mapreduce导出MSSQL的数据到HDFS

　　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。