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It doesn't work that way.  Splunk does not notify the user when their account is created.  It's up to the admin (you) to do that.
The simple calculation is daily ingestion times days times compression ratio (15%), but you must also include multipliers such as replication and datamodel acceleration.
@bowesmana Actually there is a lookup From which I want to extract such kind of pattern.  yesterday I performed so many hit and trial and finally the below one is working as expected. | input loo... See more...
@bowesmana Actually there is a lookup From which I want to extract such kind of pattern.  yesterday I performed so many hit and trial and finally the below one is working as expected. | input lookup dsa.csv | eval parts = split(Description, ".") | eval part1 = mvindex(parts, 0) | eval part2 = mvindex(parts, 1) | eval part3 = mvindex(parts, 2) | eval modified_part2= if(len(part2) == 1, "0" . part2, part2) | eval modified_part3 = if(len(part3) == 1, "0" . part3, part3) | eval modified_description = part1 . "." . modified_part2 . "." . modified_part3 | table Description, modified_description
This issue just happened to me this morning.. it was after I performed the data mapping. I was able to fix the issue without clearing my bookmarking etc by going to setup->review app configuration->u... See more...
This issue just happened to me this morning.. it was after I performed the data mapping. I was able to fix the issue without clearing my bookmarking etc by going to setup->review app configuration->update content->force update.
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Hi,  I have a single search that produces the following table where fieldA and fieldB are arbitrary strings that may be duplicate. This is an exact representation of each event where each event... See more...
Hi,  I have a single search that produces the following table where fieldA and fieldB are arbitrary strings that may be duplicate. This is an exact representation of each event where each event may have a key "fieldA" or a key "fieldB" but not both but they always have an ID and Timestamp Timestamp ID fieldA fieldB 11115 1   "z" 11245 1 "a"   11378 1 "b"   11768 1   "d" 11879 1   "d" 12550 2 "c"   13580 2   "e" 15703 2   "f" 18690 3   "g" and I need help to transform the data as follows. ID fieldA fieldB 1 "b" "d" 1 "b" "d" 2 "c" "e" 2 "c" "f" 3   "g" Thanks to suggestion below, I have tried `stats latest(fieldA) list(fieldB)` but I would prefer to not have any multivalued fields For every distinct value for "fieldA", the latest record with that value would be kept and any records with that ID occuring before that record would be discard. There is no requirement to have 2 searches. Hope that makes it more clear and easier.
You're probably going to need streamstats - here's an example that demonstrates 5 printers with randomised printing, error and spooling statuses and it then uses streamstats to find each occurrence o... See more...
You're probably going to need streamstats - here's an example that demonstrates 5 printers with randomised printing, error and spooling statuses and it then uses streamstats to find each occurrence of printer_error and then counts the occurrences of spooling after the error - it handles multiple occurences of error followed by spooling | makeresults count=1000 | streamstats c | eval _time=now() - (c * 60) | sort _time | eval printer="Printer ".(random() % 5), r=random() % 100, status=case(r<3, "printing,error", r<90, "printing", r<100, "spooling") | fields - r c | search status IN ("printing,error","spooling") ``` Up to the above is just creating dummy data then removing all the printing events so just error and spooling are left ``` ``` Create an occurrence group for each failure ``` | streamstats count(eval(status="printing,error")) as occurrence by printer ``` Ignore the first as it's not relevant here ``` | where occurrence>0 ``` Now count spooling events by failure occurrence and save start/end times ``` | stats min(_time) as printer_error max(_time) as last_spooling count(eval(status="spooling")) as spooling by occurrence printer | fieldformat last_spooling=strftime(last_spooling, "%F %T") | fieldformat printer_error=strftime(printer_error, "%F %T") | sort printer printer_error Hopefully this will give you something to start with
I want to know how much CPU is utilized in our environment along with the trendline @ITWhisperer 
How are you getting your current results - what's your existing SPL?
Have you tried setting TIME_FORMAT in props.conf, e.g. TIME_FORMAT = %s%9Q I suspect you won't get nanoseconds, but you should get microseconds, for example this can get microseconds | makeresults... See more...
Have you tried setting TIME_FORMAT in props.conf, e.g. TIME_FORMAT = %s%9Q I suspect you won't get nanoseconds, but you should get microseconds, for example this can get microseconds | makeresults | eval tf="1707613171105412540" | eval t=strptime(tf, "%s%9Q")
That's fine, but it still doesn't say which servers go in the left panel and which go in the right - how do you decide that logic - anyway, my previous post gives you an example to work with, I hope ... See more...
That's fine, but it still doesn't say which servers go in the left panel and which go in the right - how do you decide that logic - anyway, my previous post gives you an example to work with, I hope you can give that a go and see if it can get you where you're trying to get to.
So I have a schedule search running on DS to summery index which pulls all the info from two DS. Index=summery source=sc. which has the serveclass, forwarder, deplyment server, deployementappname inf... See more...
So I have a schedule search running on DS to summery index which pulls all the info from two DS. Index=summery source=sc. which has the serveclass, forwarder, deplyment server, deployementappname info.   
Yes, I realised as soon as I posted, so did the isnotnull test
The problem with this is that you will get the same count for all time periods whether or not the node was "present" in that time period. The original (second) search uses dc(node) which will only co... See more...
The problem with this is that you will get the same count for all time periods whether or not the node was "present" in that time period. The original (second) search uses dc(node) which will only count the unique instances of node present in each time period.
It is not clear what your events look like but assuming each event has an ERROR_MESSAGE field and you want to count by that message and work out the percentage of the total this represents, you could... See more...
It is not clear what your events look like but assuming each event has an ERROR_MESSAGE field and you want to count by that message and work out the percentage of the total this represents, you could do something like this | stats count by ERROR_MESSAGE | eventstats sum(count) as total | eval count=100*count/total
There's always a way to get where you want to go with Splunk, The issue you have is that timechart with a split by does not end up with a field called node anymore, as the value of node is now the c... See more...
There's always a way to get where you want to go with Splunk, The issue you have is that timechart with a split by does not end up with a field called node anymore, as the value of node is now the column name. You could use stats by time and other mangling of data, but you'd have to handle missing buckets of time in the average, so a simple solution is to effectively count the columns like this   | timechart avg(stat1) by node | eval _nodes=0 | foreach * [ eval _nodes=_nodes + if(isnotnull('<<FIELD>>'), 1, 0) ] | rename _nodes as nodes   Note the underscore in front of the field name - this prevents Splunk from including this in the * matching for foreach. It will create one more column called nodes with the count of nodes.
Try something like this | timechart span=1h avg(stat1) by node | untable _time node avg | appendpipe [| stats count as avg by _time | eval node="Nodes"] | xyseries _time node avg
You haven't explained a fundamental part of the problem - how do you know which servers go in to US and which servers go into UK (or EAST and WEST as in your example). You need to know how you can t... See more...
You haven't explained a fundamental part of the problem - how do you know which servers go in to US and which servers go into UK (or EAST and WEST as in your example). You need to know how you can tell if server 1 belongs to panel 1 or panel 2. Then you simply need to have a base search that splits up the selected servers according to their region, e.g. | makeresults | eval servers=split($server|s$, ",") | eval region=<<DEFINE YOUR LOGIC HERE TO CREATE REGION BASED ON HOST>>> | stats values(server) as server by region | eval server=mvjoin(server, ",") | transpose 0 header_field=region and then you have a <done> clause where you set the tokens for each panel accordingly <done> <set token="region_1">$result.region_1$</set> <set token="region_2">$result.region_2$</set> </done> and you then use the region_1 and 2 tokens in your panels instead of $server$
Colours are assigned to series i.e. all bars from the same series are in the same colour. This is because of the way they are drawn in the chart viz i.e. they are drawn as a single shape for the whol... See more...
Colours are assigned to series i.e. all bars from the same series are in the same colour. This is because of the way they are drawn in the chart viz i.e. they are drawn as a single shape for the whole series, not individual bars. If you want them to have different colours, they need to be different series. Think of the table of data, all data points in the same column of the table will have the same colour in the chart.
Not sure if this is feasible. Basically I would like a chart that shows the average of a statistic for different nodes and distinct count of different nodes. so the 2 searches would be something like... See more...
Not sure if this is feasible. Basically I would like a chart that shows the average of a statistic for different nodes and distinct count of different nodes. so the 2 searches would be something like: 1. index=xxx sourcetype=yyy |timechart avg(stat1) by node 2. index=xxx sourcetype=yyy|timechart dc(node) Both searches would showup on the same timechart panel for the same period with the same time span. Sorry if this is unclear, happy to clarify. I tried eventstats, append, appendcols, and join, but they do not seem to work for this. Could be I'm misusing them though.