![]() ![]() Could you please have a look at my query and let me know where I'm going wrong and what I could do to avoid using a join command: However, I'm not sure it's working correctly. Based on this join, I want to return results from both searches only in instances where ITEM values match. I'm using the join command to join to searches based on a common field called ITEM. The subsearch is *not* hitting any limits on execution time or number of results the overall data set is fairly small. I am sure this is something simple that I have overlooked, but I don't see it! I've even looked at the Search Job Inspector, but nothing shows up there either. For example, the second search gave an average of 45453.56 while the first search gave an average of 42823.32638888889. I am using the standard access_combined sourcetype for this example, so clientip is the IP address that is connecting to the Apache server, status is the HTTP status code, and bytes is the number of bytes in the HTTP request.īut the searches give slightly different results. (My real search is slightly different, but this illustrates the problem perfectly.) Successful traffic is defined as status=400. ![]() The concept of both searches is the same: Identify IPs that have had HTTP errors in the previous week, and summarize the number of bytes of "successful" traffic, average and median during that timeframe. | stats sum(bytes) as bytes count(eval(check="Bad")) as Bad by clientip Index=web sourcetype=access_combined action=purchase **Option 2: using an eval to replace the subsearch** | stats avg(bytes) as avg_bytes, median(bytes) as median_bytes ![]() Index=web sourcetype=access_combined status=400 The result shows the mean and variance of the values of the field named bytes in rows organized by the http status values of the events.Here are two searches, which I think are logically equivalent, yet they return different results in Splunk. We continue using the same fields as shown in the previous examples. ![]() In the below example, we use the functions mean() & var() to achieve this. Statistically focused values like the mean and variance of fields is also calculated in a similar manner as given above by using appropriate functions with the stats command. We continue the previous example but instead of average, we now use the max(), min() and range function together in the stats command so that we can see how the range has been calculated by taking the difference between the values of max and min columns. The stats command can be used to display the range of the values of a numeric field by using the range function. In the below example, we find the average byte size of the files grouped by the various http status code linked to the events associated with those files. But with a by clause, it will give multiple rows depending on how the field is grouped by the additional new field. Without a BY clause, it will give a single record which shows the average value of the field for all the events. This function takes the field name as input. We can find the average value of a numeric field by using the avg() function. If a BY clause is used, one row is returned for each distinct value specified in the BY clause.īelow we see the examples on some frequently used stats command. If the stats command is used without a BY clause, only one row is returned, which is the aggregation over the entire incoming result set. The stats command works on the search results as a whole and returns only the fields that you specify.Įach time you invoke the stats command, you can use one or more functions. The stats command is used to calculate summary statistics on the results of a search or the events retrieved from an index. ![]()
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