[TOC] # 需求 过滤输入的log日志中是否包含java 1. 包含java的网站输出到`e:/java.log`中 2. 不包含java的网站输出到`e:/other.log`中 输入数据 : log.txt ~~~ java.org jdxia java.com x.com java ~~~ 输出预期: `java.log` `other.log` # OutputFormat接口实现类 OutputFormat是MapReduce输出的基类,所有实现MapReduce输出都实现了OutputFormat接口. 常见是OutputFormat实现类 1. 文本输出TextOutputFormat 默认的输出格式是TextOutputFormat,它把每条记录写为文本行.他的键和值可以是任意类型,因为TextOutputFormat调用toString()方法把他们转换为字符串 2. SequenceFileOutputFormat SequenceFileOutputFormat将它的输出写为一个顺序文件.如果输出需要作为后续MapReduce任务的输入,这便是一种很好的输出格式,因为他的格式紧凑,很容易被压缩 3. 自定义OutputFormat 根据用户需求,自定义实现输出 # 代码 自定义OutputFormat步骤 1. 自定义一个类继承FileOutputFormat 2. 改写recordwrite,具体改写输出数据的方法write() **自定义一个OutputFormat** ~~~ import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.RecordWriter; import org.apache.hadoop.mapreduce.TaskAttemptContext; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import java.io.IOException; public class FilterOutputFormat extends FileOutputFormat<Text, NullWritable> { @Override public RecordWriter<Text, NullWritable> getRecordWriter(TaskAttemptContext job) throws IOException, InterruptedException { //创建一个RecordWriter return new FilterRecordWriter(job); } } ~~~ ~~~ import org.apache.hadoop.fs.FSDataOutputStream; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.RecordWriter; import org.apache.hadoop.mapreduce.TaskAttemptContext; import java.io.IOException; public class FilterRecordWriter extends RecordWriter<Text, NullWritable> { FSDataOutputStream javaOut = null; FSDataOutputStream otherOut = null; public FilterRecordWriter(TaskAttemptContext job) { //1. 获取文件系统 FileSystem fs; try { fs = FileSystem.get(job.getConfiguration()); //2. 创建输出文件路径 Path javaPath = new Path("/Users/jdxia/Desktop/website/data/java.log"); Path otherPath = new Path("/Users/jdxia/Desktop/website/data/other.log"); //3. 创建输出流 javaOut = fs.create(javaPath); otherOut = fs.create(otherPath); } catch (IOException e) { e.printStackTrace(); } } @Override public void write(Text key, NullWritable value) throws IOException, InterruptedException { //判断是否包含"java"输出到不同文件 if (key.toString().contains("java")) { javaOut.write(key.toString().getBytes()); } else { otherOut.write(key.toString().getBytes()); } } @Override public void close(TaskAttemptContext context) throws IOException, InterruptedException { //关闭资源,流不关文件是空的 if (javaOut != null) { javaOut.close(); } if (otherOut != null) { otherOut.close(); } } } ~~~ **Mapper类** ~~~ import org.apache.hadoop.io.LongWritable; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Mapper; import java.io.IOException; public class FilterMapper extends Mapper<LongWritable, Text, Text, NullWritable> { Text k = new Text(); @Override protected void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { //获取一行 String line = value.toString(); k.set(line); //写出 context.write(k, NullWritable.get()); } } ~~~ **Reducer类** ~~~ import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.Reducer; import java.io.IOException; public class FilterReducer extends Reducer<Text, NullWritable, Text, NullWritable> { @Override protected void reduce(Text key, Iterable<NullWritable> values, Context context) throws IOException, InterruptedException { String k = key.toString(); k += "\r\n"; context.write(new Text(k), NullWritable.get()); } } ~~~ **驱动类** ~~~ import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.FileSystem; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.NullWritable; 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 java.io.IOException; public class FilterDriver { public static void main(String[] args) throws IOException, ClassNotFoundException, InterruptedException { Configuration conf = new Configuration(); Job job = Job.getInstance(conf); job.setJarByClass(FilterDriver.class); job.setMapperClass(FilterMapper.class); job.setReducerClass(FilterReducer.class); //输入输出组件 job.setInputFormatClass(TextInputFormat.class); job.setOutputFormatClass(FilterOutputFormat.class); //Map的输出 job.setMapOutputKeyClass(Text.class); job.setMapOutputValueClass(NullWritable.class); //reduce的输出 job.setOutputKeyClass(Text.class); job.setOutputValueClass(NullWritable.class); //告诉框架，我们要处理的数据文件在那个路径下 FileInputFormat.setInputPaths(job, new Path("/Users/jdxia/Desktop/website/data/input/")); //如果有这个文件夹就删除 Path out = new Path("/Users/jdxia/Desktop/website/data/output/"); FileSystem fileSystem = FileSystem.get(conf); if (fileSystem.exists(out)) { fileSystem.delete(out, true); } //告诉框架，我们的处理结果要输出到什么地方 FileOutputFormat.setOutputPath(job, out); //虽然自定义OutputFormat,但是因为我们的OutputFormat继承自FileOutputFormat //而FileOutputFormat要输出一个_SUCCESS文件,所以这里还需要指定一个输出目录 FileOutputFormat.setOutputPath(job, new Path("/Users/jdxia/Desktop/website/data/output/ ")); boolean res = job.waitForCompletion(true); System.exit(res ? 0 : 1); } } ~~~ # 注意 自定义OutputFormat时,注意recordWriter中的close方法必须关闭流资源.否则输出的文件内容中数据为空