Skip to main content

SCALA : Scala code to Call Data from Oracle Data Source and Convert them to CSV files

 Hi All,

Below is the code which is used to run the query from Oracle Database and load them to CSV files using Scala.


object Main {

 

  def main(args: Array[String]): Unit = {

 

    /* Local connection details*/

    val dbUser = "dbusernameo"

    val dbPassword = "dbpassword"

    val dbURL = "jdbc:oracle:thin:@11.2.4.80:1234:databasename"

 

    val configQuery =

      """

      SELECT First_Name,Last_Name,Middle_Name,Student_Number

      ,Grade_Level,Enroll_Status,Gender

      from Students Where rownum<2

        """

    val conConfig = OracleConnect.connJdbc(dbUser, dbPassword, dbURL)

 

    val statement = conConfig.createStatement()

    statement.setFetchSize(1000)

    val resultSet: java.sql.ResultSet = statement.executeQuery(configQuery)

 

    /* Read all the variable from Orcale table*/

    while (resultSet.next) {

     // var oracleURL = resultSet.getString("First_Name")

     // var oracleUser = resultSet.getString("Last_Name")

      //var oraclePassword = resultSet.getString("Middle_Name")

      //var oracleOutPutFilePath = resultSet.getString("Student_Number")

      //var oracleOutPutFileDateFormat = resultSet.getString("Student_Number")

     // var oracleQueryFilePath = resultSet.getString("Grade_Level")

 

      //val Enroll_Status = resultSet.getString("Enroll_Status")

      //val Gender = resultSet.getString("Gender")

 

      oracleURL = "jdbc:oracle:thin:@11.2.4.80:1234:databasename "

      oracleUser = " dbusernameo "

      oraclePassword = "dbpassword"

      oracleOutPutFilePath = "C:\\Scala\\student.csv"

      oracleOutPutFileDateFormat = "yyyyMMdd"

      oracleQueryFilePath = "C:\\Scala\\Config\\sampleQuery.txt"

 

      /* Call CSV export function*/

      CSVExport.exportCSVFile(oracleUser, oraclePassword, oracleURL, oracleOutPutFilePath, oracleOutPutFileDateFormat, oracleQueryFilePath)

    }

 

  }

 

}


Comments

  1. your valuable information and time. Please keep updating.
    Msbi Developer Course
    Best Msbi Online Training

    ReplyDelete
  2. Thank you for sharing wonderful information with us to get some idea about that content.
    Msbi Online Course
    Msbi Online Training

    ReplyDelete

Post a Comment

Popular posts from this blog

BIG Data, Hadoop – Chapter 2 - Data Life Cycle

Data Life Cycle The data life cycle is pictorial defined as show below:     As we see, in our current system, we capture/ Extract our data, then we store it and later we process for reporting and analytics. But in case of big data, the problem lies in storing and then processing it faster. Hence Hadoop takes this portion, where it stores the data in effective format (Hadoop distributed File System) and also process using its engine (Map Reduce Engine). Since Map Reduce engine or Hadoop engine need data on HDFS format to process, We have favorable tools available in market to do this operation. As an example, Scoop is a tool which converts RDBMS to HDFS. Likewise we have SAP BOD to convert sap system data to HDFS.

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" returned message "The Microsoft Access database engine cannot open or write to the file ''. It is already opened exclusively by another user, or you need permission to view and write its data.". Msg 7303, Level 16, State 1, Line 1 Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)".

OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)" returned message "The Microsoft Access database engine cannot open or write to the file ''. It is already opened exclusively by another user, or you need permission to view and write its data.". Msg 7303, Level 16, State 1, Line 1 Cannot initialize the data source object of OLE DB provider "Microsoft.ACE.OLEDB.12.0" for linked server "(null)". If you get this error while Loading Data From Excel to SQL Server, then, close the Excel sheet opened and try to run queries again.

BIG Data, Hadoop – Chapter 1 - Understanding Big Data & Hadoop

Understanding Big Data We all in recent time, came across the word ‘Big Data’. So the question is what exactly is Big Data? How much TB or GB or data is called a Big Data? Well, there is no standard size definition for Big Data. If current system when not able to handle the data, then, we call such data as Big Data. (Big Data is just a terminology used in IT) As an example, if I take a text file of 50 GB, Processing a text file of 50 GB size on our Laptop or computer is not a huge task but if we take a smart phone, processing 10 GB of data is huge task. That means, for mobile phone, that 50 GB of data is Big Data. Understanding Hadoop Our current systems such as ETL tools, reporting tools, programming environment all have capability of handling few petabyte of Data. And the growth of data annually is shown below in chart And also the growth of unstructured, Semi structured data are increasingly every day. So there is a need of more adv...