Input file parsing to insert into DB

Question

Hi,
I have a sample input file as follows:
++++++++++ 2009-09-28 15:10:58 ++++++++++++++
++++++++ DAILY SCORES +++++++++++++++++
2009-09-28 15:10:58|AAAA|0
2009-09-28 15:10:58|BBBBB|0
2009-09-28 15:10:58|ACCCC|0
++++++++ MONTHLY SCORES +++++++++++++++++
2009-09-28 15:10:58|AAAA|30
2009-09-28 15:10:58|BBBBB|50
2009-09-28 15:10:58|ACCCC|60
I should ignore first line and then look for "DAILY SCORES" or "MONTHLY SCORES"string. This determines which MySql table has to be used.
Then read the following lines delimited by pipe and insert them into MySql table
Table schema is as follows:
dateandtimestamp | program | score
Please suggest the best approach to do this.
Thanks,
Mona.

Answer 1

Thanks. I got it working till the point where I am able to split each line into separate tokens.
There is a separating line in the file +++++++++++ DAILY SCORES +++++++++++++++
The string in this line can differ based on what kind of data follows. Ex: Daily Scores, Monthly Scores etc...
How should I ignore all +++ symbols and search for string?
Here is my code so far:
public static void main(String[] args) {          
          try {
               File file = new File(FILENAME);
               BufferedReader reader = new BufferedReader(new InputStreamReader(new FileInputStream(file)));
               String line = reader.readLine();
               if(line.startsWith("++++"))
                                            // Ignore +++ symbols and search for string                    
               while(line != null){     
                    dbRecordBuilder(line);
                    line = reader.readLine();                    
               reader.close();               
          } catch (IOException e) {               
               e.printStackTrace();
        public static void dbRecordBuilder(String line) throws IOException
          String[] recordData = line.split("\t");
          for(int i=0;i<recordData.length;i++)
          System.out.println(recordData);     
Edited by: IDForums on Sep 29, 2009 1:26 PM