I want to have a report with a metrics of sum by count by some column by date in LogAnalytics.
So far I could use -
Perf
| summarize sum(CounterValue) by TimeGenerated, Computer
which gives me below result in screenshot. But I want in a format per day. Something like -
Date,Computer,sum_Count
01-17-2020,ABC,100
01-16-2020,ABC,132
01-17-2020,XYZ,700
01-16-2020,XYZ,800
try using startofday():
Perf
| summarize sum(CounterValue) by startofday(TimeGenerated), Computer
or bin():
Perf
| summarize sum(CounterValue) by bin(TimeGenerated, 1d), Computer
Related
not sure if I articulated my problem well in the title but let me elaborate here. I need to find where IPs have a daily average count from the past 3 days that is at least 150% larger than a daily average count from the past 7 days. I am looking for spikes in activity based on those two averages. With the way I phrased it, that may sound confusing, but let me show you what I have and why I'm having issues calculating the averages.
| index=blah_blah
| earliest=-7d
| bucket _time span=1d
| stats count by ip _time
| sort ip
| trendline sma3(count) as 3_Day_Average
| trendline sma7(count) as 7_Day_Average
| where 3_Day_Average > 7_Day_Average * 1.5
This provides incorrect averages because if an IP doesn't have a count on a particular day, it won't include that day in the statistics table and it won't be calculated into the average. Instead, it will use a different IP's count to fill in. So if one IP doesn't have a count for 2 of the 7 days for example, then it will take 2 counts from the next IP and calculate that into the average for the original IP that was missing 2 days... I'm hoping that all makes sense. I need the days that don't have counts to still show so that they can be calculated into these averages. If this doesn't make sense to you, feel free to ask questions. I appreciate the help
Instead of stats, try timechart. The timechart command will fill in zeros for spans that have no data.
| index=blah_blah earliest=-7d
| timechart span=1d count by ip
| untable _time ip count
| sort ip
| trendline sma3(count) as 3_Day_Average
| trendline sma7(count) as 7_Day_Average
| where 3_Day_Average > 7_Day_Average * 1.5
Trying to SUM up a Group of CELLS by their Dates in Access...so that a report will give 1 of each date....and the TOTAL amount of CELLS that have that date. Followed by the next...
I'm sure it's a combination of things. or something simple but could someone please explain how I would do this?
Thanks
EVV Table
+-------------+--------+
| DateInputed | Claims |
+-------------+--------+
|02/08/2021 | 15 |
|02/08/2021 | 31 |
|03/01/2020 | 21 |
+-------------+--------+
Report Should look like
By Date Report
-------------
02/08/2021 46
03/01/2020 21
--------------
Totals 67
With Distinct obviously being used by the Date portion Query and A SUM being done per Date.... Does this make more sense
Here's what I've thought of trying
Sooo I was Massively over thinking this...and would like to credit #June7 With the win since they were able to point out Grouping and Sorting to me.....GROUPING
So Here's my Answer that worked
I Created a SQL Query
SELECT EVV.DateInputed, Sum(EVV.ClaimNumber) AS Total_Claim, Sum(EVV.[Total Failed Claims]) AS Total_Fail FROM EVV GROUP BY EVV.DateInputed HAVING (((EVV.DateInputed)>= Forms]![Search for EVV Totals]![fromDate] And (EVV.DateInputed)<=[Forms]![Search for EVV Totals]![toDate]));
Then I created a Simple Report based on that and BAMB Instant Answer. So thank you for those of everyone that was helping
2020-12-07 23:57:10,160 INFO [+] Number of fetched Availability to publish to Gcp PubSub topic. [ClassUnitKey=BU-STO-460] [NumberOfMessages=95] , [bsName="BsRunBatch"], [userId="S-OLB-U-ITSEELM"], [userIdRegion="EU"]
As the above splunk log message , How to find the sum of [NumberOfMessages=95] field value in a hourly basis. I have written as below
| timechart span=1h sum(NumberofMessages)
Its not giving the desired result. The below result i got
try this:
| bin _time span=1h | stats sum(NumberofMessages) by _time
timechart can overwrite your span depending on your time window
I have a search string like below:
index=qrp STAGE IN (ORDER_EVENT)
| bucket _time span=1h
| timechart useother=f span=1h sum(TRADES) as "TradeCount" by ODS_SRC_SYSTEM_CODE
| fillnull value=0
And this is currently giving me aggregates of trades for multiple source systems from the stage table Trade event in a tabular format for every hour of the day.
I need to search exactly for the time frame 8am every day, whether the value of sun of trade for all source systems in the table is equal to zero. How to add the condition to check the column value is Zero or not?
Your help is much appreciated.
You can use the where command to test the value of a field.
... | where TradeCount == 0
Hi I have a table like this:
idCustomer | idTime | idStatus
---------------------------------
1 | 20010101 | 2
1 | 20010102 | 2
1 | 20010103 | 3
2 | 20010101 | 1
...
I have now added this table as a factless fact table in my cube with a measure which aggregates the row count for each customer, so that for each day I can see how many customers are at each status and I can drill down to see which customers they are.
This is all well and good but when I roll it up to the month or year level it start summing up the values of each day where instead I want to see the last non empty value.
I'm not sure if this is possible but I can't think of another way of getting this information without creating a fact table with the counts for each status on each day and loosing the ability to drill down.
Can anyone help??
An easy way to get what you want would be to convert your factless fact table to one having a fact: the count. Just add a named calculation to the table object in the data source view. Name the calculation like you want your measure to be named, and use 1 as the expression. Then you can define a measure based on this calculation using the aggregate function "LastNonEmpty", and use this instead of your current count measure.