Alright, so I spent some time today trying out something I’ve been calling the ‘Silva Simon’ method in my head. It’s not really an official thing, just my name for a little process I wanted to test out.
Basically, I had this bunch of raw data sitting around. Think logs, but messier. Just lines and lines of text dumped from one of our old systems. I needed to make some sense of it, but didn’t want to spin up a whole complex database thing just for a quick look. So, I thought, let’s try a two-step approach: structure it simply first (that’s the ‘Silva’ part for me), then run a quick check or analysis (the ‘Simon’ part).
So, first step, the ‘Silva’ structuring. I opened up the main data file. It was pretty big, maybe a couple of gigs. I decided to just use simple scripting, nothing fancy. Fired up my text editor and started writing a small script. The idea was to read the file line by line and just pull out maybe three key pieces of information I thought might be useful later. Let’s say, a timestamp, an action code, and a user identifier.
Getting Hands Dirty
Writing the script took a bit longer than I thought. Had to figure out the exact position or pattern for each piece of data in those messy lines. Used some basic string splitting and checking. Tested it on the first hundred lines or so. Seemed to work, more or less. Some lines were junk, so I added a simple check to just skip those if they didn’t look right.
Then I ran the script on the whole file. Man, that took a while. Just watched the cursor blink. My machine’s fan kicked in pretty hard. Probably not the most efficient way, reading line by line like that on a big file, but hey, it was simple. Eventually, it finished and spat out a new file, much smaller, with just the structured bits I wanted, one structured record per line.
On to ‘Simon’
Okay, ‘Silva’ part done. Now for ‘Simon’. This was supposed to be the quick analysis. I wanted to answer a simple question: which action codes appeared most often?
So, another small script. This one was easier. It just read the structured file created by the ‘Silva’ script. I used a basic dictionary or hash map to count the occurrences of each action code. Read a line, grab the action code, increment its count in the map. Super straightforward.
This ‘Simon’ script ran really fast, obviously, because the input file was much smaller and cleaner now. In a few seconds, I had the counts for all the action codes.
What Came Out of It
- I got a rough idea of the most common actions in that messy log data.
- The ‘Silva’ part, structuring the data first, definitely made the ‘Simon’ analysis part trivial.
- Doing the ‘Silva’ part with my simple script was slow for the big file. Need a better way if I do this often or on bigger data.
- Skipping bad lines meant I might have missed some stuff, but for a quick look, it felt acceptable.
So, yeah. That was my ‘Silva Simon’ practice for today. It wasn’t revolutionary, just a practical way to break down the problem. Structure first, then analyze. Worked okay for a one-off check. Definitely learned that processing big raw files line-by-line in a simple script isn’t always the best idea if you’re short on time. But hey, I got the answer I needed without installing complicated tools, so I’ll call it a win for today.
