compiler error in Talend open studio for DI

[Anonymous]

Hello All,

My requirement is to load data from excel to sql server table.

Im suppose to validate my data in tmap to check for null values:

here are the my validations sample :

1. Integer (source and target) integer type. -> (row1.XXAPID == null)? null:row1.XXAPID 

2. for Date type .-> row1.INVOICE_DATE.equals("null")?null:TalendDate.parseDate("MM-dd-yyyy HH:mm:ss",row1.INVOICE_DATE) and checked with TalendDate.formateDate also.

3. string to string type-> (row1.LINE_TYPE_LOOKUP_CODE.equals("null")? null :row1.LINE_TYPE_LOOKUP_CODE 

4. float to float type --> (row1.DIST_ITEM_AMOUNT ==null) ? null : row1.DIST_ITEM_AMOUNT.floatValue() 

 I'm facing the following  error while running my job

Can any one please help me to resolve this.

It's very emergency.

[Anonymous]

I would like to use something like below code

(row1.GL_DATE!=null && row1.GL_DATE.equals(TalendDate.formatDate("M-DD-yyyy")) && row1.GL_Date.equals(TalendDate.formatDate("MM-dd-yyyy"))?TalendDate.parseDate("EEE MMM dd HH:mm:ss 'IST' yyyy",row1.GL_DATE):null 

Is this possible?

using this format "EEE MMM dd HH: mm: ss 'IST' yyyy" this date issues got solved "Mon Nov 04 00:00:00 IST 2013"

then what is the possibilities there to solve the issues for all date formats in the same column?

[Anonymous]

I would suggest using a routine to parse the dates in that case.

Take a look at the below thread in StackOverflow,

http://stackoverflow.com/questions/4024544/how-to-parse-dates-in-multiple-formats-using-simpledatefo...

[Anonymous]

Is this is the only option?

can't we validate via writing condition?

[Anonymous]

I can't really think of anything else. Moreover using a routine here would be a safer and easier solution compared to anything else.

[Anonymous]

I think the pattern "M-d-YYYY" should do the job.

[Anonymous]

Sorry, read partially.

No you cannot, because one of the parse will fail with an exception and not witha a condition.

You need a routine that check the possible format or better try to understand which one use (maybe through regexp).

I suggest if possible to normalize the date format with a single format, if not will be a nightmare with some performance impact, if the data become huge.