Simple, fast SQL queries for flat files

Question

Does anyone know of any tools to provide simple, fast queries of flat files using a SQL-like declarative query language? I'd rather not pay the overhead of loading the file into a DB since the input data is typically thrown out almost immediately after the query is run.

Consider the data file, "animals.txt":

dog 15
cat 20
dog 10
cat 30
dog 5
cat 40

Suppose I want to extract the highest value for each unique animal. I would like to write something like:

cat animals.txt | foo "select $1, max(convert($2 using decimal)) group by $1"

I can get nearly the same result using sort:

cat animals.txt | sort -t " " -k1,1 -k2,2nr

And I can always drop into awk from there, but this all feels a bit awkward (couldn't resist) when a SQL-like language would seem to solve the problem so cleanly.

I've considered writing a wrapper for SQLite that would automatically create a table based on the input data, and I've looked into using Hive in single-processor mode, but I can't help but feel this problem has been solved before. Am I missing something? Is this functionality already implemented by another standard tool?

Halp!

Answer 1

I wrote TxtSushi mostly to do SQL selects on flat files. Here is the command chain for your example (all of these commands are from TxtSushi):

tabtocsv animals.txt | namecolumns - | tssql -table animals - \
'select col1, max(as_int(col2)) from animals group by col1'

namecolumns is only required because animals.txt doesn't have a header row. You can get a quick sense of what is possible by looking through the example scripts. There are also links to similar tools on the bottom of the main page.