Extract IDOC numbers

Hello,
need to extract IDOCs numbers of a lot of IDOCs which run on a mapping error and
have been stopped in sxmb_moni. Is there a possibility to extract the IDOCs numbers as
as a list? We have XI 3.0.
Thanks
Chris

Hello
@Rajesh: This is the thing I don't want to do. Look into the payload of hundreads of IDOCs is not very funny. But thanks for your answer.
@ Jaishankar and Siddhesh Pathak
IDX5 contains the needed information. Thanks for the hint. Points given.

Similar Messages

How to extract Idocs Numbers from Bulk Purchase orders

Hi Gurus,
I have around 1400 purchase orders.I need to get their Idoc numbers to reprocess in order to generate Sales orders.Is their any process to extract the Idoc numbers of all the purchase orders at a time. Pls suggest on the same.
Thanks in Advance
Ganesh Kumar

Use t.code WE02.
Enter IDOC basic type and date ranges. This will pull the IDOC numbers.
Regards

BADI_BUILD_MESSAGE + IDOC numbers required

Hi,
I am setting up an alert notificatio in solution manager for IDOCs. It is working fine. But the requirement is to extend the functionality and add idoc numbers also in the same mail alert. I found a BADI "BADI_BUILD_MESSAGE" for this purpose.
Please help me to suggest if this is the correct BADI and also where(in which parameter of the badi) will I find the IDOC numbers. I could not find the source of the IDOC numbers as this is running in background system.

Check if note 1609090 can help you.

Logic to update the table with IDOC numbers

Hi all,
I have an issue while I am running my interface. The IDOCs are getting generated and are displaying in WE02 successfully. But in my logic, I have a requirement to update these created IDOCs in a customized database table. This table has the IDOC number as the first key field.
Now the issue is that when a file is placed on the FTP server with the data, the IDOCs get generated with no doubt but the table is not getting updated with these IDOC numbers due to which my other data is also not seen in my table.
Please help with the logic that I need to place to update these IDOC numbers in my table.
Thanks.
Taarikha

Also, this is happening when the file is placed. But when i run it manually through WE19 one by one, it has no problem. When it collectively run thorugh the file in background, this issue is ocuuring. Please help.
Thanks.
Taarikha

Extraction of Numbers from string in oracle

Dear All,
I have a AplhaNumeric field in my source table which holds the string with numbers and caharcters .i need to extract only numbers and to load into the target table which of number type.
can any one suggest me about how to do this?
regards
kumar

Hi ,
I have a table called smitems with column smitmqtyremarks which holds alpha numeric characters .nearly 180 records exists in this table.
i need extract numbers for this field and load into my target tables.
here i am giving sample rows for this field :
smitmqtyremarks
13 قطعة
4 لحاف
31 قطعة
120 قطعة
57 قطعة
110 قطعة
127قطعة
169 قطعة
12 مفرش
10 مفارش
110 قطعة
170 قطعة
20 خرطوشة
28 قطعة
60قطعة
70 قطعة
80 لعبة
70 قطعة
20 قطعة
60 قطعة
50 قطعة
10 رولات
4 رولات
35 دسته
50دستة
7 رول
3 اثواب قماش
خمسة خرطوشة سجائر
50 جاكت حريمى ورجالى
10 رول اقمشة 4 دسته
420 جوارب اطفال
60 خرطوشة سجائر
12 رول
15 خرطوشة
110 علبة
45 قطعة
40 قطعة
44 قطعة
22 قطعة
3 خرطوشة
468 قطعة
38 قطعة
80 رول قماش
2 رول
6 رول اقمشة
13 رول اجنبى الصنع
100 دسته صينى الصنع
18 رولات ملابس
10دسته
90قطعة
33 قطعة
39 قطعة
42 قطعة
300 ايشارب
500 قطعة
19000 ك 0ج
607 قطعة
24 قطعة
45 قطعة
40 اروسه
5 رول اقمشة اجنبية الصنع
75 قطعة
5 قطعة
4 رول
26 قطعة
50قطعة
105 قطعة
650 جرام
65 قطعة
50 خرطوشة
4 خرطوشة
80 قطعة
100 بنطلون
500 قطعة
40 قطعة
42قطعة
1 خرطوشة
14 قطعة
80 قطعة
7 خرطوشة سجائر
230 لمبة
50 قطعة
50قطعة تليفون
14 كرتونة
4 كرتونة احذية
17 كرتونة خزف
22 لحاف
16كرتونة ادوات صحية
8كرتونة
28 كرتونة
2كرتونة
15كرتونة
115 قطعة
6448
1937قطعة
1937 قطعة
2628كجم
6.980طن
9 كرتونة
18 شفاط
صواميل حديد
3كرتونة +20 قطعة
39.480طن ق.غ سيارات
25كرتونة مصنوعات خزفية
50بنطلون
8 كرتونة كلبسات
20كرتونة اكسسوار حريمى
279كرتونة لحوم
38 اطار كاوتش
10كرتونة
4كرتونة
10كيلو
عدد5 ماكينات
41سيارة
سيارة
90 قطعة ملابس
22250كجم
1793كجم
1371كرتونة زجاج
مستندى
252شاشة
5كرتونة
320قطعة
45خرطوشة
98 قطعة
10لفات
25كجم
320كجم
5كراتين
47طرد
50قطعة
117كجم
1200 قطعة ملابس
5كجم
75جهاز
40قطعة
5كراتين
10كجم
250ق
200ق
200 توب
20لفة
30لفة
2دستة
95قطعة
70قطعة
57523طن طلمبات مياه
43732كجم
755كرتونة
10.645طن
1537طرد
11751كجم
مكبس
77426.80متر
2600قطعة
339طن
15120كجم
مختلفة
267طرد
1200كجم
189عبوة
499كرتونة
10000كجم
960طرد
15.770كجم
111قطعة
174طرد
22000كجم
473000علبة
6720كجم
145خرطوشة
2500طن
3660كجم
27824كجم
8682كجم
14000كجم
6400كجم
133كرتونة
2738كجم
the characters are in arabic here.
hope it clears my issue.
please suggest me the right query for this to get only numbers
thanks
kumar

Idoc numbers for a certain output in Sales Orders

I have more than hundred Sales Order
One EDI output was triggered (with a unique partner type) from each of these Sales Orders.
How to find idoc numbers for all these Sales Order for this particular output?
I tried WE09 giving Segment and field with value....two issues with this. first is it is not working for me...not records found.
Secondly It take one value at a time. I can't do this for every Sales Order
Is there any database table or something else to find these idocs?
Thanks a lot!

Hi,
if this special partner type is the partner type of the IDoc receiver, then you can search for relevant IDocs in transaction WE02.
If you need a partner type out of the sales order data, then it is stored in table EDID4 "IDoc Data Records".

Extracting IDOC data from DB

I've got a requirement to list the material numbers of some failed IDOCs, but am struggling to get to the data.
I've tried doing a SQL trace, but this only gets me as far as being able to identify the IDOC numbers through EDIDC, and I need to be able to retrieve the segment data as well.
Does anyone know of a FM that would do the job?

Hi Chris,
After getting the IDOC numbers from EDIDC then you can use FM : IDOC_READ_COMPLETELY to read the IDOC segment.
[pls see in table parameter : INT_EDIDD-SDATA]
Regards,
Hendy

Capture Idoc numbers for outbound INVOIC02

Hi,
We have a requirement where we need to capture the idoc numbers before it is dispatched.
IDOCS are populated by FM IDOC_OUTPUT_INVOIC using process code SD09 for custom output type(EDI processing).
Our requirement is to capture these idoc numbers into a custom table which will be used for further custom processing. The user exits in the above FM are good for just for segment population.
What is the best approach to capture these idocs? Is there a user exit to capture these idocs?
Thanks,
Pratik

sorry wrong forum

Extracting Serial numbers to bw

Hi,
I need to extract serial numbers associated with deliveries. not sure how to go about it.
Please guide me do this.
Thank You,
GRao

Hi,
Look at DB connect functionality!
http://help.sap.com/saphelp_erp2004/helpdata/en/a1/89786c3df35c4ea930a994e884bb4c/frameset.htm
https://www.sdn.sap.com/irj/servlet/prt/portal/prtroot/com.sap.km.cm.docs/library/biw/s-u/transferring%20data%20with%20db%20connect.pdf
Hope it helps!
Bye,
Ravi

Regex expression for extracting whole numbers?

I would like to ask, how can I modify the code below, so it only returns int values inside the specific string, >100 which is a whole number.
The code below returns the following strings = 2525, 130, 129s, MH350s, from which '2525' is incorrect.
The value '2525' is extracted from '97.2525', which is a decimal number and should only extract value greater than 100, which is whole integer, not decimal numbers. Is their a way to
extract whole numbers using the regex expression.
public class Program
public static void Main()
// An example collection of your input
var input = "ASW+90s, N+20s, 97.2525, M45s, 130.5, +129s, 48E. MH350s";
var re1 = new Regex(@"^(\d+)[sS]$");
foreach(var match in Regex.Matches(input,@"\w*[1-9]\d{2,}\w*"))
// Output each match
Console.WriteLine(match);
any advice further, would be very much appreciated. Thank you

You've already asked this question in the forums and several people provided the RE that you need to do it right. Your RE is for integers, not fixed point values.
I replied to your original post and gave you the exact RE that parses the strings like you wanted. If you use that code then you'll get the results you want. The only piece missing now is that you are breaking up a single string into substrings for
parsing. To do that use
String.Split to split the string at the commas. The result is an array of values without the commas. Using the previous code you end up with this:
var inputs = input.Split(',');
var numbersGreaterThan100 = from i in ExtractNumbers(inputs) where i > 100 select I;
Michael Taylor
http://blogs.msmvps.com/p3net

Function module or BAPI for getting all the Idoc numbers of a sales order

Hi Folks,
Is there any function module or BAPI exists for getting all the Idoc numbers which are generated for a Sales order.
Thanks in advance.
Regards,
Sarath.....

Hi Sarath,
try this function module...
BAPI_IDOCAPPL_DISPLAY
Regards,
Prabhudas

Unable to extract page numbers using FIRST_BOOK_PAGE

Hi
We have to extract page numbers in views.
For this we have
Added FIRST_BOOK_PAGE in key template.
Linked key template to study views
Enabled CRF page tracking
Data entry using DCI book
But we are still not able to extract this variable. View generation fails with following error.
ORA-00904: "RDCM"."FIRST_BOOK_PAGE": invalid identifier
Is there any other step that we have to follow to extract this variable.
Note: FIRST_BOOK_PAGE column is being populated in Received_DCIs table.
Please give you inputs.
Thanks
Navi

I was quicky able to replicate your problem by just doing what I would normally do to add a column to a key template. I am not aware of any other steps.
The default extract macro for FIRST_BOOK_PAGE provides the alias "RDCM". This alias appears in the error message as well. This is an apparent error as this column is not available in rxc.received_dcms. It has to be added either as a custom macro or as a hard code revision to the rdcms_view referenced by each of the defined views for a study. And if it is added "under the sheets", the alias would need to be RDCI or at least something other than RDCM since this is already in use for all of the other stuff coming from received_dcms.
This is the explanation for the error message, ie. even though you've added it to the key template, it is an invalid reference because it is looking at the wrong table.
-JK

How to extract vendors numbers which are included in a particular payment program variant or from a payment identification?

How to extract vendors numbers which are included in a particular payment program variant or from a payment identification?

Hi ,
That's not a Problem as well.
Go to F110 nd then see as below screen shot . This will give you everything that has included in payment .
you have an option of diplay which will give same list but vendor included for paid . You have option to get paymnet summary and all other . Please check them out and let me know if you need more help

Parsing and extraction of numbers from select lines in a string

hey guys, i've been running into some issues with my code and i was wondering if you could help me out. currently what i've done is take an xml document returned from a server, put it into a string, and then select specific lines from that string, from which i will extract numbers. here's the string
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:census1="tag:govshare.info,2005:rdf/census/details/100pct/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:census="http://www.rdfabout.com/rdf/schema/census/">
    <rdf:Description rdf:about="http://www.rdfabout.com/rdf/usgov/geo/census/zcta/90041/censustables">
        <census1:totalPopulation>
            <rdf:Description>
                <dc:title>SEX BY AGE (P012001)</dc:title>
                <census1:female>
                    <rdf:Description>
                        <census1:_40To44Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1131</census1:_40To44Years>
                        <census1:_62To64Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">327</census1:_62To64Years>
                        <census1:_10To14Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">875</census1:_10To14Years>
                        <census1:under5Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">864</census1:under5Years>
                        <census1:_18And19Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">592</census1:_18And19Years>
                        <census1:_67To69Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">307</census1:_67To69Years>
                        <census1:_55To59Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">689</census1:_55To59Years>
                        <census1:_22To24Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">600</census1:_22To24Years>
                        <census1:_75To79Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">450</census1:_75To79Years>
                        <census1:_80To84Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">331</census1:_80To84Years>
                        <census1:_25To29Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">932</census1:_25To29Years>
                        <census1:_15To17Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">534</census1:_15To17Years>
                        <census1:_30To34Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1035</census1:_30To34Years>
                        <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">14540</rdf:value>
                        <census1:_50To54Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">970</census1:_50To54Years>
                        <census1:_45To49Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1038</census1:_45To49Years>
                        <census1:_5To9Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">949</census1:_5To9Years>
                        <census1:_60And61Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">261</census1:_60And61Years>
                        <census1:_21Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">264</census1:_21Years>
                        <census1:_70To74Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">482</census1:_70To74Years>
                        <census1:_65And66Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">208</census1:_65And66Years>
                        <census1:_35To39Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1026</census1:_35To39Years>
                        <census1:_20Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">285</census1:_20Years>
                        <census1:_85YearsAndOver rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">390</census1:_85YearsAndOver>
                    </rdf:Description>
                </census1:female>
                <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">27864</rdf:value>
                <census1:male>
                    <rdf:Description>
                        <census1:_40To44Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1077</census1:_40To44Years>
                        <census1:_62To64Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">270</census1:_62To64Years>
                        <census1:_10To14Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">872</census1:_10To14Years>
                        <census1:under5Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">862</census1:under5Years>
                        <census1:_18And19Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">511</census1:_18And19Years>
                        <census1:_67To69Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">258</census1:_67To69Years>
                        <census1:_55To59Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">647</census1:_55To59Years>
                        <census1:_22To24Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">569</census1:_22To24Years>
                        <census1:_75To79Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">252</census1:_75To79Years>
                        <census1:_80To84Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">183</census1:_80To84Years>
                        <census1:_25To29Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">969</census1:_25To29Years>
                        <census1:_15To17Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">525</census1:_15To17Years>
                        <census1:_30To34Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1024</census1:_30To34Years>
                        <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">13324</rdf:value>
                        <census1:_50To54Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">822</census1:_50To54Years>
                        <census1:_45To49Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">987</census1:_45To49Years>
                        <census1:_5To9Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">974</census1:_5To9Years>
                        <census1:_60And61Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">215</census1:_60And61Years>
                        <census1:_21Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">287</census1:_21Years>
                        <census1:_70To74Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">320</census1:_70To74Years>
                        <census1:_65And66Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">155</census1:_65And66Years>
                        <census1:_35To39Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1140</census1:_35To39Years>
                        <census1:_20Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">257</census1:_20Years>
                        <census1:_85YearsAndOver rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">148</census1:_85YearsAndOver>
                    </rdf:Description>
                </census1:male>
            </rdf:Description>
        </census1:totalPopulation>
    </rdf:Description>
</rdf:RDF>now my first attempt at pulling this off worked just fine, but only for the female demographics, since the tags for female and male are identical (only the numbers/data is different) and my parser would stop after reaching the first round of tags specified.
here's part of my code for that section, located in the main (response is the xml string returned from server):
while ((temp = in.readLine()) != null)
             response += temp + "\n";
        temp = null;
        in.close ();
int left = response.indexOf("<census1:under5Years rdf:datatype=\"http://www.w3.org/2001/XMLSchema#integer\">");
          int right = response.indexOf("</census1:under5Years>");
               // pull out the text inside the parens
               String parsed = response.substring(left+77, right);
               double parseddub = Double.parseDouble(parsed);
                    //divide the group Under5Years into Under12Mo and 1to4Yr
                    double Group1Adub = parseddub*.25;//25% for Under12Mo
                    Group1Adub = Math.ceil(Group1Adub);
                    int Group1A =(int)Group1Adub;
                    double Group1Bdub = parseddub*.75;//75% for 1to4Yr
                    Group1Bdub = Math.ceil(Group1Bdub);
                    int Group1B =(int)Group1Bdub;
//..need to basically duplicate this for 3 other age groups
int Group1 = Group1A;
System.out.println("Server response:\n" + "Female");
          System.out.println("Under 12 Months:    " + Group1);now basically, everything works great for the female data, but i would like to somehow loop this or selectively parse by line and then extract information from those selected lines. any thoughts? i would really appreciate some insight thanks.

lol no offense taken. sorry for the confusion, please disregard my earlier statements... :)
i actually was able to get the thing working, i just didn't quite understand what i was doing at first.
however, i noticed that the regex only handles the first four lines of each group (male and female). i was wondering if there was a way to do it that's non-sequential?
<?xml version="1.0"?>
<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:census1="tag:govshare.info,2005:rdf/census/details/100pct/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:census="http://www.rdfabout.com/rdf/schema/census/">
    <rdf:Description rdf:about="http://www.rdfabout.com/rdf/usgov/geo/census/zcta/90041/censustables">
        <census1:totalPopulation>
            <rdf:Description>
                <dc:title>SEX BY AGE (P012001)</dc:title>
                <census1:female>
                    <rdf:Description>
                        <census1:_40To44Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1131</census1:_40To44Years>
                        <census1:_62To64Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">327</census1:_62To64Years>
                       -<census1:_10To14Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">875</census1:_10To14Years>
                       -<census1:under5Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">864</census1:under5Years>
                        <census1:_18And19Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">592</census1:_18And19Years>
                        <census1:_67To69Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">307</census1:_67To69Years>
                        <census1:_55To59Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">689</census1:_55To59Years>
                        <census1:_22To24Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">600</census1:_22To24Years>
                        <census1:_75To79Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">450</census1:_75To79Years>
                        <census1:_80To84Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">331</census1:_80To84Years>
                        <census1:_25To29Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">932</census1:_25To29Years>
                       -<census1:_15To17Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">534</census1:_15To17Years>
                        <census1:_30To34Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1035</census1:_30To34Years>
                        <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">14540</rdf:value>
                        <census1:_50To54Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">970</census1:_50To54Years>
                        <census1:_45To49Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1038</census1:_45To49Years>
                       -<census1:_5To9Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">949</census1:_5To9Years>
                        <census1:_60And61Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">261</census1:_60And61Years>
                        <census1:_21Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">264</census1:_21Years>
                        <census1:_70To74Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">482</census1:_70To74Years>
                        <census1:_65And66Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">208</census1:_65And66Years>
                        <census1:_35To39Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1026</census1:_35To39Years>
                        <census1:_20Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">285</census1:_20Years>
                        <census1:_85YearsAndOver rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">390</census1:_85YearsAndOver>
                    </rdf:Description>
                </census1:female>
                <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">27864</rdf:value>
                <census1:male>
                    <rdf:Description>
                        <census1:_40To44Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1077</census1:_40To44Years>
                        <census1:_62To64Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">270</census1:_62To64Years>
                       -<census1:_10To14Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">872</census1:_10To14Years>
                       -<census1:under5Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">862</census1:under5Years>
                        <census1:_18And19Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">511</census1:_18And19Years>
                        <census1:_67To69Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">258</census1:_67To69Years>
                        <census1:_55To59Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">647</census1:_55To59Years>
                        <census1:_22To24Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">569</census1:_22To24Years>
                        <census1:_75To79Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">252</census1:_75To79Years>
                        <census1:_80To84Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">183</census1:_80To84Years>
                        <census1:_25To29Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">969</census1:_25To29Years>
                       -<census1:_15To17Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">525</census1:_15To17Years>
                        <census1:_30To34Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1024</census1:_30To34Years>
                        <rdf:value rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">13324</rdf:value>
                        <census1:_50To54Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">822</census1:_50To54Years>
                        <census1:_45To49Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">987</census1:_45To49Years>
                       -<census1:_5To9Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">974</census1:_5To9Years>
                        <census1:_60And61Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">215</census1:_60And61Years>
                        <census1:_21Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">287</census1:_21Years>
                        <census1:_70To74Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">320</census1:_70To74Years>
                        <census1:_65And66Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">155</census1:_65And66Years>
                        <census1:_35To39Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">1140</census1:_35To39Years>
                        <census1:_20Years rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">257</census1:_20Years>
                        <census1:_85YearsAndOver rdf:datatype="http://www.w3.org/2001/XMLSchema#integer">148</census1:_85YearsAndOver>
                    </rdf:Description>
                </census1:male>
            </rdf:Description>
        </census1:totalPopulation>
    </rdf:Description>
</rdf:RDF> using the regular expression, i can parse the string, but what i really need is to only parse the 8 lines designated, and they are not in sequential order, which makes it somewhat problematic.
the format of the output i want to get should be as in the following example (female: under5, 5to9, 10to14, 15to17):
[864, 949, 875, 534]
same format for male of course. i'm just not sure how to edit the regex so that it can select only the lines i'm concerned with...? thanks so much i really appreciate this.

XI and IDOC numbers

Hi,
we have the following scenario:
SAP(IDOC)->XI(IDOC)->Third Party(IDOC)
XI receives the SAP-IDOCs and creates automatically a new XI-IDOC number and sends the XI-IDOC to the third party system.
If a problem is coming up, SAP user and Third Party user have problems to find the correct IDOC, because the numbers are different (SAP IDOC number vs. XI IDOC number).
Is there a way to prevent XI from creating a new IDOC number? XI should use the SAP-IDOC number that is coming within the IDOC.
Thanks for any help,
Christian

Hi Christian,
You cannot switch off the creation of an IDOC when XI sends it to a receiving system. This is for XI to store the IDOC uniquely with an IDOC number in the XI system.
To cross reference the XI IDOC number to the Original Idoc number of the sending system, the table entries in the table IDXRCVPOR can be used. The field IDOCNUMBER in the table has the XI idoc number & the field SNDLAD has the idoc number of the sending system.
hope this information helps...
Thanks,
Renjith.

Extract IDOC numbers

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