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      JdbcDialect dialect = new JdbcDialect() {
            @Override
            public boolean canHandle(String url) {
                return url.startsWith("jdbc:oracle") 
|| url.contains("oracle");
            }

            @Override
            public Option<JdbcType> getJDBCType(DataType dt) {
                if(DataTypes.StringType.sameType(dt)) {

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/**
 * :: DeveloperApi ::
 * Default Oracle dialect, mapping a nonspecific numeric type to a general decimal type.
 */
@DeveloperApi
case object OracleDialect extends JdbcDialect {
  override def canHandle(url: String): Boolean = 
url.startsWith("jdbc:oracle")
  override def getCatalystType(
      sqlType: Int, typeName: String, size: Int,

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—NEVER EVER EVER DO 
BEGIN BATCH; 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (1, 'Jim', 'James') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (2, 'Ernie', 'Orosco') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (3, 'Jose', 'Garza') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (4, 'Sammy', 'Mason') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (5, 'Larry', 'Bird') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (6, 'Jim', 'Smith') 
APPLY BATCH; 

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BEGIN BATCH; 
UPDATE users SET name='Jim' where id =1; 
UPDATE users_by_ssn set name='Jim' where ssn='888–99–9999'; 
APPLY BATCH;

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—NEVER EVER EVER DO 
BEGIN UNLOGGED BATCH;
INSERT INTO tester.users (userID, firstName, lastName) VALUES (1, 'Jim', 'James') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (2, 'Ernie', 'Orosco') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (3, 'Jose', 'Garza') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (4, 'Sammy', 'Mason') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (5, 'Larry', 'Bird') 
INSERT INTO tester.users (userID, firstName, lastName) VALUES (6, 'Jim', 'Smith') 
APPLY BATCH; 

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BEGIN UNLOGGED BATCH; 
INSERT INTO weather_readings (date, timestamp, temp) values (20140822,'2014-08-22T11:00:00.00+0000', 98.2); 
INSERT INTO weather_readings (date, timestamp, temp) values (20140822,'2014-08-22T11:00:15.00+0000', 99.2); 
APPLY BATCH; 

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/**
 * I HAVE NOT BEEN FULLY TESTED DO NOT USE ME IN PRODUCTION CODE THERE ARE NO WARRANTIES
 */ 
 public class BulkLoader {

private final int threads;
private final String[] contactHosts;

public BulkLoader(int threads, String...contactHosts){
    this.threads = threads;

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/**
 * I HAVE NOT BEEN FULLY TESTED DO NOT USE ME IN PRODUCTION CODE THERE ARE NO WARRANTIES
 * This is with using the approach in the previous blog post
 */ 
public class BulkLoader {

private final int threads;
private final String[] contactHosts;

public BulkLoader(int threads, String...contactHosts){

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import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark._
import org.apache.spark.storage._
import org.apache.spark.streaming._

object MapWithState {


  val batchCountKey = "batchCount"

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public class KeepAlive{
     public static void main(String[] args){
     Cluster cluster = Cluster.builder().addContactPoint("foo")
                .withSocketOptions(new SocketOptions().setKeepAlive(true))
                .build();
     }
}