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How to create a new field with values in existing field based on the values in other field.

allan_newton
Path Finder

Hi,
I'm new to splunk and seek your help in achieving in a functionality.

My log goes something like this,

time=12/04/2013 12:00:36, login_id=1, head_key_value=124, txn_dur=12.54, txn_status=success
time=12/04/2013 12:02:46, login_id=2, head_key_value=232, txn_dur=6.36, txn_status=success
time=12/04/2013 14:36:11, login_id=3, head_key_value=221, txn_dur=19.23, txn_status=failure

Now I want to display a table with three fields head_key_value_for_1 (values for head_key_value whose login_id=1), head_key_value_for_2 (values for head_key_value whose login_id=2), and head_key_value_for_3 (values for head_key_value whose login_id=3).

Please help me.

Tags (2)
1 Solution

Gilberto_Castil
Splunk Employee
Splunk Employee

Splunk will create fields dynamically using the eval command. You may also pair the eval command with an if condition. Take this for example:

sourcetype="answers-1372957739" | eval head_key_value_for_1=if(login_id=="1",head_key_value,"NULL")

However, that is highly inefficient because you’d have to hard-code each one of the possible values for the login_id into a giant expression.






The solution here is to create the fields dynamically, based on the data in the message. There is a bit magic to make this happen cleanly. Here is the process:

Group the desired data values in head_key_value by the login_id

sourcetype="answers-1372957739" | stats list(head_key_value) AS head_key_value by login_id 

Dynamically create the field that will identify the desired head_key_value with the corresponding login_id:

| eval header="head_key_value_for_".login_id 

Remove the unnecessary data to match the report exactly as described in this question:

| fields - login_id 

Tranform the tabular data, where the new head_key_value_for_{no} header is the column and the associated value are the values for the head_key_value

| eval no_op=" " | xyseries no_op header head_key_value | fields - no_op

All together you will get something like this:

  sourcetype="answers-1372957739"
| stats list(head_key_value) AS head_key_value by login_id 
| eval header="head_key_value_for_".login_id 
| fields - login_id 
| eval no_op=" " 
| xyseries no_op header head_key_value 
| fields - no_op

alt text



I hope this is what you were trying to accomplish.

--gc

View solution in original post

Gilberto_Castil
Splunk Employee
Splunk Employee

Splunk will create fields dynamically using the eval command. You may also pair the eval command with an if condition. Take this for example:

sourcetype="answers-1372957739" | eval head_key_value_for_1=if(login_id=="1",head_key_value,"NULL")

However, that is highly inefficient because you’d have to hard-code each one of the possible values for the login_id into a giant expression.






The solution here is to create the fields dynamically, based on the data in the message. There is a bit magic to make this happen cleanly. Here is the process:

Group the desired data values in head_key_value by the login_id

sourcetype="answers-1372957739" | stats list(head_key_value) AS head_key_value by login_id 

Dynamically create the field that will identify the desired head_key_value with the corresponding login_id:

| eval header="head_key_value_for_".login_id 

Remove the unnecessary data to match the report exactly as described in this question:

| fields - login_id 

Tranform the tabular data, where the new head_key_value_for_{no} header is the column and the associated value are the values for the head_key_value

| eval no_op=" " | xyseries no_op header head_key_value | fields - no_op

All together you will get something like this:

  sourcetype="answers-1372957739"
| stats list(head_key_value) AS head_key_value by login_id 
| eval header="head_key_value_for_".login_id 
| fields - login_id 
| eval no_op=" " 
| xyseries no_op header head_key_value 
| fields - no_op

alt text



I hope this is what you were trying to accomplish.

--gc

View solution in original post

allan_newton
Path Finder

Can't beat this explanation!!
bow!!

Thank you.

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