klogg VS q

I'd love to see a tool that lets you modify large files efficiently.

I had to replace line 4 of a 200 GB SQL dump, it took a substantial amount of compute time to perform a find / replace with sed and it also required having over double the disk space since sed creates a temp file before it writes out the new file.

Using a hex editor could have worked but it seemed too risky because data integrity was really important.

There's also some other scenarios where maybe you have a massive file and the tool that's using it (such as a SQL import) throws an error on line 1,025,421. Trying to find what the contents of that line is on the command line could be time consuming if you need to read in the whole file. For read operations I know there's a few graphical tools like https://github.com/variar/klogg that efficiently let you scan, search and jump to points in a file quickly but I haven't found a good one on the command line.

reminds me a bit of klogg https://github.com/variar/klogg which is more for log files and based off glogg which went dead. it has nice filtering and highlighting type stuff. It's great for live views of log files.

glogg / klogg

For anybody who goes through this hell, I highly recommend [Klogg](https://github.com/variar/klogg).

For example, the file star2002-full.csv from https://sdm.lbl.gov/fastbit/data/samples.html is a 1.99GB file and it takes less than 10 seconds to load in Notepad+. It's almost instant in https://github.com/variar/klogg.

CSV utilities (still haven't pick a favorite one...): https://github.com/harelba/q https://github.com/BurntSushi/xsv https://github.com/wireservice/csvkit https://github.com/johnkerl/miller

I think they're talking about https://github.com/harelba/q, which is not very fast.

Apparently, there were many who thought the same thing; Tools to execute SQL against CSV were trdsql, q, csvq, TextQL. They were highly functional, hoewver, had many options and no input completion. I found it just a little difficult to use.

Hi, author of q here.

Regarding the error you got, q currently does not autodetect headers, so you'd need to add -H as a flag in order to use the "country" column name. You're absolutely correct on failing-fast here - It's a bug which i'll fix.

In general regarding speed - q supports automatic caching of the CSV files (through the "-C readwrite" flag). Once it's activated, it will write the data into another file (with a .qsql extension), and will use it automatically in further queries in order to speed things considerably.

Effectively, the .qsql files are regular sqlite3 files (with some metadata), and q can be used to query them directly (or any regular sqlite3 file), including the ability to seamlessly join between multiple sqlite3 files.

http://harelba.github.io/q/#auto-caching-examples