0x00 文章内容
- Text格式概念
- 编码实现
- 校验结果
- 可能出现的问题解决
Hadoop支持的四种常用的文件格式：Text(csv)、Parquet、Avro以及SequenceFile，非常关键！
0x01 Text格式概念
1. Text是啥
普通的文档格式，txt格式。
0x02 编码实现
1. 写文件完整代码
package com.shaonaiyi.hadoop.filetype.text; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.fs.Path; import org.apache.hadoop.io.NullWritable; import org.apache.hadoop.io.Text; import org.apache.hadoop.mapreduce.*; import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat; import org.apache.hadoop.mapreduce.task.JobContextImpl; import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl; import java.io.IOException; /** * @Author shaonaiyi@163.com * @Date 2019/12/17 11:20 * @Description Hadoop支持的文件格式之写Text */ public class MRTextFileWriter { public static void main(String[] args) throws IOException, IllegalAccessException, InstantiationException, ClassNotFoundException, InterruptedException { //1 构建一个job实例 Configuration hadoopConf = new Configuration(); Job job = Job.getInstance(hadoopConf); //2 设置job的相关属性 job.setOutputKeyClass(NullWritable.class); job.setOutputValueClass(Text.class); job.setOutputFormatClass(TextOutputFormat.class); //3 设置输出路径 FileOutputFormat.setOutputPath(job, new Path("hdfs://master:9999/user/hadoop-sny/mr/filetype/text")); //FileOutputFormat.setCompressOutput(job, true); //FileOutputFormat.setOutputCompressorClass(job, GzipCodec.class); //4 构建JobContext JobID jobID = new JobID("jobId", 123); JobContext jobContext = new JobContextImpl(job.getConfiguration(), jobID); //5 构建taskContext TaskAttemptID attemptId = new TaskAttemptID("jobTrackerId", 123, TaskType.REDUCE, 0, 0); TaskAttemptContext hadoopAttemptContext = new TaskAttemptContextImpl(job.getConfiguration(), attemptId); //6 构建OutputFormat实例 OutputFormat format = job.getOutputFormatClass().newInstance(); //7 设置OutputCommitter OutputCommitter committer = format.getOutputCommitter(hadoopAttemptContext); committer.setupJob(jobContext); committer.setupTask(hadoopAttemptContext); //8 获取writer写数据，写完关闭writer RecordWriter<NullWritable, Text> writer = format.getRecordWriter(hadoopAttemptContext); writer.write(null, new Text("shao")); writer.write(null, new Text("nai")); writer.write(null, new Text("yi")); writer.write(null, new Text("bigdata-man")); writer.close(hadoopAttemptContext); //9 committer提交job和task committer.commitTask(hadoopAttemptContext); committer.commitJob(jobContext); } }
2. 读文件完整代码
package com.shaonaiyi.hadoop.filetype.text; import org.apache.hadoop.conf.Configuration; import org.apache.hadoop.mapreduce.*; import org.apache.hadoop.mapreduce.lib.input.FileInputFormat; import org.apache.hadoop.mapreduce.lib.input.TextInputFormat; import org.apache.hadoop.mapreduce.task.JobContextImpl; import org.apache.hadoop.mapreduce.task.TaskAttemptContextImpl; import java.io.IOException; import java.util.List; import java.util.function.Consumer; /** * @Author shaonaiyi@163.com * @Date 2019/12/17 11:38 * @Description Hadoop支持的文件格式之读Text */ public class MRTextFileReader { public static void main(String[] args) throws IOException, IllegalAccessException, InstantiationException { //1 构建一个job实例 Configuration hadoopConf = new Configuration(); Job job = Job.getInstance(hadoopConf); //2 设置需要读取的文件全路径 FileInputFormat.setInputPaths(job, "hdfs://master:9999/user/hadoop-sny/mr/filetype/text"); //3 获取读取文件的格式 TextInputFormat inputFormat = TextInputFormat.class.newInstance(); //4 获取需要读取文件的数据块的分区信息 //4.1 获取文件被分成多少数据块了 JobID jobID = new JobID("jobId", 123); JobContext jobContext = new JobContextImpl(job.getConfiguration(), jobID); List<InputSplit> inputSplits = inputFormat.getSplits(jobContext); //读取每一个数据块的数据 inputSplits.forEach(new Consumer<InputSplit>() { @Override public void accept(InputSplit inputSplit) { TaskAttemptID attemptId = new TaskAttemptID("jobTrackerId", 123, TaskType.MAP, 0, 0); TaskAttemptContext hadoopAttemptContext = new TaskAttemptContextImpl(job.getConfiguration(), attemptId); RecordReader reader = inputFormat.createRecordReader(inputSplit, hadoopAttemptContext); try { reader.initialize(inputSplit, hadoopAttemptContext); System.out.println("<key,value>"); System.out.println("-----------"); while (reader.nextKeyValue()) { System.out.println("<"+reader.getCurrentKey() + "," + reader.getCurrentValue()+ ">" ); } } catch (IOException e) { e.printStackTrace(); } catch (InterruptedException e) { e.printStackTrace(); } } }); } }
0x03 校验结果
1. 启动集群
a. 启动HDFS集群，
start-dfs.sh
PS：如不启动会处于一个卡死状态
Exception in thread "main" java.net.ConnectException: Call From shaonaiyi/192.168.98.205 to master:9999 failed on connection exception: java.net.ConnectException: Connection refused: no further information; For more details see: http://wiki.apache.org/hadoop/ConnectionRefused
2. 执行写Text文件格式代码
a. 直接在Win上执行，如无报错，去集群查看结果：
hadoop fs -ls hdfs://master:9999/user/hadoop-sny/mr/filetype hadoop fs -cat hdfs://master:9999/user/hadoop-sny/mr/filetype/text/*
PS：如果报权限错误：
Exception in thread "main" org.apache.hadoop.security.AccessControlException: Permission denied: user=Administrator, access=WRITE, inode="/user/hadoop-sny":hadoop-sny:supergroup:drwxr-xr-x
解决方案：需要去集群里修改权限
hadoop fs -mkdir -p hdfs://master:9999/user/hadoop-sny/mr/filetype hadoop fs -chmod 757 hdfs://master:9999/user/hadoop-sny/mr/filetype
3. 执行读Text文件格式代码
a. 可得如下结果
System.out.println("<"+reader.getCurrentKey() + "," + reader.getCurrentValue()+ ">" );
reader.getCurrentKey()为偏移量，每一行的起始值
reader.getCurrentValue()为具体的值
与MapReduce单词计数例子时一样。
0x04 可能出现的问题解决
1. 类无法导入
请参考文章：“Usage of API documented as @since 1.8+”报错的解决办法
0xFF 总结
Hadoop支持的文件格式系列：
Hadoop支持的文件格式之Text
Hadoop支持的文件格式之Avro
Hadoop支持的文件格式之Parquet
Hadoop支持的文件格式之SequenceFile
项目实战中，文章：网站用户行为分析项目之会话切割（二）中使用的存储格式是Parquet。
