import java.io.*;
import java.sql.PreparedStatement;
import java.sql.ResultSet;
import java.sql.SQLException;
import org.apache.hadoop.io.Writable;
import org.apache.hadoop.mapreduce.lib.db.DBWritable;
public class DBInputWritable implements Writable, DBWritable
{
String symbol;
String date;
double open;
double high;
double low;
double close;
int volume;
double adjClose;
//private final static SimpleDateFormat sdf = new SimpleDateFormat("yyyy-MM-dd");
public void readFields(DataInput in) throws IOException
{
symbol=in.readLine();
date=in.readLine();
open=in.readDouble();
high=in.readDouble();
low=in.readDouble();
close=in.readDouble();
volume=in.readInt();
adjClose=in.readDouble();
}
public void readFields(ResultSet rs) throws SQLException
{
symbol = rs.getString(2);
date = rs.getString(3);
open = rs.getDouble(4);
high = rs.getDouble(5);
low = rs.getDouble(6);
close = rs.getDouble(7);
volume = rs.getInt(8);
adjClose = rs.getDouble(9);
}
public void write(DataOutput out) throws IOException
{
}
public void write( PreparedStatement ps) throws SQLException
{
}
public String getSymbol()
{
return symbol;
}
public String getDate()
{
return date;
}
public double getOpen()
{
return open;
}
public double getHigh()
{
return high;
}
public double getLow()
{
return low;
}
public double getClose()
{
return close;
}
public int getVolume()
{
return volume;
}
public double getAdjClose()
{
return adjClose;
}
}
public class DBOutputWritable implements Writable, DBWritable
{
String symbol;
String date;
double open;
double high;
double low;
double close;
int volume;
double adjClose;
;
public DBOutputWritable(String symbol,String date,String open,String high,String low,String close,String volume,String adjClose)
{
this.symbol=symbol;
this.date=date;
this.open=Double.parseDouble(open);
this.high=Double.parseDouble(high);
this.low=Double.parseDouble(low);
this.close=Double.parseDouble(close);
this.volume=Integer.parseInt(volume);
this.adjClose=Double.parseDouble(adjClose);
}
public void readFields(DataInput in) throws IOException
{
}
public void readFields(ResultSet rs) throws SQLException
{
}
public void write(DataOutput out) throws IOException
{
out.writeChars(symbol);
out.writeChars(date);
out.writeDouble(open);
out.writeDouble(high);
out.writeDouble(low);
out.writeDouble(close);
out.writeInt(volume);
out.writeDouble(adjClose);
}
public void write(PreparedStatement ps) throws SQLException
{
ps.setString(1,symbol);
ps.setString(2,date);
ps.setDouble(3,open);
ps.setDouble(4,high);
ps.setDouble(5,low);
ps.setDouble(6,close);
ps.setInt(7,volume);
ps.setDouble(8,adjClose);
}
}
public class Map extends Mapper<LongWritable,DBInputWritable,Text,Text>
{
public void map(LongWritable key, DBInputWritable value, Context ctx)
{
try
{
Text set;
set= new Text(value.getDate());
String line = value.getSymbol()+","+value.getDate()+","+value.getOpen()+","+value.getHigh()+","+value.getLow()+","+value.getClose()+","+value.getVolume()+","+value.getAdjClose();
ctx.write(set,new Text(line));
}
catch(IOException e)
{
e.printStackTrace();
}
catch(InterruptedException e)
{
e.printStackTrace();
}
}
}
public class Reduce extends Reducer<Text, Text, DBOutputWritable, NullWritable>
{
public void reduce(Text key, Text value, Context ctx)
{
try
{
String []line= value.toString().split(",");
String sym=line[0];
String dt=line[1];
String opn=line[2];
String hgh=line[3];
String lw=line[4];
String cls=line[5];
String vlm=line[6];
String adcls=line[7];
ctx.write(new DBOutputWritable(sym,dt,opn,hgh,lw,cls,vlm,adcls),NullWritable.get());
}
catch(IOException e)
{
e.printStackTrace();
}
catch(InterruptedException e)
{
e.printStackTrace();
}
}
}
public class Main
{
public static void main(String [] args) throws Exception
{
Configuration conf = new Configuration();
DBConfiguration.configureDB(conf,
"com.mysql.jdbc.Driver", //Driver Class
"jdbc:mysql://192.168.198.128:3306/testDb", //DB URL
"sqoopuser", //USERNAME
"passphrase"); //PASSWORD
Job job = new Job(conf);
job.setJarByClass(Main.class);
job.setMapperClass(Map.class);
job.setReducerClass(Reduce.class);
job.setMapOutputKeyClass(Text.class);
job.setMapOutputValueClass(Text.class);
job.setOutputKeyClass(DBOutputWritable.class);
job.setOutputValueClass(NullWritable.class);
job.setInputFormatClass(DBInputFormat.class);
job.setOutputFormatClass(DBOutputFormat.class);
DBInputFormat.setInput(
job,
DBInputWritable.class,
"aapldata", //input table name
null,
null,
new String[] {"stock","symbol", "date" ,"open", "high", "low", "close", "volume", "adjClose"}
//Table Columns
);
DBOutputFormat.setOutput(
job,
"aapldatanew", //Output Table Name
new String[] {"symbol", "date" ,"open", "high", "low", "close", "volume", "adjClose"}
//Table Columns
);
System.exit(job.waitForCompletion(true) ? 0 : 1);
}
}
我认为Code是完美的。但我仍然遇到以下错误：
14/11/26 22:09:47 INFO mapred.JobClient: map 100% reduce 0%
14/11/26 22:09:55 INFO mapred.JobClient: map 100% reduce 33%
14/11/26 22:09:58 INFO mapred.JobClient: Task Id : attempt_201411262208_0001_r_000000_2, Status : FAILED
java.lang.ClassCastException: org.apache.hadoop.io.Text cannot be cast to org.apache.hadoop.mapreduce.lidb.DBWritable
at org.apache.hadoop.mapreduce.lib.db.DBOutputFormat$DBRecordWriter.write(DBOutputFormat.java:66
at org.apache.hadoop.mapred.ReduceTask$NewTrackingRecordWriter.write(ReduceTask.java:586)
at org.apache.hadoop.mapreduce.TaskInputOutputContext.write(TaskInputOutputContext.java:80)
at org.apache.hadoop.mapreduce.Reducer.reduce(Reducer.java:156)
at org.apache.hadoop.mapreduce.Reducer.run(Reducer.java:177)
at org.apache.hadoop.mapred.ReduceTask.runNewReducer(ReduceTask.java:649)
at org.apache.hadoop.mapred.ReduceTask.run(ReduceTask.java:418)
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:1190)
at org.apache.hadoop.mapred.Child.main(Child.java:249)
需要您宝贵的见解。
答案 0 :(得分：0)
在map课程中，将输入视为文字而不是DBInputWritable：
public class Map extends Mapper {
public void map(LongWritable key,Text value, Context ctx)
答案 1 :(得分：0)
我可以找到2个问题：
映射器输出键，值类与作业配置不匹配。请你好。 作业配置时的映射器。 请根据需要更正。考虑到映射键，我接近第二个问题，值对是你正确的选择。
您没有覆盖 reduce方法!!
根据您的job配置，签名应为：
public void reduce(Text key, Iterable<Text> values, Context context){
//...your code
}
您的例外说明
由于您没有覆盖Reducer的reduce，因此reducer将使用默认实现（称为identity reducer）减少。源代码：
protected void reduce(KEYIN key, Iterable<VALUEIN> values, Context context
) throws IOException, InterruptedException {
for(VALUEIN value: values) {
context.write((KEYOUT) key, (VALUEOUT) value);
}
}
如源代码中所指定的，它只是迭代值并使用输出键值calsses来编写它。但在您的情况下，中间对（即IntWritable，Text）与DBoutputFormat对不匹配。
HTH！