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DBILITY
M/R 미국 상업 항공편 지연 출발 통계 그래프 작성하기 본문
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- 맵리듀스로 분석할 사항은
2008년도 월별 지연 출발 통계로 ASA Data expo에서 2008년 데이터를 다운로드한다. - 대상 데이터 구조를 분석하기 위해 ASA Data expo '09의 Variable Descriptions확인 결과
CSV 파일의 1번 Year, 2번 Month, 16번 departure delay, in minutes임을 확인.
Mapper구현 시 input value에 대해 split후 결과 배열의 1,15번 index를 사용하기로 함.
1번의 월 값을 key로 사용하고, 15번 지연시간은 value로 NA 문자열이 포함되어 있으므로,
Interger convert 오류가 발생할 수 있으며, 음수가 존재함, 양수만 카운트하도록 조건 추가.
파일 사이즈 약 657M. - 프로젝트 생성 및 Mapper, Reducer, Driver(Client) Class를 구현한다.
윈도 우상 eclipse에서 실행 후 결과만 얻을 것이므로 build관련 설정은 제외함
pom.xml
logback.xml<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd"> <modelVersion>4.0.0</modelVersion> <groupId>com.dbility.hadoop.apps</groupId> <artifactId>departure_delay_2008</artifactId> <version>0.0.1-SNAPSHOT</version> <properties> <java.version>1.7</java.version> <hadoop.version>1.2.1</hadoop.version> <slf4j.version>1.7.20</slf4j.version> <logback.version>1.1.7</logback.version> </properties> <dependencies> <dependency> <groupId>org.apache.hadoop</groupId> <artifactId>hadoop-core</artifactId> <version>${hadoop.version}</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>slf4j-api</artifactId> <version>${slf4j.version}</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>jcl-over-slf4j</artifactId> <version>${slf4j.version}</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>log4j-over-slf4j</artifactId> <version>${slf4j.version}</version> </dependency> <dependency> <groupId>org.slf4j</groupId> <artifactId>jul-to-slf4j</artifactId> <version>${slf4j.version}</version> </dependency> <dependency> <groupId>ch.qos.logback</groupId> <artifactId>logback-classic</artifactId> <version>${logback.version}</version> </dependency> <dependency> <groupId>ch.qos.logback</groupId> <artifactId>logback-core</artifactId> <version>${logback.version}</version> </dependency> </dependencies> </project>
DepartureDelayMapper2008.java<!--?xml version="1.0" encoding="UTF-8"?--> <configuration> <appender name="console" class="ch.qos.logback.core.ConsoleAppender"> <!-- encoders are assigned the type ch.qos.logback.classic.encoder.PatternLayoutEncoder by default --> <encoder> <pattern>%d{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n</pattern> </encoder> </appender> <logger name="org.apache.hadoop.mapred.JobClient" additivity="false"> <level value="info" /> <appender-ref ref="console" /> </logger> <root level="warn"> <appender-ref ref="console" /> </root> </configuration>
package com.dbility.hadoop.apps; import java.io.IOException; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; public class DepartureDelay2008Mapper extends Mapper<longwritable, text, intwritable> { private Text outputKey = new Text(); private static final IntWritable one = new IntWritable(1); @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String[] columns = value.toString().split(","); if ( !columns[15].equals("NA") && Integer.parseInt(columns[15]) > 0 ){ outputKey.set(columns[1]); context.write(outputKey, one); } } }
DepartureDelayReducer2008.java
package com.dbility.hadoop.apps; import java.io.IOException; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; public class DepartureDelay2008Reducer extends Reducer<Text, IntWritable, Text, IntWritable> { IntWritable count = new IntWritable(); @Override protected void reduce(Text key, Iterable<IntWritable> values, Context context) throws IOException, InterruptedException { int sum = 0; for (IntWritable value : values) { sum+=value.get(); } count.set(sum); context.write(key, count); } }
WindowsLocalFileSystem.java
DepartureDelay2008Client.javapackage com.dbility.hadoop.apps; import java.io.IOException; import org.apache.hadoop.fs.LocalFileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.fs.permission.FsPermission; public class WindowsLocalFileSystem extends LocalFileSystem { public WindowsLocalFileSystem() { super(); } //@Override public boolean mkdirs(final Path f, final FsPermission permission) throws IOException { final boolean result = super.mkdirs(f); this.setPermission(f, permission); return result; } public void setPermission(final Path f, final FsPermission permission ) { try { super.setPermission(f, permission); } catch (final IOException e) { System.err.println(e.getMessage()); } } }
실행 로그package com.dbility.hadoop.apps; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.IntWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Job; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; 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.slf4j.Logger; import org.slf4j.LoggerFactory; public class DepartureDelay2008Client { private static final Logger log = LoggerFactory.getLogger(DepartureDelay2008Client.class); public static void main(String[] args) throws Exception { if ( args.length != 2 ){ log.info("Usage : <input> <output>"); Runtime.getRuntime().exit(1); } Configuration conf = new Configuration(); conf.set("fs.default.name", "file:///"); conf.set("mapred.job.tracker", "local"); conf.set("fs.file.impl", "com.dbility.hadoop.apps.WindowsLocalFileSystem"); conf.set("io.serializations", "org.apache.hadoop.io.serializer.JavaSerialization,org.apache.hadoop.io.serializer.WritableSerialization"); conf.set("io.sort.mb","512"); conf.set("mapred.used.genericoptionsparser", "true"); Job job = new Job(conf,"DepartureDelay2008MapReduce"); job.setJarByClass(DepartureDelay2008Client.class); job.setMapperClass(DepartureDelay2008Mapper.class); job.setReducerClass(DepartureDelay2008Reducer.class); job.setInputFormatClass(TextInputFormat.class); job.setOutputFormatClass(TextOutputFormat.class); job.setOutputKeyClass(Text.class); job.setOutputValueClass(IntWritable.class); FileInputFormat.addInputPath(job, new Path(args[0])); FileOutputFormat.setOutputPath(job, new Path(args[1])); FileSystem hdfs = FileSystem.get(conf); Path path = new Path(args[1]); if ( hdfs.exists(path) ) hdfs.delete(path, true); Runtime.getRuntime().exit(job.waitForCompletion(true) ? 0 : 1); } }
실행결과 part-r-0000023:58:25.283 [main] WARN o.a.hadoop.util.NativeCodeLoader - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable Failed to set permissions of path: \tmp\hadoop-ROOKIE\mapred\staging\ROOKIE1086790840\.staging to 0700 Failed to set permissions of path: \tmp\hadoop-ROOKIE\mapred\staging\ROOKIE1086790840\.staging\job_local1086790840_0001 to 0700 23:58:25.298 [main] WARN org.apache.hadoop.mapred.JobClient - No job jar file set. User classes may not be found. See JobConf(Class) or JobConf#setJar(String). 23:58:25.314 [main] WARN o.a.h.io.compress.snappy.LoadSnappy - Snappy native library not loaded Failed to set permissions of path: \tmp\hadoop-ROOKIE\mapred\staging\ROOKIE1086790840\.staging\job_local1086790840_0001\job.split to 0644 Failed to set permissions of path: \tmp\hadoop-ROOKIE\mapred\staging\ROOKIE1086790840\.staging\job_local1086790840_0001\job.splitmetainfo to 0644 Failed to set permissions of path: \tmp\hadoop-ROOKIE\mapred\staging\ROOKIE1086790840\.staging\job_local1086790840_0001\job.xml to 0644 23:58:25.486 [main] INFO org.apache.hadoop.mapred.JobClient - Running job: job_local1086790840_0001 23:58:26.487 [main] INFO org.apache.hadoop.mapred.JobClient - map 0% reduce 0% 23:58:27.489 [main] INFO org.apache.hadoop.mapred.JobClient - map 4% reduce 0% 23:58:28.489 [main] INFO org.apache.hadoop.mapred.JobClient - map 9% reduce 0% 23:58:29.489 [main] INFO org.apache.hadoop.mapred.JobClient - map 19% reduce 0% 23:58:30.497 [main] INFO org.apache.hadoop.mapred.JobClient - map 23% reduce 0% 23:58:31.512 [main] INFO org.apache.hadoop.mapred.JobClient - map 33% reduce 0% 23:58:32.512 [main] INFO org.apache.hadoop.mapred.JobClient - map 38% reduce 0% 23:58:33.513 [main] INFO org.apache.hadoop.mapred.JobClient - map 47% reduce 0% 23:58:34.513 [main] INFO org.apache.hadoop.mapred.JobClient - map 52% reduce 0% 23:58:35.520 [main] INFO org.apache.hadoop.mapred.JobClient - map 61% reduce 0% 23:58:36.521 [main] INFO org.apache.hadoop.mapred.JobClient - map 66% reduce 0% 23:58:37.525 [main] INFO org.apache.hadoop.mapred.JobClient - map 76% reduce 0% 23:58:38.553 [main] INFO org.apache.hadoop.mapred.JobClient - map 85% reduce 0% 23:58:39.556 [main] INFO org.apache.hadoop.mapred.JobClient - map 90% reduce 0% 23:58:40.559 [main] INFO org.apache.hadoop.mapred.JobClient - map 100% reduce 0% 23:58:41.561 [main] INFO org.apache.hadoop.mapred.JobClient - map 100% reduce 100% 23:58:41.562 [main] INFO org.apache.hadoop.mapred.JobClient - Job complete: job_local1086790840_0001 23:58:41.583 [main] INFO org.apache.hadoop.mapred.JobClient - Counters: 17 23:58:41.583 [main] INFO org.apache.hadoop.mapred.JobClient - File Output Format Counters 23:58:41.583 [main] INFO org.apache.hadoop.mapred.JobClient - Bytes Written=123 23:58:41.583 [main] INFO org.apache.hadoop.mapred.JobClient - File Input Format Counters 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Bytes Read=689494964 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - FileSystemCounters 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - FILE_BYTES_READ=8461331084 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - FILE_BYTES_WRITTEN=289237537 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Map-Reduce Framework 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Reduce input groups=12 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Map output materialized bytes=22191676 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Combine output records=0 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Map input records=7009728 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Reduce shuffle bytes=0 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Reduce output records=12 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Spilled Records=6906730 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Map output bytes=16789602 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Total committed heap usage (bytes)=23908057088 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - SPLIT_RAW_BYTES=1974 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Map output records=2700974 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Combine input records=0 23:58:41.584 [main] INFO org.apache.hadoop.mapred.JobClient - Reduce input records=2700974
1 247948 10 162531 11 157278 12 263949 2 252765 3 271969 4 220864 5 220614 6 271014 7 253632 8 231349 9 147061
- 실행 후 결과를 토대로 보고서에 삽입할 엑셀 피벗 차트를 작성한다.
뭔가 이상한데, 천조국이라 그런가?! 숫자가 너무 큼. 정확한 결과인지는 CSV데이터를 RDBMS에 IMPORT 후 확인해야 하겠다!
다음은 지연 출발 사유별로 필드가 있길래 조건을 수정해가며 분석해 보았습니다만, 이게 정상인지 확신할 수 없으며,
Quartz JobChain이나 SpringBatch jobstep 같은 개념이 당연히 있을 텐데, 아직 공부를 못해서 단순하게 수정해가며 작성되었다.
(나중에 확인한 결과 ChainMapper, ChainReducer, MultipleOutputs가 있다. 역시 무식하면 죄를 짓는다)
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