Hadoop中的Context使用
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简要截取：
本篇博客以经典的wordcount程序为例来说明context的用法：
直接上代码：
package MapReduce;import java.io.IOException;import org.apache.hadoop.conf.Configuration;import org.apache.hadoop.fs.FSDataInputStream;import org.apache.hadoop.fs.FileSystem;import org.apache.hadoop.fs.Path;import org.apache.hadoop.io.LongWritable;import org.apache.hadoop.io.Text;import org.apache.hadoop.mapreduce.Counter;import org.apache.hadoop.mapreduce.Job;import org.apache.hadoop.mapreduce.JobID;import org.apache.hadoop.mapreduce.Mapper;import org.apache.hadoop.mapreduce.Reducer;import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;import org.apache.hadoop.mapreduce.lib.input.FileSplit;import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;import org.apache.hadoop.mapreduce.lib.partition.HashPartitioner;import org.apache.zookeeper.common.IOUtils;public class WordCount { public static String path1 = "file:///C:\\word.txt"; public static String path2 = "file:///C:\\dirout\\"; public static void main(String[] args) throws Exception { Configuration conf = new Configuration(); FileSystem fileSystem = FileSystem.get(conf);//获取本地文件系统中的一个fileSystem实例 if(fileSystem.exists(new Path(path2))) { fileSystem.delete(new Path(path2), true); } Job job = Job.getInstance(conf,"wordcount"); //job.setJarByClass(WordCount.class); FileInputFormat.setInputPaths(job, new Path(path1)); job.setInputFormatClass(TextInputFormat.class); job.setMapperClass(MyMapper.class); job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(LongWritable.class); job.setNumReduceTasks(1); job.setPartitionerClass(HashPartitioner.class); job.setReducerClass(MyReducer.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(LongWritable.class); job.setOutputFormatClass(TextOutputFormat.class); FileOutputFormat.setOutputPath(job, new Path(path2)); job.waitForCompletion(true); //查看运行结果： FSDataInputStream fr = fileSystem.open(new Path("file:///C:\\dirout\\part-r-00000")); IOUtils.copyBytes(fr, System.out, 1024, true); } public static class MyMapper extends Mapper<LongWritable, Text, Text, LongWritable> { protected void map(LongWritable k1, Text v1,Context context)throws IOException, InterruptedException { //在这里我们利用context获取日志中的相关数据:键值对信息 LongWritable key = context.getCurrentKey(); System.out.println(v1.toString()+"对应的起始偏移量是："+key.get()); Text value = context.getCurrentValue(); System.out.println("当前文本行是："+value.toString()); //获取当前行文本所对应的文件的信息 FileSplit inputSplit = (FileSplit) context.getInputSplit(); Path path = inputSplit.getPath(); System.out.println(v1.toString()+"对应的文本路径是："+path); String filename = path.getName(); System.out.println(v1.toString()+"对应的文件名是："+filename); System.out.println("----------------------------------------------------------"); //利用context获取计数器,对敏感词汇进行计数 Counter counter = context.getCounter("Sensitive Word", "sensitiveword"); if(v1.toString().contains("fenlie")) { counter.increment(1L); //如果日志当中包含dalai这个敏感词,自定义计数器加1 } String[] splited = v1.toString().split("\t"); for (String string : splited) { context.write(new Text(string),new LongWritable(1L)); } } protected void cleanup(Context context)throws IOException, InterruptedException { String jobName = context.getJobName(); System.out.println("当前运行的jobname是："+jobName); JobID jobID = context.getJobID(); System.out.println("当前运行的jobId是："+jobID); Configuration conf = context.getConfiguration(); System.out.println("运行中读取的配置文件是："+conf); String user = context.getUser(); System.out.println("当前操作用户是："+user); } } public static class MyReducer extends Reducer<Text, LongWritable, Text, LongWritable> { protected void reduce(Text k2, Iterable<LongWritable> v2s,Context context)throws IOException, InterruptedException { long sum = 0L; for (LongWritable v2 : v2s) { sum += v2.get(); } context.write(k2,new LongWritable(sum)); } }}运行结果
2016-07-10 13:29:56,715 INFO [main] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(1009)) - session.id is deprecated. Instead, use dfs.metrics.session-id2016-07-10 13:29:56,719 INFO [main] jvm.JvmMetrics (JvmMetrics.java:init(76)) - Initializing JVM Metrics with processName=JobTracker, sessionId=2016-07-10 13:29:57,138 WARN [main] mapreduce.JobSubmitter (JobSubmitter.java:copyAndConfigureFiles(150)) - Hadoop command-line option parsing not performed. Implement the Tool interface and execute your application with ToolRunner to remedy this.2016-07-10 13:29:57,142 WARN [main] mapreduce.JobSubmitter (JobSubmitter.java:copyAndConfigureFiles(259)) - No job jar file set. User classes may not be found. See Job or Job#setJar(String).2016-07-10 13:29:57,151 INFO [main] input.FileInputFormat (FileInputFormat.java:listStatus(280)) - Total input paths to process : 12016-07-10 13:29:57,202 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:submitJobInternal(396)) - number of splits:12016-07-10 13:29:57,350 INFO [main] mapreduce.JobSubmitter (JobSubmitter.java:printTokens(479)) - Submitting tokens for job: job_local492959629_00012016-07-10 13:29:57,426 WARN [main] conf.Configuration (Configuration.java:loadProperty(2358)) - file:/tmp/hadoop-Administrator/mapred/staging/Administrator492959629/.staging/job_local492959629_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval; Ignoring.2016-07-10 13:29:57,436 WARN [main] conf.Configuration (Configuration.java:loadProperty(2358)) - file:/tmp/hadoop-Administrator/mapred/staging/Administrator492959629/.staging/job_local492959629_0001/job.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts; Ignoring.2016-07-10 13:29:57,648 WARN [main] conf.Configuration (Configuration.java:loadProperty(2358)) - file:/tmp/hadoop-Administrator/mapred/local/localRunner/Administrator/job_local492959629_0001/job_local492959629_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval; Ignoring.2016-07-10 13:29:57,656 WARN [main] conf.Configuration (Configuration.java:loadProperty(2358)) - file:/tmp/hadoop-Administrator/mapred/local/localRunner/Administrator/job_local492959629_0001/job_local492959629_0001.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts; Ignoring.2016-07-10 13:29:57,663 INFO [main] mapreduce.Job (Job.java:submit(1289)) - The url to track the job: http://localhost:8080/2016-07-10 13:29:57,664 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1334)) - Running job: job_local492959629_00012016-07-10 13:29:57,667 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(471)) - OutputCommitter set in config null2016-07-10 13:29:57,673 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:createOutputCommitter(489)) - OutputCommitter is org.apache.hadoop.mapreduce.lib.output.FileOutputCommitter2016-07-10 13:29:57,753 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:runTasks(448)) - Waiting for map tasks2016-07-10 13:29:57,754 INFO [LocalJobRunner Map Task Executor #0] mapred.LocalJobRunner (LocalJobRunner.java:run(224)) - Starting task: attempt_local492959629_0001_m_000000_02016-07-10 13:29:57,788 INFO [LocalJobRunner Map Task Executor #0] util.ProcfsBasedProcessTree (ProcfsBasedProcessTree.java:isAvailable(182)) - ProcfsBasedProcessTree currently is supported only on Linux.2016-07-10 13:29:58,098 INFO [LocalJobRunner Map Task Executor #0] mapred.Task (Task.java:initialize(581)) - Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@3030ff482016-07-10 13:29:58,103 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:runNewMapper(733)) - Processing split: file:/C:/word.txt:0+642016-07-10 13:29:58,115 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:createSortingCollector(388)) - Map output collector class = org.apache.hadoop.mapred.MapTask$MapOutputBuffer2016-07-10 13:29:58,162 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:setEquator(1182)) - (EQUATOR) 0 kvi 26214396(104857584)2016-07-10 13:29:58,162 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:init(975)) - mapreduce.task.io.sort.mb: 1002016-07-10 13:29:58,162 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:init(976)) - soft limit at 838860802016-07-10 13:29:58,163 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:init(977)) - bufstart = 0; bufvoid = 1048576002016-07-10 13:29:58,163 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:init(978)) - kvstart = 26214396; length = 6553600hello you对应的起始偏移量是：0当前文本行是：hello youhello you对应的文本路径是：file:/C:/word.txthello you对应的文件名是：word.txt----------------------------------------------------------hello me对应的起始偏移量是：11当前文本行是：hello mehello me对应的文本路径是：file:/C:/word.txthello me对应的文件名是：word.txt----------------------------------------------------------hello she对应的起始偏移量是：21当前文本行是：hello shehello she对应的文本路径是：file:/C:/word.txthello she对应的文件名是：word.txt----------------------------------------------------------hello he对应的起始偏移量是：32当前文本行是：hello hehello he对应的文本路径是：file:/C:/word.txthello he对应的文件名是：word.txt----------------------------------------------------------hello he对应的起始偏移量是：42当前文本行是：hello hehello he对应的文本路径是：file:/C:/word.txthello he对应的文件名是：word.txt----------------------------------------------------------fenlie hello对应的起始偏移量是：52当前文本行是：fenlie hellofenlie hello对应的文本路径是：file:/C:/word.txtfenlie hello对应的文件名是：word.txt----------------------------------------------------------当前运行的jobname是：wordcount当前运行的jobId是：job_local492959629_0001运行中读取的配置文件是：Configuration: core-default.xml, core-site.xml, mapred-default.xml, mapred-site.xml, yarn-default.xml, yarn-site.xml, hdfs-default.xml, hdfs-site.xml, file:/tmp/hadoop-Administrator/mapred/local/localRunner/Administrator/job_local492959629_0001/job_local492959629_0001.xml当前操作用户是：Administrator2016-07-10 13:29:58,177 INFO [LocalJobRunner Map Task Executor #0] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 2016-07-10 13:29:58,177 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:flush(1437)) - Starting flush of map output2016-07-10 13:29:58,178 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:flush(1455)) - Spilling map output2016-07-10 13:29:58,178 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:flush(1456)) - bufstart = 0; bufend = 156; bufvoid = 1048576002016-07-10 13:29:58,178 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:flush(1458)) - kvstart = 26214396(104857584); kvend = 26214352(104857408); length = 45/65536002016-07-10 13:29:58,202 INFO [LocalJobRunner Map Task Executor #0] mapred.MapTask (MapTask.java:sortAndSpill(1641)) - Finished spill 02016-07-10 13:29:58,212 INFO [LocalJobRunner Map Task Executor #0] mapred.Task (Task.java:done(995)) - Task:attempt_local492959629_0001_m_000000_0 is done. And is in the process of committing2016-07-10 13:29:58,224 INFO [LocalJobRunner Map Task Executor #0] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - map2016-07-10 13:29:58,224 INFO [LocalJobRunner Map Task Executor #0] mapred.Task (Task.java:sendDone(1115)) - Task 'attempt_local492959629_0001_m_000000_0' done.2016-07-10 13:29:58,224 INFO [LocalJobRunner Map Task Executor #0] mapred.LocalJobRunner (LocalJobRunner.java:run(249)) - Finishing task: attempt_local492959629_0001_m_000000_02016-07-10 13:29:58,225 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:runTasks(456)) - map task executor complete.2016-07-10 13:29:58,229 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:runTasks(448)) - Waiting for reduce tasks2016-07-10 13:29:58,229 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:run(302)) - Starting task: attempt_local492959629_0001_r_000000_02016-07-10 13:29:58,247 INFO [pool-3-thread-1] util.ProcfsBasedProcessTree (ProcfsBasedProcessTree.java:isAvailable(182)) - ProcfsBasedProcessTree currently is supported only on Linux.2016-07-10 13:29:58,334 INFO [pool-3-thread-1] mapred.Task (Task.java:initialize(581)) - Using ResourceCalculatorProcessTree : org.apache.hadoop.yarn.util.WindowsBasedProcessTree@c8a80d82016-07-10 13:29:58,338 INFO [pool-3-thread-1] mapred.ReduceTask (ReduceTask.java:run(362)) - Using ShuffleConsumerPlugin: org.apache.hadoop.mapreduce.task.reduce.Shuffle@50d379e82016-07-10 13:29:58,351 INFO [pool-3-thread-1] reduce.MergeManagerImpl (MergeManagerImpl.java:<init>(193)) - MergerManager: memoryLimit=1331114752, maxSingleShuffleLimit=332778688, mergeThreshold=878535744, ioSortFactor=10, memToMemMergeOutputsThreshold=102016-07-10 13:29:58,354 INFO [EventFetcher for fetching Map Completion Events] reduce.EventFetcher (EventFetcher.java:run(61)) - attempt_local492959629_0001_r_000000_0 Thread started: EventFetcher for fetching Map Completion Events2016-07-10 13:29:58,381 INFO [localfetcher#1] reduce.LocalFetcher (LocalFetcher.java:copyMapOutput(140)) - localfetcher#1 about to shuffle output of map attempt_local492959629_0001_m_000000_0 decomp: 182 len: 186 to MEMORY2016-07-10 13:29:58,390 INFO [localfetcher#1] reduce.InMemoryMapOutput (InMemoryMapOutput.java:shuffle(100)) - Read 182 bytes from map-output for attempt_local492959629_0001_m_000000_02016-07-10 13:29:58,419 INFO [localfetcher#1] reduce.MergeManagerImpl (MergeManagerImpl.java:closeInMemoryFile(307)) - closeInMemoryFile -> map-output of size: 182, inMemoryMapOutputs.size() -> 1, commitMemory -> 0, usedMemory ->1822016-07-10 13:29:58,420 INFO [EventFetcher for fetching Map Completion Events] reduce.EventFetcher (EventFetcher.java:run(76)) - EventFetcher is interrupted.. Returning2016-07-10 13:29:58,421 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.2016-07-10 13:29:58,422 INFO [pool-3-thread-1] reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(667)) - finalMerge called with 1 in-memory map-outputs and 0 on-disk map-outputs2016-07-10 13:29:58,445 INFO [pool-3-thread-1] mapred.Merger (Merger.java:merge(591)) - Merging 1 sorted segments2016-07-10 13:29:58,445 INFO [pool-3-thread-1] mapred.Merger (Merger.java:merge(690)) - Down to the last merge-pass, with 1 segments left of total size: 173 bytes2016-07-10 13:29:58,450 INFO [pool-3-thread-1] reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(742)) - Merged 1 segments, 182 bytes to disk to satisfy reduce memory limit2016-07-10 13:29:58,451 INFO [pool-3-thread-1] reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(772)) - Merging 1 files, 186 bytes from disk2016-07-10 13:29:58,452 INFO [pool-3-thread-1] reduce.MergeManagerImpl (MergeManagerImpl.java:finalMerge(787)) - Merging 0 segments, 0 bytes from memory into reduce2016-07-10 13:29:58,452 INFO [pool-3-thread-1] mapred.Merger (Merger.java:merge(591)) - Merging 1 sorted segments2016-07-10 13:29:58,453 INFO [pool-3-thread-1] mapred.Merger (Merger.java:merge(690)) - Down to the last merge-pass, with 1 segments left of total size: 173 bytes2016-07-10 13:29:58,453 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.2016-07-10 13:29:58,467 INFO [pool-3-thread-1] Configuration.deprecation (Configuration.java:warnOnceIfDeprecated(1009)) - mapred.skip.on is deprecated. Instead, use mapreduce.job.skiprecords2016-07-10 13:29:58,474 INFO [pool-3-thread-1] mapred.Task (Task.java:done(995)) - Task:attempt_local492959629_0001_r_000000_0 is done. And is in the process of committing2016-07-10 13:29:58,476 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - 1 / 1 copied.2016-07-10 13:29:58,476 INFO [pool-3-thread-1] mapred.Task (Task.java:commit(1156)) - Task attempt_local492959629_0001_r_000000_0 is allowed to commit now2016-07-10 13:29:58,483 INFO [pool-3-thread-1] output.FileOutputCommitter (FileOutputCommitter.java:commitTask(439)) - Saved output of task 'attempt_local492959629_0001_r_000000_0' to file:/C:/dirout/_temporary/0/task_local492959629_0001_r_0000002016-07-10 13:29:58,484 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:statusUpdate(591)) - reduce > reduce2016-07-10 13:29:58,484 INFO [pool-3-thread-1] mapred.Task (Task.java:sendDone(1115)) - Task 'attempt_local492959629_0001_r_000000_0' done.2016-07-10 13:29:58,484 INFO [pool-3-thread-1] mapred.LocalJobRunner (LocalJobRunner.java:run(325)) - Finishing task: attempt_local492959629_0001_r_000000_02016-07-10 13:29:58,484 INFO [Thread-3] mapred.LocalJobRunner (LocalJobRunner.java:runTasks(456)) - reduce task executor complete.2016-07-10 13:29:58,666 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1355)) - Job job_local492959629_0001 running in uber mode : false2016-07-10 13:29:58,667 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1362)) - map 100% reduce 100%2016-07-10 13:29:58,668 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1373)) - Job job_local492959629_0001 completed successfully2016-07-10 13:29:58,679 INFO [main] mapreduce.Job (Job.java:monitorAndPrintJob(1380)) - Counters: 34 File System Counters FILE: Number of bytes read=804 FILE: Number of bytes written=462717 FILE: Number of read operations=0 FILE: Number of large read operations=0 FILE: Number of write operations=0 Map-Reduce Framework Map input records=6 Map output records=12 Map output bytes=156 Map output materialized bytes=186 Input split bytes=82 Combine input records=0 Combine output records=0 Reduce input groups=6 Reduce shuffle bytes=186 Reduce input records=12 Reduce output records=6 Spilled Records=24 Shuffled Maps =1 Failed Shuffles=0 Merged Map outputs=1 GC time elapsed (ms)=7 CPU time spent (ms)=0 Physical memory (bytes) snapshot=0 Virtual memory (bytes) snapshot=0 Total committed heap usage (bytes)=467664896 Sensitive Word sensitiveword=1 Shuffle Errors BAD_ID=0 CONNECTION=0 IO_ERROR=0 WRONG_LENGTH=0 WRONG_MAP=0 WRONG_REDUCE=0 File Input Format Counters Bytes Read=64 File Output Format Counters Bytes Written=51fenlie 1he 2hello 6me 1she 1you 11、计数器counter是全局的。 换言之，MapReduce框架将跨所有map和reduce聚集这些计数器，并在作业结束 时产生一个最终结果。
2、Configuration: core-site.xml, mapred-site.xml, yarn-site.xml, hdfs-site.xml这四个配置文件读取的方式分为3种：
第一：用Hadoop的集群模式运行程序，将会读取hadoop中这几个配置文件的内容。
第二：将这个xxx-site.xml加载到eclipse的工程src中
第三：在代码中用 conf.set(name, value)的方式进行指定
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