Command Line FTW!

TL;DR Summary : BASH command line to extract the most often repeated line of text from a log file: cat filename.log | sort | uniq -c | sort -nr

I was reading some blog posts by my friend Cori Drew who is in the process of changing into a command line user, when I realized I’ve been doing some very cool log analysis recently which I should blog about. I’ve have two different situations recently in which I was thrust into analyzing log files. The first was a web site which was throwing logging large numbers of exceptions in production which were not happening in lower environments. The second was a performance challenge, attempting to determine which indexes would be best applied to a Mongo database.

In the first challenge, I had a log file composed mostly of .NET stack traces, and I they seemed to be from “all over the place”, no one component being the source of the exceptions. But I suspected that some component was shared in common between these various exceptions, so I realized I wanted to do the following things:

  • Sort the lines of the file, so all the duplicates were next to each other.
  • Get a count of each distinct lines number of repeats.
  • Find the line which repeated the most often.

Now I’ve been in this programming field for a long time now, and it has taught me some very important lessons, the first and most important is that if you’re manipulating long files of text, a DOS prompt is not the place to do it, and neither is a GUI. So I openned my handy-dandy BASH shell which I use for GIT, and other stuff. After a little bit of google’ing, I realized that I had everything I needed:

  • sort - sorts lines of a file
  • uniq -c - counts all the unique lines, and puts the count at the front of each line of the output.
  • sort -nr - sorts, backwards, with numeric rules (hence sorting the numbers put in by uniq)

This worked fantastically well, and quickly isolated to a base class on our security attributes of the MVC application as the true source of the exceptions in the application. When just a week later the second situation occurred, having to analyze the logs of a mongod process for often executed queries, in hopes of finding good candidates for indexing, I returned to my command line friend and after a minor modification had exactly what I was looking for.

What was the minor modification? The use of some sed and grep commands to remove everything other than query output, and then remove info from each line about the connection it was performed on, so that I had a clean list of queries. The final command for the Mongo analysis looked like this:

cat mongo.log | grep "runQuery" | sed 's/ \[conn[0-9]*\]//' | sed 's/[A-Za-z]* [A-Za-z]* [0-9]* [0-9]*:[0-9]*:[0-9]* //' | sort | uniq -c | sort -nr

Simple eh? No? You might want to follow those links on grep and sed then.