= Hello Hadoop V2 = * hellohadoop v2 main {{{ #!java import java.io.IOException; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; 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.output.FileOutputFormat; // HelloHadoopV2 // 說明: // 此程式碼比HelloHadoop 增加 // * 檢查輸出資料夾是否存在並刪除 // * input 資料夾內的資料若大於兩個,則資料不會被覆蓋 // * map 與 reduce 拆開以利程式再利用 // // 測試方法: // 將此程式運作在hadoop 0.20 平台上,執行: // --------------------------- // hadoop jar HelloHadoopV2.jar // --------------------------- // // 注意: // 1. 在hdfs 上來源檔案的路徑為 "/user/$YOUR_NAME/input" // 請注意必須先放資料到此hdfs上的資料夾內,且此資料夾內只能放檔案,不可再放資料夾 // 2. 運算完後,程式將執行結果放在hdfs 的輸出路徑為 "/user/$YOUR_NAME/output-hh2" // public class HelloHadoopV2 { public static void main(String[] args) throws IOException, InterruptedException, ClassNotFoundException { Configuration conf = new Configuration(); Job job = new Job(conf, "Hadoop Hello World 2"); job.setJarByClass(HelloHadoopV2.class); // 設定 map and reduce 以及 Combiner class job.setMapperClass(HelloMapperV2.class); job.setCombinerClass(HelloReducerV2.class); job.setReducerClass(HelloReducerV2.class); // 設定map的輸出型態 job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(Text.class); // 設定reduce的輸出型態 job.setOutputKeyClass(Text.class); job.setOutputValueClass(Text.class); FileInputFormat.addInputPath(job, new Path("input")); FileOutputFormat.setOutputPath(job, new Path("output-hh2")); // 呼叫checkAndDelete函式,檢查是否存在該資料夾,若有則刪除之 CheckAndDelete.checkAndDelete("output-hh2", conf); boolean status = job.waitForCompletion(true); if (status) { System.err.println("Integrate Alert Job Finished !"); } else { System.err.println("Integrate Alert Job Failed !"); System.exit(1); } } } }}} * mapper {{{ #!java import java.io.IOException; import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; public class HelloMapperV2 extends Mapper { public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { context.write(new Text(key.toString()), value); } } }}} * reducer {{{ #!java import java.io.IOException; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; public class HelloReducerV2 extends Reducer { public void reduce(Text key, Iterable values, Context context) throws IOException, InterruptedException { String str = new String(""); Text final_key = new Text(); Text final_value = new Text(); // 將key值相同的values,透過 && 符號分隔之 for (Text tmp : values) { str += tmp.toString() + " &&"; } final_key.set(key); final_value.set(str); context.write(final_key, final_value); } } }}}