I have a table with attributes
TotalSales, and I would like to extract the rows which are in the top 50% of total sales. Naively, I would pipe this into
search TotalSales>=median(TotalSales). However, since
search doesn't support the
median function, Splunk returns no events.
I can make this work via the following hack:
| eventstats median(TotalSales) as MTS | where TotalSales>=MTS | fields - MTS
I'm worried about the efficiency of this hack. If I omit the
fields - MTS command, then the output is a table with attribute MTS, with the median value replicated across all rows. If I have only 20 products, then this isn't that big of a deal, but if I have 500,000 products, then this is an enormous amount of redundancy in memory.
My question: what is Splunk doing under the hood? That is,
dc(ProductName)of times, then deleting it once I remove the MTS field?
That is not a hack; it is a valid approach. Here is an alternate approach, which I believe will be slower, not faster:
yoursearchhere | eval MTS = [ yoursearchhere-again | stats median(TotalSales) as query ] | where TotalSales >= MTS
But you can test and see...
That information is not published, and I don't think it is the sort of thing that Splunk will reveal. However, it does seem silly to replicate the number in memory; I would guess that it is optimized.
Thanks, Lisa! That's an interesting workaround. However, it doesn't quite answer my "under the hood" question.
Suppose that we have 500,000 products. I'd like to know whether Splunk is literally storing the median value 500,000 times during the piping (replicated across each product name), or whether the replication happens purely at the end of the pipeline (when the visual table is being generated).