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mvexpand multiple multi-value fields?


I have a query that extracts useful info from a storage system report.

rex "quota list --verbose (?<fs>[A-Z0-9_]+) " | rex max_match=1000 "ViVol: (?<vivol>(?!user)[A-Za-z0-9]+)\nUsage\s+:\s+(?<usage>[0-9. A-Za-z]+)\n\s*Limit\s+:\s+(?<limit>[0-9A-Z. ]+)" | table fs, vivol, usage, limit

There is a single line at the start of the report with the filesystem which I extract as the "fs" field. Then there are several volume descriptions containing separate lines for the volume, usage and limit.

This query produces a single-value field for "fs" then three multi-value fields "vivol", "usage" and "limit". e.g.

   fs                       vivol                 usage                    limit
   FIRST_FS                 VOL_ABC               100                      300
                            VOL_XYZ               320                      800
                            VOL_123               50                       150

When I export this to Excel (using CSV) the multi-value fields are all within a single cell. I want them on separate rows. If I use mvexpand I get the unexpected behaviour that it will properly expand one field but leave the others unexpanded. If I expand all three fields they lose correlation so I get rows that are mixed-up.

   FIRST_FS                 VOL_123              320                       300

How do I turn my three multi-value fields into tuples? I want to keep them together so the first row in "vivol" matches the first rows in "usage" and "limit". Bear in mind there are many "fs" events (about 100 of them).

Tags (2)

Ultra Champion
| makeresults 
| eval x="another_single_value_field" 
| eval f1=split("a1,a2,a3",",") 
| eval f2=split("b1,b2,b3",",") 
| eval f3=split("c1,c2,c3",",") 
| eval f4=split("d1,d2,d3",",") 

`comment(" this is solution multiple fields mvexpand ")`
`comment(" create counter ")`
| eval _counter=mvrange(0,mvcount(f1)) 
`comment(" prepare to batch ")`
| stats list(*) as * by _counter 
`comment(" batch all  fields except _counter ")`
| foreach * 
    [ eval <<FIELD>>=if(mvcount(<<FIELD>>)=1,<<FIELD>>,mvindex(<<FIELD>>,_counter))]

Mvexpand_memory_limits FREE

0 Karma


Here is another answer to this question:


Please upvote, if it helps.


I downvoted this post because .

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Separate the data into lines (events):

| rex max_match=0 "(?<line>[^\)]+\)\n\N+)" | mvexpand line | table line

Next, do your extractions:

| rex field=line "quota list --verbose (?<fs>[A-Z0-9_]+) " | rex field=line max_match=1000 "ViVol: (?<vivol>(?!user)[A-Za-z0-9]+)\nUsage\s+:\s+(?<usage>[0-9. A-Za-z]+)\n\s*Limit\s+:\s+(?<limit>[0-9A-Z. ]+)" | table fs, vivol, usage, limit

Use the SPL command filldown:

| filldown fs

to get:

    fs                       vivol                 usage                    limit
FIRST_FS                 VOL_ABC               100                      300
FIRST_FS                 VOL_XYZ               320                      800
FIRST_FS                 VOL_123               50                       150

then take it from there.

0 Karma

New Member

Updated regex a bit to select the values as per the example:

| rex field=line "quota list --verbose (?[A-Z0-9_]+) "
| rex field=line max_match=1000 "ViVol: (?(?!user)[A-Za-z0-9_]+)\nUsage\s+:\s+(?[0-9.]+)[A-Za-z\s\n]+Limit\s+:\s+(?[0-9]+)[A-Za-z\s+()]+"
| table fs, vivol, usage, limit

0 Karma

Splunk Employee
Splunk Employee

Use mvzip, makemv and then reset the fields based on index.

First, mvzip the multi-values into a new field:

| eval reading=mvzip(vivol, usage)    // create multi-value field for reading
| eval reading=mvzip(reading, limit)  // add the third field

At this point you'll have a multi-value field called reading. Here's an example of a field value (a list of four items):

"VOL_ABC,100,300",  "VOL_XYZ,320,800", "VOL_123, 50,150", "VOL_FOO, 80,120"

Expand the field and restore the values:

| mvexpand reading                    // separate multi-value into into separate events
| makemv reading delim=","            // convert the reading into a multi-value
| eval vivol=mvindex(reading, 0)      // set vivol to the first value of reading
| eval usage=mvindex(reading, 1)      // set usage to the second value of reading
| eval limit=mvindex(reading, -1)     // set limit to the last value of reading


Here is another solution to this problem:


0 Karma


Thanks , It helped me so much 🙂 .

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Assuming that all the mv fields MUST have the same number of items...

| eval myFan=mvrange(0,mvcount(vivol))
| mvexpand myFan
| eval vivol=mvindex(vivol,myFan)
| eval usage=mvindex(usage,myFan)
| eval limit=mvindex(limit,myFan)


Thanks a lot!

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Path Finder

Hi DalJeanis,
your solution is ingenious.

Thanks so much!


0 Karma


Seriously this is a great help

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Splunk Employee
Splunk Employee

Thanks @sk314. To be fair, this question was left unanswered for four years and 35 hours. Some improvements have been made to the docs since this answer, but this example is still better, IMO.

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This is so great. I am writing this comment (and upvoting) AFTER searching for this answer and using it for the third time. Quite ungrateful. 😕

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this worked for some JSON data I had where I needed to preserve relationships among elements of an array

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Path Finder

Very helpful, thanks. I ended up with a completed search that did exactly what I wanted using the above stuff.

source="/Znfs200g/Mainframe/splunk/volSpaceReport.txt" | rex max_match=0 "(?:PRIVATE\s+)(?\d+)\s+(?\d+)" | eval my_zip=mvzip(vol,vol_pct) | mvexpand my_zip | makemv my_zip delim="," | eval vol=mvindex(my_zip,0) | eval vol_pct=mvindex(my_zip,1) | eventstats sum(vol) as vol_sum | eval weighted_vol_pct=(vol_pct*vol/vol_sum) | stats sum(weighted_vol_pct) as Average_HardDisk_Utilization

0 Karma


I ran into the same issue with two multi-valued fields, and arrived at a different solution - make a copy of the field to preserve the order for an mvfind, then use mvexpand, look up the value in the added field, lookup each field that was NOT expanded, then drop the added field. It would look something like:

...| eval vivolIndex=vivol | mvexpand vivol | eval idx=mvfind(vivolIndex,vivol) | eval usage=mvindex(usage,idx) | eval limit=mvindex(limit,idx) | fields - vivolIndex ...

This solution worked better for me as I was using a stats list(x) list(y) and needed to keep the values correlated.


Just ran into a similar issue, glad I found your solution. Thanks!

0 Karma

Splunk Employee
Splunk Employee

I just had the same issue.

Create a single field with all the eventual fields you want, so you have a single MV, then use mvexpand to create the multiple entries, then do another parse on the (now single-) value to extract the three fields.

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