNg6Y62e2ed/n12MvfdabwVT7n9v4mNe/1OUNjVrYGGna1YPwBAnXIASnazvcGX/hjEcId8f8LzoM1YdBlp/zdbmWxM2qvG/qxssD7H1w8AUKsQgLr72JEhn/yIRSc+lePL2JBStjBHUS8jNPZnZYP1WTHkBgBUigLQYISheQToev7p5Y+/v/pnNd+fVm4/V5cj307U/7g/m2QECABmlA1A2XONW88BGg7AlHfYpfYbj35l+9/an3U5BwgAZhRcBh9dghVehZTbIScN1QxYhO3ny7KGov639mdVmfXpKjAAmMowAPWPLPUPdHWPN5WLjyaPVg1XZO9zU3Xte13/W/uzvPL6dB8gAJiEO0EDAIcjAAEAhyMAAQCHIwABjPvfP//MNPMGO7BM/8tL6T36RpfmeBV8k5ZiqOkDlSfhTlHUM+pPsejpu/0ZXtvWtoCJhMVlgSVk9531O9TRXXvNv6jNppkLi3uv8zUvobJZAYh1NRRDTWeJrjR/mrCoZ9Sfin5W9yd3g+ho+qxKxWWBBbXusHuzNc1c034agEY7NtpsfUxpVb+4+gBUyFjRQ9IPo+qLoZan33fc+bGVlhv6Re209icS1SwbPh5NX4YbHcLKnjnm7XGOyqGUyvnnDkCtr3S0n4WWs9MLjdSPBjWNk3Fw1cVQU5k781QHoJGSDuUAFMWC+rgwFshe/YmmL0MAgo1qOnhUyEmVR5GG0yeZv6mrpdXRvhKyI2SFeXrz18TE+sDEkVUXQ/39/X2dE1MfBSYs6vn58E9+cenxvLRiajR9EQIQbEXl3rRpenZ3Xt7HTzIC1JTeRp9SOX9rAOpFt+H00aULQNSoLobaMX4OUDrnFEU9J0k/uf48Gvk7J/uSthdNX4AABOuIhlV6/xk+q/7PqMFyxPmmADS6QoajPtn/Z5c+zEACEFn1xVAb5/gzSVHPaGmNRTJqlvf5QbZpCECwsppxi9+x3Xk0W/0hsN780XOzHSgfAsvmkprGR/tfsyZ/ixml1/Psc3v/780sADGqoRhqcZb6k6DLV4Fl2on6U+xnQ38qHl0+jghAsLKaWFP/3E9mHqaZ4RMLoyxzjAC1vsAoIUXDWtlRnLd7KACR1VAMtVOns79z7geOd4t6DoNL1J9S0dOm/qQPDS9Iy3dzNuX1BiymcgSo5rnDR2v+RYsu/CdtPNuZtQJQ9GdNACq8nJqeSz9EvvdO0Nez6AC87Y0M0TRPds7C3r0Qd8rN9g4nFQ5UVR7SanqBw5lrGoyyS1NnBCDKvjUAvXF6EMBLNDiRndI6Q3a20XGj4Ww1wzbZHNA6jlI5c6EDTQ2WD4HVDClV9pMj+9YABPCRwvjBJAGoN75S32Zrnth7AKo8BDYcrDICRJkABND34b6z9QhRdKQp22Z2dKQ883CehQNQ6zG1aJ766a1HLTmgAxVDjefvnE+dX8TC90B0AjSsp7zzLu/Ihy2MLivNKIVme7NF7fTi0bDxaCmtL7O8ZipHgKKgOXxK09quj3cc2VGKoRbnv56jgh8t/ZxK6+sCtqZmgKQm62QnvnewbNoRoAmNvtjWDqz1QtidoxVDzc6fDUBv3LBxcktXIAOAgzhaMdTs/LkjXW+W7JiW2yECwCyOVgy1OH96xtL7/ZyK4R8AmMvRiqGOzP/q7sojQNIPAMzoUMVQx+dPurPiOUDu4ggA8zpQMdTKS9eez1ntKrDq4TUA4D1HKYZamj/pa3DO05Kn/5RfFwAwge+9E7RiqABA4FsDkNNoAIDQtwYgAICQAAQAHM6Oi6F2H6o+3ydXYCvsT9D/2a21XAA4hh0XQ02fXH3Kz6NfvfJjg/4U+j+rtZYLAIey42KoaeipDEC3y+l0uXbnLfdnrWpcqoABwIx2XQz1fuTqfK284v12OZ0ut14PRvojAAHAF9p1MdT4Dob5p7+OblUP+QhAAPCFdlwMNRn3uV1OIx16xp9+D4wAAcDx7LcYaveZI0GqUJnDOUAAcDj7LYbauSRscL1a4Vyifpwq9kcAAoAvtN9iqL2HKk/K/s2OJw37U+7/fNZaLgAcyvfeCVoxVAAg8K0BSDFUACD0rQEIACAkAAEAh6MYatifwnJnpxgqAMxJMdSwPxXrYXqKoQLAAhRDrbkxY+39qqfjPkAAMCPFUGtKcywfRwQgAJiRYqij/Vl++CfbDQBgMoqhjo9IrXE/RQEIAGakGGqhPyveTVEAAoAZKYYaXwVWPcw1AwEIAGakGGrUn8JyZ6QYKgAs4HvvBK0YKgAQ+NYApBgqABD61gAEABASgACAw9lBMdTCctva6bWVXgcfnHDc3v5EFEMFgDntoBhqtNzmdoKXU1FsdbnbISqGCgAL2G8x1OYbKlbM8lH7k3IfIACY0a6KoRbqv4+P0dyf8DyolZ056e2bJTumIgABwIz2UQw1s9zmdh6l439/f/NHw7qv9/2irZMQgABgRnsphjpYbnM7vT737pM4eL4RIAD4Xrsohppdbms7vQiTBqCKYqvOAQKAL7KDYqjRcpvb6Y0fpWc7j5zpvfT4jwAEALPafjHU0nKb2uk29XyoVPR0+fsAKYYKAAv43jtBK4YKAAS+NQAphgoAhL41AAEAhAQgAOBwFEMtTO+cH73oCUWKoQLAnBRDLb/MpUOIYqgAsADFUAtPXSEAJYsWgABgLoqhFoqkLn8boM6iBSAAmIliqKNFUlc5I0cAAoAZKYZaLpIavYy5CUAAMCPFUAtFUksvY2YCEADMSDHUeHq3MYfAAOBrKIYaT0+mLnYTIMVQAWAB33snaMVQAYDAtwYgxVABgNC3BiAAgJAABAAcjmKo3an5G0EvfkWWYqgAMCfFUNPThaIXXH/jx08phgoAC1AMtXu6dH6m1qD2OfcBAoAZKYba7WG2nRUuKROAAGBGiqF2jm91Znrn9U5FAAKAGSmG+pvefvl8ybaz3DlA6RIFIACYiWKoY/3tL3cZAhAAzEgx1JHeBq93bgIQAMxIMdRO+8ML0ha+D5BiqACwgO+9E7RiqABA4FsDkGKoAEDoWwMQAEBIAAIADmffxVBbi4ZGy80XQ+0te8kzihRDBYA57bUY6htFQ6PlhsVQw5c/I8VQAWAB+y2GGrUfiZYbFkNd9VY87gMEADPabTHUcg9Hn/tablQMNSqeugwBCABmtNtiqC1PLy83KIYaFk9dhAAEADPabTHUqP1IabnZYqiF4qkLEIAAYEb7LYba+vy65XbPDRKAAOAr7bgYatR+1E7F1WfDkPTm5WofE4AAYEZ7LYY6VjQ0H6Syy42KoXYfWiiNKIYKAAv43jtBK4YKAAS+NQAphgoAhL41AAEAhAQgAOBwFEPtTh9eY7bKmciKoQLAnBRDDYuhhkVS56QYKgAsQDHUqBhqWCR1Ee4DBAAzUgw1KoYaTV+GAAQAM1IMNSqGGk5fhAAEADNSDPU3KIZamL4AAQgAZqQY6lh/3+rnxwQgAJiRYqgjvS1On48ABAAzUgw1LIZaKJI6H8VQAWAB33snaMVQAYDAtwYgxVABgNC3BiAAgJAABAAcTj4AJSdCB+VQ+/cUbJm+AMVEAYBYJgCl14inp9JUXkbeMn16iokCAKOCAJSpiF5zI8H64qlzcx8dACCUPQT2qHyVXkleU8IiuvRqhUuyBCAAIBSWwuifAlQsYhoVK20vnjoVAQgACOVLYaSnAP39UVXEdP1zgNIlCkAAQFa+FEa3pMU9ulQVE93MQTABCAAIDQPQ7XLqldz6+2MXV4GlSxSAAICswknQmRv4jBYTrZk+K8VEAYBR7gQNAByOAAQAHI4ABAAcjgAEAByOYqgAwOEohgoAHM5axVDvQWW+iOI+QABAaK1iqAIQALAaxVABgMNRDBUAOBzFUAGAw1mrGKpzgACA1axVDHWuAKQYKgAwyp2gAYDDEYAAgMMRgACAwxGAAIDDmaIYas38K9wGyFVgAEDeBMVQK+Zf7j5AiqECAKMmKIYazB/+fxHuAwQAhCYphpqbvzR9AQIQABCapBhqbv7S9AUIQABAaIJiqPn54+mLEIAAgNDnxVDr5o+qh81FAAIAQp8XQ43mD9tZhAAEAIQmKIYazx+2Mx/FUAGAUe4EDQAcjgAEAByOAAQAHM67ASi6tfNw+vXsNBwAYFO+NAAphgoAxKIANHbrwvoAtCzFUAGAUUEAup5/zudBBa/XNebnSxp0stPTC9IzNTRyV9S/nnI6nz8LUu4DBACE8gHoen5klCREpMey0kNM0fTkaZmbAz0mdW8pXWinjQAEAIRyAeh2OWXqfw1LW0SlMMYDUK+o2Pla0U4bAQgACGUC0DP/hNUvfpOAEk1/qgxAo+20EYAAgFBQC2xYSkIAAgC+xSAA3U//6fz9SjrpaT+5oqfp9EED+b87SarUThsBCAAI9QPQcOAliRLPK7fO18HpQbnp/efn/k6fUGynjmKoAMCorZbCuA6uwQcAmMg2A1B6OAwAYGIbCkCdo1fSDwAwmw0FoI26XU4fpbE01y15VG+t08DXer1bVVsLb9L3y5sAMEYASopyDHYWUw5K9a7zn93a18Et/Xq3aoUA9K2rPqquk62rU7Ld+bvvW9TO+Pwfvv+KSXMMwwBUuCNztI1u3XankWP9n6jXa6em2euF3F9WZgTorf5PsFcqrf9BbzYYgLL9XNHnqyh3sWJyI9GW5RY60/p5m+r7ONVHaJJ2OkEyXe/x3VrzNjx/1euqmP/926gpJs2h1Aag3jby+fsgmv5o5/l49vvbl/zE66Wu5yPhpiW9bqy+neHyXw/cW+wHoNb+l54Xzd8ZeTpdboX1fJ81va/ArROAMj8iO2310+1g/kLx2pbXG/az93Jn6U/D+hzpT//zk7la8e9OWvnhirHvy/B1xZ+3zPuYuQvE2PrJt19aP6XPT2b9lF/vqxOd97e/3eiU5+k01N1ejWetdecffA2GIWbsdQXzh/9/y9o/n2AR840AdW5mmPx8Czfo6fhLMtO9nefWL/p5+rqBY2M7hRdyu5x+fk6nygAULDd8XjT/fakV3QsmJY/k9zev6JEuNpo/bKfp9cb9HPy67Ubrz/vTtD7H+tP//Dz/9/yE9z9btW9a9LriAJR/H6P2o/VTCPTBm1b6/GS/X+MjXr0d/2C78WgwzUGvd733lS2Ouaw8fyYAvV5y/zdc1E5u/tL0NwhAHEI+AAW//ZoDUDdI9Xa1P8M88Jrw+v6HX8XeL55M/bK6dvId6K6O/JH2qv5HzUfzN+2QOscFijPnfxMmM0XzR9ObXm/cz/7L7QSdKfrTuIOv7U/y+Pma7rav0a3Uy8stvF/5z1vhyePBrvN+he03DXcUZm4OQIPtxmtU7TUOlP9aj/V5a/P//nYG5sLDj+nfuflL098gAHEI844A5QNQZ5bCYPnrp3U8dvDcyfV+HrW0E/bv8cj5nN9/V/U/WsIb/ZwqAHUPlLwZgJpeb9zPcEM/VX8ad8y1/UmW/7eDvlxOP+frYHDx8wDUmeWnl2IG72Op/dL7lWk/WnU1n5+219sWgG6X8/m8zxGgjGS8JhmsjNvJzx9Pf4sAxCEsFYBK29LXNz73nS19Ff++850f3W+0kx8deT14vqZbl8b+R/2K5m8bsahOFp2Rks6P/0lGgMZeb9jPmUaA4gUkphgB+v3LPqfL7XY5nS6X3gDQlAHot/95y72PUfsVu+L+XGE7FZ+fwkvLTAzbefz1+Ipfz/eI9pfB7t/Miu1M1Jmtzf9a/1E7dfPXvdu1vYIv1RSAmvYx1/Pr12G60byeg5Hd4GdL8at4Pf+cLpfzcCC4oZ1o3/x3qsPtcuqUJmvtf9qtmn7mTxPIN/GcOxieigJE55fimwGo8fWG/ezMl3Rosv60rc/a/vSaP11uwxGU3+B54fcl/3rzn7fofQy7Gn4vgs9zoZ8Vn5/R19uLcp12MtuN4hBtcD7T/f0oRNyF5//NfRg77136R9BONH/YzlsEIA6hKQB1xtHzp8X0LsM+nwdz94biO9+y7th67aGr/Ma1tp3+oYHuzm/Yz9b+p4/l08tw/ujYRrD+u10aCTTp7KfL9blBbg4c7a83289eM7lBgY/707g+a/rTe1WvUFI93NNbbun1jnU+fR9LXY2+F/n2o/VT9fkZfb2viX8DOmnnM9uN4G3pNd+Zng8o683/mwtA3bWTW0BhcveBsJ163U/I4C2A7zLfjRC/5TfE7cM7QQP1vmW7AWyeAARsh+0GsBABCNgO2w1gIWqBAQCH86UBKHc26m/p5EQA4EAq7gSdXJ3RvfIoufIle9VAdMnYnB6X1GaK+RUvTwUADiQcAbr27/zXu8lJJwAFV4JW3Ah4LsNetd6gDAD4Wk0B6HTq3PesEIAGN+JaOnAMlhffWh4AOJqmAHS/I/Lz/myFAJTNH0sGjkEH+hMMAQHAcTUGoNfYTnQOUHDb5dUDkBEgAOChOQA9ItB5Z4fAnAMEADy8EYB61Qv3chK0q8AAgD9Nl8H3yleWq2Svehl8UMzPfYAAgN+vvREiAEBMAAIADkcAAgAORwACAA7nCwNQeha3S70AgKG2Yqj5a6u6D62eOa7XxxVeg7sRAQD8thZDPafR4v7w/brz9B7Lt+0MurjfDwCQ8WYAev617Tsqb7t3AMBK3gtAz2NLy9/iuZ7hHwAgry0AZU8M2mTIkH4AgNC7h8DSqZsLGr3K7wAAHZ8GoL+ToLeUgTaZyQCADWm7DD4YVskeHVtLv/+yEADQ84U3QgQAKBOAAIDDEYAAgMNZKgC5MAsA2IwvDUDX8/pnYwMAWzV2FdhU11AtFYDuV+X/nM+KYAAAkXwAekSH/i11/uJF72L3TmRKU8dr9vOlE4By7dyX+3zkw+SlChgAECoHoGfNr/4fnUoTr/rvnclpekoPSQXt3GPUs8S8AAQAzKUYgDoDQN3qWsEhrd6Tu2M+97+idqaNLAIQABAqnwOURojBHaK72aj/pF410m7QybUjAAEAC4lHgG6X008/wuSOS3UOk71yRxiAonYEIABgIcVDYJ1sM0hEyfyPqf3Te9LDYd0H8u0IQADAAsonQf9Fl+BYV+cM578p18vpp5d7fh5Xd2WvApv4EFi35Umv5AcAvoVSGADA4QhAAMDhCEAAwOHsLQApqgoAfEwA2iTFXCYZJgMAAAnCSURBVAFgTksVQ53KtwcgxVwBYAFTFEPtXHreKQV2vj7jVNBMvxhqkr9yV81/XFT1ll6mv2HuYwQAM/q8GGq0q+7c/DBJUt06qq82/5LP8J7SkxZVFYAAgAmKoQY3ds4UQz1dbsNKGM/Zerv85wLWLaq6lu94FQCwUZMUQ02ORXXvIZ0JQP09+1gAWrmo6lq+41UAwEZ9Xgw11T9alYlDrSNAKxdVXct3vAoA2KiPi6HertdMmvmtOl1ncA5Q7hDYtEVVnQMEAHxeDDVfH/XRzjl3EVjxKrB0nk6Wus/8aVHVrQcgxVwBYAHz3QjRGAYAsFECEABwOAIQAHA4e6sFBgDwsS8MQOkNgpxADAAMZQNQ7x6DO0sR12vnwn2H4QCAnmEAKt3wsL746LCV6zl7OX1lEdP31Ny8EQA4nIYA1Fh8tHcS9PX8URHT9zgRGwDIyB0Cu4Z3L2wqPpreszBJNIsVMTX8AwDkFU+CTgdl3ig+2qnb1RkZamvnHdIPABAauwrsFSTeKT76d97P6/DXm+006tbLAADoytUCS7NDvzRqY/HR6/nndLmch5XAWouYNkhL0gMADOWLoSY6meTN4qPDEvLN7dTrH2KThQCAni+8ESIAQJkABAAcjgAEAByOavAAwOF8aQC6nvvnbwMAPMxXDPWNADRBZvq7vux8Nv4EAESaiqGmV6/Hl8cnd47uVDrtFcDotjO8P/Rn8cUBOAAgVB+AOtP7BU2LNzZM68Bnnvt6bMLUIgABAKHqYqj9XPRMGOXSFsOqFFEx1F8BCABYRnUx1H6ieP4dRY1HjOqHo6gYaqGpNwhAAECouhjqmyNAw8pchXOMBCAAYAn1xVDL5wAN00bnHKA08gTnDPUX8RkBCAAINRVDrbsKLIk9j5nuj2evAuseJEsW/l4S6rb8QUMAwPdSCgMAOBwBCAA4HAEIADicvQWg4X2FAAAafWkAUgwVAIg1FUOd6tryD9oZC0CKoQIAo2prgZWKlXYe69W1eF6WnpRIjdrJFUntTT5fKg+BuQ8QABBqqgYfpIrbLb2/z+O5aR2N2+WUvYt0t5mgSGp6H8XqQ1sCEAAQqi6G+nignCqSOQozZx+KiqR2Z649CVoAAgBC1cVQH3/nUkXuRtDNASgoktobkBKAAICPVRdD/f0tjNw8p042AhRNFoAAgI/VF0P9DTJKeopOGoYKESSfdYIiqf02nQMEAHyoqRhqUKz0NfF0uT5LwxcjSFD0NCiS+pz7flVZxWXwgyNpAABPe7sRIgDAxwQgAOBwBCAA4HC2F4DSk6oBAGYgAG1Oehb6oVcEAMxmb8VQD+B6TW87YEUBwPS2Uww1vYA9cyei1xO7dTH+Wj+f626QuC+FumwAwPs2VAw1ePAv+QzvNf1WkdR9MVQGALPYTjHU6MHe3887Ib5XJHVHDP8AwFy2Uww1ejAIQG/WCNsL6QcAZrSdYqjRgwcMQF/1YgBggzZUDDW3xOHfz3DwXpHUHTj8fQAAYHbbKob6eKgmAKWtjBdJ3Y/+dXKyEABMbns3QnzP9SwpAACVviMAuWMgANBgxwGoc+2Z9AMAVJs6AH1+Lo5zgAGAmQlAm6MYKgDMLX8VWBJhruemQFMVgFR4KFEMFQDmVh+A7tOzZTJeZ+OcL7mr1Hv3h+5SDDXmftAAMIu2ANTJMWkh0mxR0nyR1OEiuhRDfTFUBgCzaB0Bekx+RZqqoqTdmRRDrWH4BwDm8nEAKtXkyhZJHS6iSy2w31/pBwBm9W4Aev4VBpGoSOpwEV0C0He9GADYoMxl8J3E8SoxkZ5mk4abqChpVCT1VzHUssPfBwAAZpe9D1D2gqzr+efnfM5dBBYVJc0XSe09pBhqj2KoADC7+hshbvuKJMVQAYBq3xGA3DEQAGiw4wCkGCoA8J7paoE5dxcA2IkvDUBfemdoAGASUxdDXdvfcbHzeWsH7ACA7WgJQJ2Tbp6DPdssYrq5M5YAgO14907QQ9sqYioAAQCh+gB0u5yKJ/lsq4ipAAQAhBrPAXoevBqGi23V8BKAAIDQeydB5674EoAAgJ2oLoZ6u15v+VmCaesWMRWAAIBQdTHUziVguXOBtlHEtNtN1UQBgIzpboT4HkVMAYDFrRuAFDEFAFawQgBSxBQAWNfnAcjpxgDAznxpAFIMFQCI9QNQ5qKs2+VUOk95WwFIMVQAYFQ/AGWuysqXQ03vFPR3OfuWLjrfViwDADalH4Cewz3Pmz0/p6SXbCX3c77f1Cf5YxMRSAACAEKDc4D+xnte92h+DAB1a1i8bmA4LG66hQQkAAEAoUEAug/4XM8/58vldD+29RoSyt1iWQACAHYmWwz1fLmcTpfb7XI6XS6PM4CiaNONGlsJHlvpBwCwQcMAdD+d+XS59U7vuT8wjEDpFefbubOzAAQAhIJq8Mn5Pf2KpplDYKfL5dyZth7FUAGAUWsXQwUAWJwABAAcjgAEAByOAAQAHM6XBiDFUAGA2LcFIMVQAYBRuQDUuedzr+jpdXC9ezR9Xe4DBACEcgHodksrfj0Szas62G+n6Gk0fV0CEAAQGjkEluSIqOaXWmAAwM5kA1D3dsoCEADwXYJaYI/sEI4Avf5SDBUA2JlsNfhu/dMkAOWKniqGCgDsTPkqsNPlejn95Zvr+e/q8t7FXtH0dSiGCgCMqr8PUDSmYqwFANgZAQgAOBwBCAA4nG8rhQEAMOpLA5BiqABArCkA7eBol2KoAMCo2mKonWndKqmbtIOsBgCspb4Y6u+uUsWOugoALK2+GOrgr03bUVcBgKXVF0P93VWq2FFXAYCl1RdDHfy1aTvqKgCwtPpiqL+DU4K2TAACAEL1xVB7D200CSmGCgCM+tIbIQIAxAQgAOBwBCAA4HA+D0DpWTfp6TbRdACAlU03AhRdIrajS8e2QzFXAJjTGgFo85eSrUgxVwBYQD4AdS4mf4aUXJHU7nMqAlB6m6HOH50799wup3QJSX86V+S3zL8v7mMEADPKBKDb5ZQfmgmLpIbTBtN7d1ZMd/RhoEmfkzTWOv++CEAAMKN8KYzRzJDZP1cFoMHzXo9Ggabb7uuB1vn3RQACgBnlS2EEu96oSOrzwTkCUOfAW3JMrnX+fRGAAGBG9SNAhSKpo89rPgSW/BG12zr/vghAADCj6Byg4d63UCT1Oe2Tk6Bf8z2uhErP6Rm23Dr/vghAADCjiqvAOsM+j4NK10FKqr8MPmm988Cj/dPlFl/V9dO9bqxl/j1QzBUAFrBqKYz73t4OHgBY1uq1wL7igBUAsCurByAAgKXVByDFTQGAL9E+ArSLy8wVEwUAYt8WgBQTBQBG/R9hYde8qO74PQAAAABJRU5ErkJggg==" alt="" />

hadoop2.7.x运行wordcount程序卡住在INFO mapreduce.Job: Running job:job _1469603958907_0002的更多相关文章

  1. (三)配置Hadoop1.2.1+eclipse(Juno版)开发环境,并运行WordCount程序

    配置Hadoop1.2.1+eclipse(Juno版)开发环境,并运行WordCount程序 一.   需求部分 在ubuntu上用Eclipse IDE进行hadoop相关的开发,需要在Eclip ...

  2. 021_在Eclipse Indigo中安装插件hadoop-eclipse-plugin-1.2.1.jar,直接运行wordcount程序

    1.工具介绍 Eclipse Idigo.JDK1.7-32bit.hadoop1.2.1.hadoop-eclipse-plugin-1.2.1.jar(自己网上下载) 2.插件安装步骤 1)将ha ...

  3. hadoop2.6.4运行wordcount

    hadoop用户登录,启动服务: start-dfs.sh && start-yarn.sh 创建输入目录: hadoop df -mkdir /input 把测试文件导入/input ...

  4. Eclipse环境搭建并且运行wordcount程序

    一.安装Hadoop插件 1. 所需环境  hadoop2.0伪分布式环境平台正常运行 所需压缩包:eclipse-jee-luna-SR2-linux-gtk-x86_64.tar.gz 在Linu ...

  5. 解决在windows的eclipse上面运行WordCount程序出现的一系列问题详解

    一.简介 要在Windows下的 Eclipse上调试Hadoop2代码,所以我们在windows下的Eclipse配置hadoop-eclipse-plugin- 2.6.0.jar插件,并在运行H ...

  6. hadoop2.6.5运行wordcount实例

    运行wordcount实例 在/tmp目录下生成两个文本文件,上面随便写两个单词. cd /tmp/ mkdir file cd file/ echo "Hello world" ...

  7. Hadoop2.8.2 运行wordcount

    1 例子jar位置 [hadoop@hadoop02 mapreduce]$ pwd /hadoop/hadoop-2.8.2/share/hadoop/mapreduce [hadoop@hadoo ...

  8. spark运行wordcount程序

    首先提一下spark rdd的五大核心特性: 1.rdd由一系列的分片组成,比如说128m一片,类似于hadoop中的split2.每一个分区都有一个函数去迭代/运行/计算3.一系列的依赖,比如:rd ...

  9. python在mapreduce运行Wordcount程序

    首先脚本文件: mapper.py: #!/usr/bin/env python import sys for line in sys.stdin: line = line.strip() words ...

随机推荐

  1. 第一百五十六节,封装库--JavaScript,延迟加载

    封装库--JavaScript,延迟加载 延迟加载的好处,就是在浏览器视窗外的图片,不加载,拖动鼠标到浏览器视窗内后加载,用户不看的图片就不用加载,可以减少服务器大量流量 将图片的src地址用一张统一 ...

  2. C++学习之拷贝构造函数篇

    一.拷贝构造函数的声明 Array(const Array & arr); 二.拷贝构造函数的实现分为两种,即是深拷贝和浅拷贝. 1.浅拷贝 代码例如以下: class Array { pub ...

  3. 【watcher】 #02 c# 中实现时间戳等,日期数字及大概率绝对随机数 实现

    在Wacher的项目中,用到了很多时间记录的地方,为了将来能够和在线数据打通,我们使用了时间戳来记录时间信息 由于c# 没有现成的方法,所以我们重新写了一个Helper类来帮助我们使用这些公共函数 同 ...

  4. 《C++程序设计》朝花夕拾

      (以后再也不用破Markdown写东西了,直到它有一个统一的标准,不然太乱了--) 函数签名 int f (int a, int b) ↑ ↑ ↑ ↑ 返回类型 函数名 形 式 参 数 其中,函数 ...

  5. Android中的ACCESS_MOCK_LOCATION权限使用Demo

    转载地址:http://mobiarch.wordpress.com/2012/07/17/testing-with-mock-location-data-in-android/ The DDMS t ...

  6. trait优先级 与 使用

    之前一直沒有讲到trait,在此我不得不提一下trait中的优先级: 在trait继承中,优先顺序依次是:来自当前类的成员覆盖了 trait 的方法,而 trait 则覆盖了被继承的方法. For e ...

  7. 如何使用C#操作WinAPI

    Windows API是对Windows操作系统的API函数,在C#中调用Windows API的实质是托管代码对非托管代码的调用. 主要使用的格式就是: using System.Runtime.I ...

  8. java关于Timer schedule执行定时任务 !!!!!!!!!

    1.在应用开发中,经常需要一些周期性的操作,比如每5分钟执行某一操作等.对于这样的操作最方便.高效的实现方式就是使用java.util.Timer工具类. private java.util.Time ...

  9. Codeforces Round #372 (Div. 1) B. Complete The Graph

    题目链接:传送门 题目大意:给你一副无向图,边有权值,初始权值>=0,若权值==0,则需要把它变为一个正整数(不超过1e18),现在问你有没有一种方法, 使图中的边权值都变为正整数的时候,从 S ...

  10. Kubernetes之kubectl常用命令

    最近项目有用到Kubernetes作集群配置,所以学习下相关命令,记录下以备下次使用... kubectl help 显示具体的用法 kubectl controls the Kubernetes c ...