gpt4 book ai didi

java - 将数据写入 MySQL 数据库时 map reduce 作业中的类转换异常

转载 作者:可可西里 更新时间:2023-11-01 15:33:24 26 4
gpt4 key购买 nike

我正在尝试使用 map reduce 作业将数据加载到 mysql 数据库中,但是我遇到了类转换异常错误,这是我使用的过程:

我首先创建一个实现了 Writable 和 DBWritable 接口(interface)的 DBOutputWritable 类。然后我使用我的 reduce 作业将数据写入数据库,但是当我运行该作业时,它失败了,提示有错误:

java.lang.ClassCastException: com.amalwa.hadoop.DataBaseLoadMapReduce.DBOutputWritable cannot be cast to org.apache.hadoop.mapreduce.lib.db.DBWritable

at org.apache.hadoop.mapreduce.lib.db.DBOutputFormat$DBRecordWriter.write(DBOutputFormat.java:66)
at org.apache.hadoop.mapred.ReduceTask$NewTrackingRecordWriter.write(ReduceTask.java:601)
at org.apache.hadoop.mapreduce.TaskInputOutputContext.write(TaskInputOutputContext.java:80)
at com.amalwa.hadoop.DataBaseLoadMapReduce.DBMapReduce$DBReducer.reduce(DBMapReduce.java:58)
at com.amalwa.hadoop.DataBaseLoadMapReduce.DBMapReduce$DBReducer.reduce(DBMapReduce.java:53)
at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:176)
at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:663)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:426)
at org.apache.hadoop.mapred.Child$4.run(Child.java:255)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1132)
at org.apache.hadoop.mapred.Child.main(Child.java:249)

我很难弄清楚,如果我的类实现了我们使用 map reduce 作业写入数据库所需的接口(interface),那么为什么会出现类转换异常。我正在实现所需的所有功能。

谢谢。

DBOutputWritable
package com.amalwa.hadoop.DataBaseLoadMapReduce;

import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;

import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapred.lib.db.DBWritable;


public class DBOutputWritable implements Writable, DBWritable{

private String keyValue;
private String response;

public DBOutputWritable(String keyValue, String response){
this.keyValue = keyValue;
this.response = response;
}

public void readFields(DataInput resultSet) throws IOException {

}

public void readFields(ResultSet resultSet) throws SQLException {
keyValue = resultSet.getString(1);
response = resultSet.getString(2);
}

public void write(PreparedStatement preparedStatement) throws SQLException {
preparedStatement.setString(1, keyValue);
preparedStatement.setString(2, response);
}

public void write(DataOutput dataOutput) throws IOException {

}

}

reducer :

public static class DBReducer extends Reducer<Text, Text, DBOutputWritable, NullWritable>{

public void reduce(Text requestKey, Iterable<Text> response, Context context){
for(Text responseSet: response){
try{
context.write(new DBOutputWritable(requestKey.toString(), responseSet.toString()), NullWritable.get());
}catch(IOException e){
System.err.println(e.getMessage());
}
catch(InterruptedException e){
System.err.println(e.getMessage());
}
}
}
}

映射器:

公共(public)静态类 DBMapper 扩展 Mapper{

    public void map(LongWritable key, Text value, Context context) throws IOException{
String tweetInfo = value.toString();
String[] myTweetData = tweetInfo.split(",", 2);
String requestKey = myTweetData[0];
String response = myTweetData[1];
try {
context.write(new Text(requestKey), new Text(response));
} catch (InterruptedException e) {
System.err.println(e.getMessage());;
}
}
}

主类:

public static void main(String[] args) throws Exception{
Configuration conf = new Configuration();
DBConfiguration.configureDB(conf, "com.mysql.jdbc.Driver", "jdbc:mysql://ec2-54-152-254-194.compute-1.amazonaws.com/TWEETS", "user", "password");
Job job = new Job(conf);
job.setJarByClass(DBMapReduce.class);
job.setMapperClass(DBMapper.class);
job.setReducerClass(DBReducer.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
job.setOutputKeyClass(DBOutputWritable.class);
job.setOutputValueClass(NullWritable.class);
job.setInputFormatClass(TextInputFormat.class);
job.setOutputFormatClass(DBOutputFormat.class);
FileInputFormat.addInputPath(job, new Path(args[1]));
DBOutputFormat.setOutput(job, "TWEET_INFO", new String[] { "REQUESTKEY", "TWEET_DETAILS" });
System.exit(job.waitForCompletion(true) ? 0 : 1);
}

最佳答案

看来您正在混合使用旧的 (org.apache.hadoop.mapred.*) 和新的 (org.apache.hadoop.mapreduce.*) MapReduce API,它正在引起冲突。我怀疑您的 DBReducer 类正在从新 API 扩展 Reducer 类,但您的 DBOutputWritable 正在实现 DBWritable 来自旧 API。

您应该在整个实现过程中仅选择这些 API 之一,这意味着所有导入的 MapReduce 类型都以相同的包前缀开头。

请注意,通常您在使用旧 API 时实现 MapReduce 接口(interface),并在使用新 API 时扩展 MapReduce 基类。

关于java - 将数据写入 MySQL 数据库时 map reduce 作业中的类转换异常,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/29134892/

26 4 0
Copyright 2021 - 2024 cfsdn All Rights Reserved 蜀ICP备2022000587号
广告合作:1813099741@qq.com 6ren.com