我正在努力学习hadoop。
我从免费的大型数据集网站下载了以下文件。我做了样本测试的简称。这是一个小文件。
"CAMIS","DBA","BORO","BUILDING","STREET","ZIPCODE","PHONE","CUISINECODE","INSPDATE","ACTION","VIOLCODE","SCORE","CURRENTGRADE","GRADEDATE","RECORDDATE"
"40280083","INTERCONTINENTAL THE BARCLAY","1","111 ","EAST 48 STREET ","10017","2129063134","03","2014-02-07 00:00:00","D","10F","4","A","2014-02-07 00:00:00","2014-04-24 06:01:04.920000000"
"40356649","REGINA CATERERS","3","6409","11 AVENUE","11219","7182560829","03","2013-07-30 00:00:00","D","08A","12","A","2013-07-30 00:00:00","2014-04-24 06:01:04.920000000"
"40356649","REGINA CATERERS","3","6409","11 AVENUE","11219","7182560829","03","2013-07-30 00:00:00","D","08B","12","A","2013-07-30 00:00:00","2014-04-24 06:01:04.920000000"
"40356731","TASTE THE TROPICS ICE CREAM","3","1839 ","NOSTRAND AVENUE ","11226","7188560821","43","2013-07-10 00:00:00","D","06C","8","A","2013-07-10 00:00:00","2014-04-24 06:01:04.920000000"
"40356731","TASTE THE TROPICS ICE CREAM","3","1839 ","NOSTRAND AVENUE ","11226","7188560821","43","2013-07-10 00:00:00","D","10B","8","A","2013-07-10 00:00:00","2014-04-24 06:01:04.920000000"
"40357217","WILD ASIA","2","2300","SOUTHERN BOULEVARD","10460","7182207846","03","2013-06-19 00:00:00","D","10B","4","A","2013-06-19 00:00:00","2014-04-24 06:01:04.920000000"
"40360045","SEUDA FOODS","3","705 ","KINGS HIGHWAY ","11223","7183751500","50","2013-10-10 00:00:00","D","08C","13","A","2013-10-10 00:00:00","2014-04-24 06:01:04.920000000"
"40361521","GLORIOUS FOOD","1","522","EAST 74 STREET","10021","2127372140","03","2013-12-19 00:00:00","U","08A","16","B","2013-12-19 00:00:00","2014-04-24 06:01:04.920000000"
"40362098","HARRIET'S KITCHEN","1","502","AMSTERDAM AVENUE","10024","2127210045","18","2014-03-04 00:00:00","U","10F","13","A","2014-03-04 00:00:00","2014-04-24 06:01:04.920000000"
"40361322","CARVEL ICE CREAM","4","265-15 ","HILLSIDE AVENUE ","11004","7183430392","43","2013-09-18 00:00:00","D","08A","10","A","2013-09-18 00:00:00","2014-04-24 06:01:04.920000000"
"40361708","BULLY'S DELI","1","759 ","BROADWAY ","10003","2122549755","27","2014-01-21 00:00:00","D","10F","12","A","2014-01-21 00:00:00","2014-04-24 06:01:04.920000000"
"40362098","HARRIET'S KITCHEN","1","502","AMSTERDAM AVENUE","10024","2127210045","18","2014-03-04 00:00:00","U","04N","13","A","2014-03-04 00:00:00","2014-04-24 06:01:04.920000000"
"40362274","ANGELIKA FILM CENTER","1","18","WEST HOUSTON STREET","10012","2129952570","03","2014-04-03 00:00:00","D","06D","9","A","2014-04-03 00:00:00","2014-04-24 06:01:04.920000000"
"40362715","THE COUNTRY CAFE","1","60","WALL STREET","10005","3474279132","83","2013-09-18 00:00:00","D","10B","13","A","2013-09-18 00:00:00","2014-04-24 06:01:04.920000000"
"40362869","SHASHEMENE INT'L RESTAURA","3","195","EAST 56 STREET","11203","3474300871","17","2013-05-08 00:00:00","D","10B","7","A","2013-05-08 00:00:00","2014-04-24 06:01:04.920000000"
"40363021","DOWNTOWN DELI","1","107","CHURCH STREET","10007","2122332911","03","2014-02-26 00:00:00","D","10B","9","A","2014-02-26 00:00:00","2014-04-24 06:01:04.920000000"
"40362432","HO MEI RESTAURANT","4","103-05","37 AVENUE","11368","7187796903","20","2014-04-21 00:00:00","D","06C","10","A","2014-04-21 00:00:00","2014-04-24 06:01:04.920000000"
"40362869","SHASHEMENE INT'L RESTAURA","3","195","EAST 56 STREET","11203","3474300871","17","2013-05-08 00:00:00","D","10F","7","A","2013-05-08 00:00:00","2014-04-24 06:01:04.920000000"
"40363117","MEJLANDER & MULGANNON","3","7615","5 AVENUE","11209","7182386666","03","2013-10-24 00:00:00","D","02G","11","A","2013-10-24 00:00:00","2014-04-24 06:01:04.920000000"
"40363289","HAPPY GARDEN","2","1236 ","238 SPOFFORD AVE ","10474","7186171818","20","2013-12-30 00:00:00","D","10F","8","A","2013-12-30 00:00:00","2014-04-24 06:01:04.920000000"
"40363644","DOMINO'S PIZZA","1","464","3 AVENUE","10016","2125450200","62","2014-03-06 00:00:00","D","08A","11","A","2014-03-06 00:00:00","2014-04-24 06:01:04.920000000"
"30191841","DJ REYNOLDS PUB AND RESTAURANT","1","351 ","WEST 57 STREET ","10019","2122452912","03","2013-07-22 00:00:00","D","10B","11","A","2013-07-22 00:00:00","2014-04-24 06:01:04.920000000"
"40280083","INTERCONTINENTAL THE BARCLAY","1","111 ","EAST 48 STREET ","10017","2129063134","03","2014-02-07 00:00:00","D","10B","4","A","2014-02-07 00:00:00","2014-04-24 06:01:04.920000000"
"40356442","KOSHER ISLAND","5","2206","VICTORY BOULEVARD","10314","7186985800","50","2013-04-04 00:00:00","D","10F","12","A","2013-04-04 00:00:00","2014-04-24 06:01:04.920000000"
"40356483","WILKEN'S FINE FOOD","3","7114 ","AVENUE U ","11234","7184443838","27","2014-01-14 00:00:00","D","10B","10","A","2014-01-14 00:00:00","2014-04-24 06:01:04.920000000"
文件是关于餐馆的一些检查。
你可以看到有CUISINECODE。它的值范围从＆＃34; 00＆＃34;某种价值或可以是任何价值。会有很多餐厅都有相同的CUISINECODE。
我只想显示每个cusinecode中的餐馆数量。
这是我的MapReducer计划
import java.io.IOException;
import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reducer;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.TextOutputFormat;
public class RestaurantInspection {
public static class Map extends MapReduceBase implements
Mapper<LongWritable, Text, Text, IntWritable> {
@Override
public void map(LongWritable key, Text value, OutputCollector<Text, IntWritable> output, Reporter reporter)
throws IOException {
String line = value.toString();
if (line.startsWith("\"CAMIS\",")) {
// Line is the header, ignore it
return;
}
List<String> columns = new ArrayList<String>();
String[] tokens = line.split(",(?=([^\"]*\"[^\"]*\")*[^\"]*$)");
if (tokens.length != 15) {
// Line isn't the correct number of columns or formatted properly
return;
}
for(String t : tokens) {
columns.add(t.replaceAll("\"", ""));
}
int cusineCode = Integer.parseInt(columns.get(7));
String violations = columns.get(9) + " --- " + columns.get(10);
value.set(violations);
output.collect(value, new IntWritable(cusineCode));
}
}
public static class Reduce extends MapReduceBase implements
Reducer<Text, IntWritable, Text, IntWritable> {
@Override
public void reduce(Text key, Iterator<IntWritable> values,
OutputCollector<Text, IntWritable> output, Reporter reporter)
throws IOException {
int sum = 0;
while (values.hasNext()) {
sum += values.next().get();
}
output.collect(key, new IntWritable(sum));
}
}
public static void main(String[] args) throws Exception {
JobConf conf = new JobConf(RestaurantInspection.class);
conf.setJobName("Restaurent Inspection");
conf.setOutputKeyClass(Text.class);
conf.setOutputValueClass(IntWritable.class);
conf.setMapperClass(Map.class);
conf.setReducerClass(Reduce.class);
conf.setInputFormat(TextInputFormat.class);
conf.setOutputFormat(TextOutputFormat.class);
FileInputFormat.setInputPaths(conf, new Path(args[0]));
FileOutputFormat.setOutputPath(conf, new Path(args[1]));
JobClient.runJob(conf);
}
}
我正在使用 hadoop 1.2.1 。我从WordCount示例复制了上面的代码，只更改了几行。
当我在hadoop中运行上面的代码时，我得到了上面给出的相同文件的以下行
D --- 02G 3
D --- 06C 63
D --- 06D 3
D --- 08A 108
D --- 08B 3
D --- 08C 50
D --- 10B 182
D --- 10F 117
U --- 04N 18
U --- 08A 3
U --- 10F 18
那只是一个考验。我没有得到任何编写代码以获得所需输出的逻辑。我期待以上文件的以下输出。
01 -- 1
03 -- 9
43 -- 3
50 -- 2
18 -- 2
27 -- 2
83 -- 1
17 -- 2
20 -- 2
62 -- 1
通过这个，我想我可以学习hadoop和map reduce。
那么如何编写代码呢？感谢。
答案 0 :(得分：1)
您需要密钥才能成为CUISINECODE。
String cusineCode = columns.get(7);
output.collect(new Text(cusineCode), new IntWritable(1));
这将为你完成这项工作。