Error inserting data into orc table - orc

Question

Even am facing the same problem of loading data from a text format table to orc format table.When i try to load data from a text format table to orc table am getting this error "Exception in thread "main" java.sql.SQLException: Error while processing statement: FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask"
This is my code:
import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.SQLException;
import java.sql.Statement;
import org.apache.hive.jdbc.HiveDriver;
public class HiveJdbcClient {
private static String driverName = "org.apache.hive.jdbc.HiveDriver";
public static void main(String[] args) throws SQLException {
try {
Class.forName(driverName);
} catch (ClassNotFoundException e) {
e.printStackTrace();
System.exit(1);
}
Connection con = DriverManager.getConnection("jdbc:hive2://hdn01.sasken.com:10000/default", "","");
System.out.println("Connected to Hive");
Statement stmt = con.createStatement();
String tempTable = "tempTable";
String orcTable= "orcTable";
stmt.execute("CREATE TABLE IF NOT EXISTS "+ tempTable +" (key int, value string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' STORED AS TEXTFILE");
stmt.execute("CREATE TABLE IF NOT EXISTS " + orcTable + "(key int, value string) CLUSTERED BY (key) INTO 2 BUCKETS STORED AS ORC TBLPROPERTIES ('transactional'='true')");
String filepath = "/home/ee208961/spark-hive/resto.csv";
stmt.execute("LOAD DATA LOCAL INPATH '" + filepath + "' OVERWRITE INTO TABLE " + tempTable);
stmt.execute("INSERT OVERWRITE TABLE "+ orcTable +" SELECT * FROM "+ tempTable);
String sql = "select * from " + orcTable;
System.out.println("Running: " + sql);
ResultSet res = stmt.executeQuery(sql);
while (res.next()) {
System.out.println(String.valueOf(res.getInt(1)) + "\t" + res.getString(2));
}
am getting error on this line "stmt.execute("INSERT OVERWRITE TABLE "+ orcTable +" SELECT * FROM "+ tempTable)"
can any1 please help me in fixing this issue?
Thanku.