突然接到一個任務，需要用java使用Extract API 2.0實現抽取資料庫的數並生成.hyper檔案。沒辦法，只能一邊看文件一邊寫個demo先試試看能不能行得通。
文件：https://onlinehelp.tableau.com/current/api/extract_api/en-us/Extract/extract_api.htm
Extract API 2.0安裝包下載：https://onlinehelp.tableau.com/current/api/extract_api/en-us/Extract/extract_api_installing.htm#downloading
需要注意的是java使用Extract API 2.0需要把下載的Extract API 2.0包裡的dll檔案放到jdk的bin資料夾裡，並把相關jar包匯入到專案當中去。
由於是測試demo，所需我隨便用了一個mysql的資料庫，看是否能把資料抽取到.hyper檔案裡去。
下面是程式碼:

package com.app.dataController;

import java.sql.DriverManager;
import java.sql.ResultSet;
import java.sql.Statement;
import java.util.HashMap;

import com.mysql.jdbc.Connection;
import com.tableausoftware.TableauException;
import com.tableausoftware.common.Collation;
import com.tableausoftware.common.Type;
import com.tableausoftware.hyperextract.Extract;
import com.tableausoftware.hyperextract.ExtractAPI;
import com.tableausoftware.hyperextract.Row;
import com.tableausoftware.hyperextract.Table;
import com.tableausoftware.hyperextract.TableDefinition;


public class ConnectSource {
	public static ResultSet consource() {
		try {
		      Class.forName("com.mysql.jdbc.Driver");     //載入MYSQL JDBC驅動程式   
		     System.out.println("Success loading Mysql Driver!");
		    }
		    catch (Exception e) {
		      System.out.print("Error loading Mysql Driver!");
		      e.printStackTrace();
		    }
		    try {
		      java.sql.Connection connect = DriverManager.getConnection(
		          "jdbc:mysql://localhost:3306/talend","root","123456");
		           //連線URL為   jdbc:mysql//伺服器地址/資料庫名  ，後面的2個引數分別是登陸使用者名稱和密碼

		      System.out.println("Success connect Mysql server!");
		      Statement stmt = connect.createStatement();
		      ResultSet rs = stmt.executeQuery("select * from user");
		      return rs;
		    }
		    catch (Exception e) {
		      System.out.print("get data error!");
		      e.printStackTrace();
		    }
			return null;
	}
	public static void main(String args[]) {
		HashMap<String, String> options = new HashMap<>();
    	options.put("filename", "C:\\Users\\Silence\\Desktop\\Silence.hyper");
    	options.put("build", "1");
    	 if ( options.containsKey( "build" ) ) {
             try {
                 //  Initialize the Tableau Extract API
                 ExtractAPI.initialize();
                 Extract extract = createOrOpenExtract( options.get( "filename" ), true ,true);
                 populateExtract( extract, options.containsKey( "spatial" ) );

                 //  Flush the Extract to Disk
                 extract.close();

                 // Close the Tableau Extract API
                 ExtractAPI.cleanup();
             }catch ( TableauException e ) {
                 System.err.println( "A fatal error occurred while opening or closing the Extract API:" );
                 System.err.println( e.getMessage() );
                 System.err.println( "Printing stack trace now:" );
                 e.printStackTrace( System.err );
                 System.err.println( "Exiting now." );
                 System.exit( -1 );
             }
             catch ( Throwable t ) {
                 System.err.println( "An unknown error occured while opening or closing the Extract API:" );
                 System.err.println( "Printing stack trace now:" );
                 t.printStackTrace( System.err );
                 System.err.println( "Exiting now." );
                 System.exit( -1 );
             }
    	 }
		 
	  }
	private static Extract createOrOpenExtract(String filename,boolean useSpatial,boolean createMultipleTables) {
		Extract user = null;
        Table table = null;
        try {
            //  Create Extract Object
            //  (NOTE: TabExtractCreate() opens an existing extract with the given
            //   filename if one exists or creates a new extract with the given filename
            //   if one does not)
            user = new Extract( filename );

            //  Define Table Schema (If we are creating a new extract)
            //  (NOTE: in Tableau Data Engine, all tables must be named "Extract")
            if ( !user.hasTable( "Extract" ) ) {
                TableDefinition schema = new TableDefinition();
                schema.setDefaultCollation( Collation.EN_GB );
                schema.addColumn( "ID",Type.INTEGER );
                schema.addColumn( "Name",Type.CHAR_STRING );
                schema.addColumn( "CountryCode",Type.CHAR_STRING );
                schema.addColumn( "District",Type.CHAR_STRING );
                schema.addColumn( "Population",Type.CHAR_STRING );
                table = user.addTable( "Extract", schema );
                if ( table == null ) {
                    System.err.println( "A fatal error occured while creating the table" );
                    System.err.println( "Exiting now." );
                    System.exit( -1 );
                }
            }
        }
        catch ( TableauException e ) {
            System.err.println( "A fatal error occurred while creating the extract:" );
            System.err.println( e.getMessage() );
            System.err.println( "Printing stack trace now:" );
            e.printStackTrace( System.err );
            System.err.println( "Exiting now." );
            System.exit( -1 );
        }
        catch ( Throwable t ) {
            System.err.println( "An unknown error occured while creating the extract" );
            System.err.println( "Printing stack trace now:" );
            t.printStackTrace( System.err );
            System.err.println( "Exiting now." );
            System.exit( -1 );
        }
		return user;
	}
	
	 private static void populateExtract(Extract user,boolean useSpatial) {
	     try {
	            //  Get Schema
	            Table table = user.openTable( "Extract" );
	            TableDefinition tableDef = table.getTableDefinition();
                ResultSet rs = consource();
	            //  Insert Data
	            Row row = new Row( tableDef );
	            while (rs.next()) {
	            	row.setInteger(0, rs.getInt("ID"));                         //  ID
		            row.setCharString( 1, rs.getString("Name"));                //  Name
		            row.setCharString( 2, rs.getString("CountryCode"));         //  CountryCode
		            row.setCharString( 3, rs.getString("District"));            //  District
		            row.setCharString( 4, rs.getString("Population"));          //  Population
		            table.insert( row );
	            }
	            
	        }
	        catch ( TableauException e ) {
	            System.err.println( "A fatal error occurred while populating the extract:" );
	            System.err.println( e.getMessage() );
	            System.err.println( "Printing stack trace now:" );
	            e.printStackTrace( System.err );
	            System.err.println( "Exiting now." );
	            System.exit( -1 );
	            }
	        catch ( Throwable t ) {
	            System.err.println( "An unknown error occured while populating the extract" );
	            System.err.println( "Printing stack trace now:" );
	            t.printStackTrace( System.err );
	            System.err.println( "Exiting now." );
	            System.exit( -1 );
	        }
		 
	 }
	 
}

 

環境配置好之後可以直接執行main方法即可生成.hyper檔案。
生成的檔案用Tableau開啟效果：

接下來就該開始用java連線RedShift庫，把億級的資料通過多執行緒的方式生成.hyper檔案啦。