不使用Sqoop流程，利用CacheManager直接完成SparkSQL数据流直接回写Oracle

以前都是使用Sqoop来完成数据从生成的hdfs数据存储上来抽取至oracle的数据库：sqoop抽取语句：
sqoop export --connect "jdbc:oracle:thin:@ip:port:sid" --username 用户名 --password 密码 --table sid.表名 --export-dir hdfs://nameservice1/user/XXX(hdfs地址) --fields-terminated-by "\001" --null-non-string '' --null-string '' -m 10;

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 由于项目需求我们现在要完成在代码中省城所需字段之后，直接回写到oracle中，因为数据量每天都很大，用实例或者List存有很大的局限性，可能会出现内存异常等不可预料的东西，所以我通过缓存器机制来存储数据，然后进行生成结果的临时表直接回写（后面做的hbase接口封装批量提交也比较类似）
 废话不多说直接上代码：
 1、建立缓存实体
 package usi.java.oracle;

/**

@author HK
@date 2011-2-15 下午06:45:57
*/
public class Cache {
private String key;
private Object value;
private long timeOut;
private boolean expired;
public Cache() {
super();
}
public Cache(String key, String value, long timeOut, boolean expired) {
this.key = key;
this.value = value;
this.timeOut = timeOut;
this.expired = expired;
}
public String getKey() {
return key;
}
public long getTimeOut() {
return timeOut;
}
public Object getValue() {
return value;
}
public void setKey(String string) {
key = string;
}
public void setTimeOut(long l) {
timeOut = l;
}
public void setValue(Object object) {
value = object;
}
public boolean isExpired() {
return expired;
}
public void setExpired(boolean b) {
expired = b;
}
}

2、建立缓存控制器
package usi.java.oracle;

import java.util.Date;
import java.util.HashMap;

/**

@author HK
@date 2011-2-15 下午09:40:00
*/
public class CacheManager {
private static HashMap cacheMap = new HashMap();
/**
- This class is singleton so private constructor is used.
  */
  private CacheManager() {
  super();
  }
  /**
- returns cache item from hashmap
- @param key
- @return Cache
  */
  private synchronized static Cache getCache(String key) {
  return (Cache)cacheMap.get(key);
  }
  /**
- Looks at the hashmap if a cache item exists or not
- @param key
- @return Cache
  */
  private synchronized static boolean hasCache(String key) {
  return cacheMap.containsKey(key);
  }
  /**
- Invalidates all cache
  */
  public synchronized static void invalidateAll() {
  cacheMap.clear();
  }
  /**
- Invalidates a single cache item
- @param key
  */
  public synchronized static void invalidate(String key) {
  cacheMap.remove(key);
  }
  /**
- Adds new item to cache hashmap
- @param key
- @return Cache
  */
  private synchronized static void putCache(String key, Cache object) {
  cacheMap.put(key, object);
  }
  /**
- Reads a cache item's content
- @param key
- @return
  */
  public static Cache getContent(String key) {
  if (hasCache(key)) {
  Cache cache = getCache(key);
  if (cacheExpired(cache)) {
  cache.setExpired(true);
  }
  return cache;
  } else {
  return null;
  }
  }
  /**
- @param key
- @param content
- @param ttl
  */
  public static void putContent(String key, Object content, long ttl) {
  Cache cache = new Cache();
  cache.setKey(key);
  cache.setValue(content);
  cache.setTimeOut(ttl + new Date().getTime());
  cache.setExpired(false);
  putCache(key, cache);
  }
  /* @modelguid {172828D6-3AB2-46C4-96E2-E72B34264031} /
  private static boolean cacheExpired(Cache cache) {
  if (cache == null) {
  return false;
  }
  long milisNow = new Date().getTime();
  long milisExpire = cache.getTimeOut();
  if (milisExpire < 0) { // Cache never expires
  return false;
  } else if (milisNow >= milisExpire) {
  return true;
  } else {
  return false;
  }
  }

}

3、建立需要导出数据对象
package usi.java.oracle;

public class TaskAll {
private String mme_eid;
private String mme_editor;
private String entitytype_eid;
private String project_eid;
private String resource_eid;
public String getMme_eid() {
return mme_eid;
}
public void setMme_eid(String mme_eid) {
this.mme_eid = mme_eid;
}
public String getMme_editor() {
return mme_editor;
}
public void setMme_editor(String mme_editor) {
this.mme_editor = mme_editor;
}
public String getEntitytype_eid() {
return entitytype_eid;
}
public void setEntitytype_eid(String entitytype_eid) {
this.entitytype_eid = entitytype_eid;
}
public String getProject_eid() {
return project_eid;
}
public void setProject_eid(String project_eid) {
this.project_eid = project_eid;
}
public String getResource_eid() {
return resource_eid;
}
public void setResource_eid(String resource_eid) {
this.resource_eid = resource_eid;
}

}
5、执行逻辑主体，回写数据，批量提交

package usi.java.oracle;

import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
//import java.sql.ResultSet;
import java.util.List;

import org.apache.spark.SparkConf;
import org.apache.spark.SparkContext;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.hive.HiveContext;

public class redict_to_171ora {
public static void main(String[] args) {
SparkConf sc = new SparkConf().setAppName("redict_to_171ora");
SparkContext jsc = new SparkContext(sc);
HiveContext hc = new HiveContext(jsc);
String hivesql1="select t.mme_eid,t.mme_editor,t.entitytype_eid,t.project_eid,t.resource_eid from usi_odso.c_taskall t limit 150000";

    DataFrame redict_to_171ora= hc.sql(hivesql1);
    //redict_to_171ora.registerTempTable("hivesql1");       
    List collect=redict_to_171ora.javaRDD().collect();

    int o=0;
    for (Row lists: collect){
        TaskAll task=new TaskAll();
        task.setMme_eid(lists.getString(0));
        task.setMme_editor(lists.getString(1));
        task.setEntitytype_eid(lists.getString(2));
        task.setProject_eid(lists.getString(3));
        task.setResource_eid(lists.getString(4));
        CacheManager.putContent(o+"", task, 30000000);
        o++;
    /* System.out.println(lists.size());
     System.out.println(lists.getString(0));
     System.out.println(lists.getString(1));
     System.out.println(lists.getString(2));
     System.out.println(lists.getString(3));
     System.out.println(lists.getString(4));*/
      }
    System.out.println(o);

        Connection con = null;// 创建一个数据库连接
        PreparedStatement pre = null;// 创建预编译语句对象，一般都是用这个而不用Statement
        //ResultSet result = null;// 创建一个结果集对象
        try
        {
            Class.forName("oracle.jdbc.driver.OracleDriver");// 加载Oracle驱动程序
            System.out.println("开始尝试连接数据库！");
            String url = "jdbc:oracle:" + "thin:@ip:1521:sid";// 127.0.0.1是本机地址，XE是精简版Oracle的默认数据库名
            String user = "user";// 用户名,系统默认的账户名
            String password = "password";// 你安装时选设置的密码
            con = DriverManager.getConnection(url, user, password);// 获取连接
            System.out.println("连接成功！");
            String sql = "insert into c_taskall_test(mme_eid,mme_editor,entitytype_eid,project_eid,resource_eid) values(?,?,?,?,?)";// 预编译语句，“？”代表参数
            pre = con.prepareStatement(sql);// 实例化预编译语句
            for(int i=0;i

}

            
            
                            

                新闻标题：不使用Sqoop流程，利用CacheManager直接完成SparkSQL数据流直接回写Oracle                

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