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我正在運行Apache的Hadoop,並使用該安裝提供的grep示例。 我想知道爲什麼地圖減少百分比顯示運行兩次?我以爲他們只需要運行一次;這讓我懷疑我對地圖縮小的理解。我查了一下(http://grokbase.com/t/gg/mongodb-user/125ay1eazq/map-reduce-percentage-seems-running-twice),但確實沒有解釋,這個鏈接是針對MongoDB的。hadoop顯示地圖減少百分比運行兩次
[email protected]:/usr/local/hadoop$ bin/hadoop jar hadoop*examples*.jar grep /user/hduser/grep /user/hduser/grep-output4 ".*woe is me.*"
我在一個項目gutenberg .txt文件上運行這個。輸出文件是正確的。
這裏是如果需要運行該命令的輸出:
12/08/06 06:56:57 INFO util.NativeCodeLoader: Loaded the native-hadoop library
12/08/06 06:56:57 WARN snappy.LoadSnappy: Snappy native library not loaded
12/08/06 06:56:57 INFO mapred.FileInputFormat: Total input paths to process : 1
12/08/06 06:56:58 INFO mapred.JobClient: Running job: job_201208030925_0011
12/08/06 06:56:59 INFO mapred.JobClient: map 0% reduce 0%
12/08/06 06:57:18 INFO mapred.JobClient: map 100% reduce 0%
12/08/06 06:57:30 INFO mapred.JobClient: map 100% reduce 100%
12/08/06 06:57:35 INFO mapred.JobClient: Job complete: job_201208030925_0011
12/08/06 06:57:35 INFO mapred.JobClient: Counters: 30
12/08/06 06:57:35 INFO mapred.JobClient: Job Counters
12/08/06 06:57:35 INFO mapred.JobClient: Launched reduce tasks=1
12/08/06 06:57:35 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=31034
12/08/06 06:57:35 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0
12/08/06 06:57:35 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0
12/08/06 06:57:35 INFO mapred.JobClient: Rack-local map tasks=2
12/08/06 06:57:35 INFO mapred.JobClient: Launched map tasks=2
12/08/06 06:57:35 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=11233
12/08/06 06:57:35 INFO mapred.JobClient: File Input Format Counters
12/08/06 06:57:35 INFO mapred.JobClient: Bytes Read=5592666
12/08/06 06:57:35 INFO mapred.JobClient: File Output Format Counters
12/08/06 06:57:35 INFO mapred.JobClient: Bytes Written=391
12/08/06 06:57:35 INFO mapred.JobClient: FileSystemCounters
12/08/06 06:57:35 INFO mapred.JobClient: FILE_BYTES_READ=281
12/08/06 06:57:35 INFO mapred.JobClient: HDFS_BYTES_READ=5592862
12/08/06 06:57:35 INFO mapred.JobClient: FILE_BYTES_WRITTEN=65331
12/08/06 06:57:35 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=391
12/08/06 06:57:35 INFO mapred.JobClient: Map-Reduce Framework
12/08/06 06:57:35 INFO mapred.JobClient: Map output materialized bytes=287
12/08/06 06:57:35 INFO mapred.JobClient: Map input records=124796
12/08/06 06:57:35 INFO mapred.JobClient: Reduce shuffle bytes=287
12/08/06 06:57:35 INFO mapred.JobClient: Spilled Records=10
12/08/06 06:57:35 INFO mapred.JobClient: Map output bytes=265
12/08/06 06:57:35 INFO mapred.JobClient: Total committed heap usage (bytes)=336404480
12/08/06 06:57:35 INFO mapred.JobClient: CPU time spent (ms)=7040
12/08/06 06:57:35 INFO mapred.JobClient: Map input bytes=5590193
12/08/06 06:57:35 INFO mapred.JobClient: SPLIT_RAW_BYTES=196
12/08/06 06:57:35 INFO mapred.JobClient: Combine input records=5
12/08/06 06:57:35 INFO mapred.JobClient: Reduce input records=5
12/08/06 06:57:35 INFO mapred.JobClient: Reduce input groups=5
12/08/06 06:57:35 INFO mapred.JobClient: Combine output records=5
12/08/06 06:57:35 INFO mapred.JobClient: Physical memory (bytes) snapshot=464568320
12/08/06 06:57:35 INFO mapred.JobClient: Reduce output records=5
12/08/06 06:57:35 INFO mapred.JobClient: Virtual memory (bytes) snapshot=1539559424
12/08/06 06:57:35 INFO mapred.JobClient: Map output records=5
12/08/06 06:57:35 INFO mapred.FileInputFormat: Total input paths to process : 1
12/08/06 06:57:35 INFO mapred.JobClient: Running job: job_201208030925_0012
12/08/06 06:57:36 INFO mapred.JobClient: map 0% reduce 0%
12/08/06 06:57:50 INFO mapred.JobClient: map 100% reduce 0%
12/08/06 06:58:05 INFO mapred.JobClient: map 100% reduce 100%
12/08/06 06:58:10 INFO mapred.JobClient: Job complete: job_201208030925_0012
12/08/06 06:58:10 INFO mapred.JobClient: Counters: 30
12/08/06 06:58:10 INFO mapred.JobClient: Job Counters
12/08/06 06:58:10 INFO mapred.JobClient: Launched reduce tasks=1
12/08/06 06:58:10 INFO mapred.JobClient: SLOTS_MILLIS_MAPS=15432
12/08/06 06:58:10 INFO mapred.JobClient: Total time spent by all reduces waiting after reserving slots (ms)=0
12/08/06 06:58:10 INFO mapred.JobClient: Total time spent by all maps waiting after reserving slots (ms)=0
12/08/06 06:58:10 INFO mapred.JobClient: Rack-local map tasks=1
12/08/06 06:58:10 INFO mapred.JobClient: Launched map tasks=1
12/08/06 06:58:10 INFO mapred.JobClient: SLOTS_MILLIS_REDUCES=14264
12/08/06 06:58:10 INFO mapred.JobClient: File Input Format Counters
12/08/06 06:58:10 INFO mapred.JobClient: Bytes Read=391
12/08/06 06:58:10 INFO mapred.JobClient: File Output Format Counters
12/08/06 06:58:10 INFO mapred.JobClient: Bytes Written=235
12/08/06 06:58:10 INFO mapred.JobClient: FileSystemCounters
12/08/06 06:58:10 INFO mapred.JobClient: FILE_BYTES_READ=281
12/08/06 06:58:10 INFO mapred.JobClient: HDFS_BYTES_READ=505
12/08/06 06:58:10 INFO mapred.JobClient: FILE_BYTES_WRITTEN=42985
12/08/06 06:58:10 INFO mapred.JobClient: HDFS_BYTES_WRITTEN=235
12/08/06 06:58:10 INFO mapred.JobClient: Map-Reduce Framework
12/08/06 06:58:10 INFO mapred.JobClient: Map output materialized bytes=281
12/08/06 06:58:10 INFO mapred.JobClient: Map input records=5
12/08/06 06:58:10 INFO mapred.JobClient: Reduce shuffle bytes=0
12/08/06 06:58:10 INFO mapred.JobClient: Spilled Records=10
EDIT驅動程序類爲grep的: Grep.java
/**
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.examples;
import java.util.Random;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
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.mapred.*;
import org.apache.hadoop.mapred.lib.*;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;
/* Extracts matching regexs from input files and counts them. */
public class Grep extends Configured implements Tool {
private Grep() {} // singleton
public int run(String[] args) throws Exception {
if (args.length < 3) {
System.out.println("Grep <inDir> <outDir> <regex> [<group>]");
ToolRunner.printGenericCommandUsage(System.out);
return -1;
}
Path tempDir =
new Path("grep-temp-"+
Integer.toString(new Random().nextInt(Integer.MAX_VALUE)));
JobConf grepJob = new JobConf(getConf(), Grep.class);
try {
grepJob.setJobName("grep-search");
FileInputFormat.setInputPaths(grepJob, args[0]);
grepJob.setMapperClass(RegexMapper.class);
grepJob.set("mapred.mapper.regex", args[2]);
if (args.length == 4)
grepJob.set("mapred.mapper.regex.group", args[3]);
grepJob.setCombinerClass(LongSumReducer.class);
grepJob.setReducerClass(LongSumReducer.class);
FileOutputFormat.setOutputPath(grepJob, tempDir);
grepJob.setOutputFormat(SequenceFileOutputFormat.class);
grepJob.setOutputKeyClass(Text.class);
grepJob.setOutputValueClass(LongWritable.class);
JobClient.runJob(grepJob);
JobConf sortJob = new JobConf(getConf(), Grep.class);
sortJob.setJobName("grep-sort");
FileInputFormat.setInputPaths(sortJob, tempDir);
sortJob.setInputFormat(SequenceFileInputFormat.class);
sortJob.setMapperClass(InverseMapper.class);
sortJob.setNumReduceTasks(1); // write a single file
FileOutputFormat.setOutputPath(sortJob, new Path(args[1]));
sortJob.setOutputKeyComparatorClass // sort by decreasing freq
(LongWritable.DecreasingComparator.class);
JobClient.runJob(sortJob);
}
finally {
FileSystem.get(grepJob).delete(tempDir, true);
}
return 0;
}
public static void main(String[] args) throws Exception {
int res = ToolRunner.run(new Configuration(), new Grep(), args);
System.exit(res);
}
}
爲什麼有兩個工作呢?哈託普分別在第一和第二職位上做了什麼?它如何分裂工作,爲什麼它將工作分解爲一個簡單的grep文件? – 2012-08-06 22:34:01
添加您的驅動程序類的實現 - 您設置作業並啓動它的類。 – Razvan 2012-08-06 22:37:48
上面的編輯是你駕駛員級別的意思嗎? – 2012-08-06 23:01:40