今天想通过一些数据，来测试一下我的《基于信息熵的无字典分词算法》这篇文章的正确性。就写了一下MapReduce程序从MSSQL SERVER2008数据库里取数据分析。程序发布到hadoop机器上运行报SQLEXCEPTION错误
奇怪了，我的SQL语句中没有LIMIT，这LIMIT哪来的。我翻看了DBInputFormat类的源码，
protected RecordReader<LongWritable, T> createDBRecordReader(DBInputSplit split,
Configuration conf) throws IOException {
@SuppressWarnings("unchecked")
Class<T> inputClass = (Class<T>) (dbConf.getInputClass());
try {
// use database product name to determine appropriate record reader.
if (dbProductName.startsWith("ORACLE")) {
// use Oracle-specific db reader.
return new OracleDBRecordReader<T>(split, inputClass,
conf, createConnection(), getDBConf(), conditions, fieldNames,
tableName);
} else if (dbProductName.startsWith("MYSQL")) {
// use MySQL-specific db reader.
return new MySQLDBRecordReader<T>(split, inputClass,
conf, createConnection(), getDBConf(), conditions, fieldNames,
tableName);
} else {
// Generic reader.
return new DBRecordReader<T>(split, inputClass,
conf, createConnection(), getDBConf(), conditions, fieldNames,
tableName);
}
} catch (SQLException ex) {
throw new IOException(ex.getMessage());
}
}
DBRecordReader的源码
protected String getSelectQuery() {
StringBuilder query = new StringBuilder();
// Default codepath for MySQL, HSQLDB, etc. Relies on LIMIT/OFFSET for splits.
if(dbConf.getInputQuery() == null) {
query.append("SELECT ");
for (int i = 0; i < fieldNames.length; i++) {
query.append(fieldNames[i]);
if (i != fieldNames.length -1) {
query.append(", ");
}
}
query.append(" FROM ").append(tableName);
query.append(" AS ").append(tableName); //in hsqldb this is necessary
if (conditions != null && conditions.length() > 0) {
query.append(" WHERE (").append(conditions).append(")");
}
String orderBy = dbConf.getInputOrderBy();
if (orderBy != null && orderBy.length() > 0) {
query.append(" ORDER BY ").append(orderBy);
}
} else {
//PREBUILT QUERY
query.append(dbConf.getInputQuery());
}
try {
query.append(" LIMIT ").append(split.getLength()); //问题所在
query.append(" OFFSET ").append(split.getStart());
} catch (IOException ex) {
// Ignore, will not throw.
}
return query.toString();
}
终于找到原因了。
原来，hadoop只实现了Mysql的DBRecordReader（MySQLDBRecordReader）和ORACLE的DBRecordReader（OracleDBRecordReader）。
原因找到了，我参考着OracleDBRecordReader实现了MSSQL SERVER的DBRecordReader代码如下：
MSSQLDBInputFormat的代码：
/**
*
*/
package org.apache.hadoop.mapreduce.lib.db; import java.io.IOException;
import java.sql.SQLException; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.RecordReader; /**
* @author summer
* MICROSOFT SQL SERVER
*/
public class MSSQLDBInputFormat<T extends DBWritable> extends DBInputFormat<T> { public static void setInput(Job job,
Class<? extends DBWritable> inputClass,
String inputQuery, String inputCountQuery,String rowId) {
job.setInputFormatClass(MSSQLDBInputFormat.class);
DBConfiguration dbConf = new DBConfiguration(job.getConfiguration());
dbConf.setInputClass(inputClass);
dbConf.setInputQuery(inputQuery);
dbConf.setInputCountQuery(inputCountQuery);
dbConf.setInputFieldNames(new String[]{rowId});
} @Override
protected RecordReader<LongWritable, T> createDBRecordReader(
org.apache.hadoop.mapreduce.lib.db.DBInputFormat.DBInputSplit split,
Configuration conf) throws IOException { @SuppressWarnings("unchecked")
Class<T> inputClass = (Class<T>) (dbConf.getInputClass());
try { return new MSSQLDBRecordReader<T>(split, inputClass,
conf, createConnection(), getDBConf(), conditions, fieldNames,
tableName); } catch (SQLException ex) {
throw new IOException(ex.getMessage());
} } }
MSSQLDBRecordReader的代码：
/**
*
*/
package org.apache.hadoop.mapreduce.lib.db; import java.io.IOException;
import java.sql.Connection;
import java.sql.SQLException; import org.apache.hadoop.conf.Configuration; /**
* @author summer
*
*/
public class MSSQLDBRecordReader <T extends DBWritable> extends DBRecordReader<T>{ public MSSQLDBRecordReader(DBInputFormat.DBInputSplit split,
Class<T> inputClass, Configuration conf, Connection conn, DBConfiguration dbConfig,
String cond, String [] fields, String table) throws SQLException {
super(split, inputClass, conf, conn, dbConfig, cond, fields, table); } @Override
protected String getSelectQuery() {
StringBuilder query = new StringBuilder();
DBConfiguration dbConf = getDBConf();
String conditions = getConditions();
String tableName = getTableName();
String [] fieldNames = getFieldNames(); // Oracle-specific codepath to use rownum instead of LIMIT/OFFSET.
if(dbConf.getInputQuery() == null) {
query.append("SELECT "); for (int i = 0; i < fieldNames.length; i++) {
query.append(fieldNames[i]);
if (i != fieldNames.length -1) {
query.append(", ");
}
} query.append(" FROM ").append(tableName);
if (conditions != null && conditions.length() > 0)
query.append(" WHERE ").append(conditions);
String orderBy = dbConf.getInputOrderBy();
if (orderBy != null && orderBy.length() > 0) {
query.append(" ORDER BY ").append(orderBy);
}
} else {
//PREBUILT QUERY
query.append(dbConf.getInputQuery());
} try {
DBInputFormat.DBInputSplit split = getSplit();
if (split.getLength() > 0){
String querystring = query.toString();
String id = fieldNames[0];
query = new StringBuilder();
query.append("SELECT TOP "+split.getLength()+"* FROM ( ");
query.append(querystring);
query.append(" ) a WHERE " + id +" NOT IN (SELECT TOP ").append(split.getEnd());
query.append(" "+id +" FROM (");
query.append(querystring);
query.append(" ) b");
query.append(" )");
System.out.println("----------------------MICROSOFT SQL SERVER QUERY STRING---------------------------");
System.out.println(query.toString());
System.out.println("----------------------MICROSOFT SQL SERVER QUERY STRING---------------------------");
}
} catch (IOException ex) {
// ignore, will not throw.
} return query.toString();
} }
mapreduce的代码
/**
*
*/
package com.nltk.sns.mapreduce; import java.io.IOException;
import java.util.List; import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.MRJobConfig;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.lib.db.DBConfiguration;
import org.apache.hadoop.mapreduce.lib.db.MSSQLDBInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat; import com.nltk.utils.ETLUtils; /**
* @author summer
*
*/
public class LawDataEtl { public static class CaseETLMapper extends
Mapper<LongWritable, LawCaseRecord, LongWritable, Text>{ static final int step = 6; LongWritable key = new LongWritable(1);
Text value = new Text(); @Override
protected void map(
LongWritable key,
LawCaseRecord lawCaseRecord,
Mapper<LongWritable, LawCaseRecord, LongWritable, Text>.Context context)
throws IOException, InterruptedException { System.out.println("-----------------------------"+lawCaseRecord+"------------------------------"); key.set(lawCaseRecord.id);
String source = ETLUtils.format(lawCaseRecord.source);
List<LawCaseWord> words = ETLUtils.split(lawCaseRecord.id,source, step);
for(LawCaseWord w:words){
value.set(w.toString());
context.write(key, value);
}
}
} static final String driverClass = "com.microsoft.sqlserver.jdbc.SQLServerDriver";
static final String dbUrl = "jdbc:sqlserver://192.168.0.1:1433;DatabaseName=XXX";
static final String uid = "XXX";
static final String pwd = "XXX";
static final String inputQuery = "select id,source from tablename where id<1000";
static final String inputCountQuery = "select count(1) from LawDB.dbo.case_source where id<1000";
static final String jarClassPath = "/user/lib/sqljdbc4.jar";
static final String outputPath = "hdfs://ubuntu:9000/user/test";
static final String rowId = "id"; public static Job configureJob(Configuration conf) throws Exception{ String jobName = "etlcase";
Job job = Job.getInstance(conf, jobName); job.addFileToClassPath(new Path(jarClassPath));
MSSQLDBInputFormat.setInput(job, LawCaseRecord.class, inputQuery, inputCountQuery,rowId);
job.setJarByClass(LawDataEtl.class); FileOutputFormat.setOutputPath(job, new Path(outputPath)); job.setMapOutputKeyClass(LongWritable.class);
job.setMapOutputValueClass(Text.class);
job.setOutputKeyClass(LongWritable.class);
job.setOutputValueClass(Text.class);
job.setMapperClass(CaseETLMapper.class); return job;
} public static void main(String[] args) throws Exception{ Configuration conf = new Configuration();
FileSystem fs = FileSystem.get(conf);
fs.delete(new Path(outputPath), true); DBConfiguration.configureDB(conf, driverClass, dbUrl, uid, pwd);
conf.set(MRJobConfig.NUM_MAPS, String.valueOf(10));
Job job = configureJob(conf);
System.out.println("------------------------------------------------");
System.out.println(conf.get(DBConfiguration.DRIVER_CLASS_PROPERTY));
System.out.println(conf.get(DBConfiguration.URL_PROPERTY));
System.out.println(conf.get(DBConfiguration.USERNAME_PROPERTY));
System.out.println(conf.get(DBConfiguration.PASSWORD_PROPERTY));
System.out.println("------------------------------------------------");
System.exit(job.waitForCompletion(true) ? 0 : 1); }
}
辅助类的代码：
/**
*
*/
package com.nltk.sns; import java.util.ArrayList;
import java.util.List; import org.apache.commons.lang.StringUtils; /**
* @author summer
*
*/
public class ETLUtils { public final static String NULL_CHAR = "";
public final static String PUNCTUATION_REGEX = "[(\\pP)&&[^\\|\\｛\\｝\\＃]]+";
public final static String WHITESPACE_REGEX = "[\\p{Space}]+"; public static String format(String s){ return s.replaceAll(PUNCTUATION_REGEX, NULL_CHAR).replaceAll(WHITESPACE_REGEX, NULL_CHAR);
} public static List<String> split(String s,int stepN){ List<String> splits = new ArrayList<String>();
if(StringUtils.isEmpty(s) || stepN<1)
return splits;
int len = s.length();
if(len<=stepN)
splits.add(s);
else{
for(int j=1;j<=stepN;j++)
for(int i=0;i<=len-j;i++){
String key = StringUtils.mid(s, i,j);
if(StringUtils.isEmpty(key))
continue;
splits.add(key);
}
}
return splits; } public static void main(String[] args){ String s="谢婷婷等与姜波等";
int stepN = 2;
List<String> splits = split(s,stepN);
System.out.println(splits);
}
}
运行成功了
代码初略的实现，主要是为了满足我的需求，大家可以根据自己的需要进行修改。
实际上DBRecordReader作者实现的并不好，我们来看DBRecordReader、MySQLDBRecordReader和OracleDBRecordReader源码，DBRecordReader和MySQLDBRecordReader耦合度太高。一般而言，就是对于没有具体实现的数据库DBRecordReader也应该做到运行不报异常，无非就是采用单一的SPLIT和单一的MAP。