q's purpose is to bring SQL expressive power to the Linux command line and to provide easy access to text as actual data.
q allows the following:
- Performing SQL-like statements directly on tabular text data, auto-caching the data in order to accelerate additional querying on the same file.
- Performing SQL statements directly on multi-file sqlite3 databases, without having to merge them or load them into memory
The following table shows the impact of using caching:
Rows | Columns | File Size | Query time without caching | Query time with caching | Speed Improvement |
---|---|---|---|---|---|
5,000,000 | 100 | 4.8GB | 4 minutes, 47 seconds | 1.92 seconds | x149 |
1,000,000 | 100 | 983MB | 50.9 seconds | 0.461 seconds | x110 |
1,000,000 | 50 | 477MB | 27.1 seconds | 0.272 seconds | x99 |
100,000 | 100 | 99MB | 5.2 seconds | 0.141 seconds | x36 |
100,000 | 50 | 48MB | 2.7 seconds | 0.105 seconds | x25 |
Notice that for the current version, caching is not enabled by default, since the caches take disk space. Use -C readwrite
or -C read
to enable it for a query, or add caching_mode
to .qrc
to set a new default.
q's web site is https://harelba.github.io/q/ or https://q.textasdata.wiki It contains everything you need to download and use q immediately.
q treats ordinary files as database tables, and supports all SQL constructs, such as WHERE
, GROUP BY
, JOIN
s, etc. It supports automatic column name and type detection, and provides full support for multiple character encodings.
Here are some example commands to get the idea:
$ q "SELECT COUNT(*) FROM ./clicks_file.csv WHERE c3 > 32.3"
$ ps -ef | q -H "SELECT UID, COUNT(*) cnt FROM - GROUP BY UID ORDER BY cnt DESC LIMIT 3"
$ q "select count(*) from some_db.sqlite3:::albums a left join another_db.sqlite3:::tracks t on (a.album_id = t.album_id)"
Detailed examples are in here
New Major Version 3.1.6
is out with a lot of significant additions.
Instructions for all OSs are here.
The previous version 2.0.19
Can still be downloaded from here
Any feedback/suggestions/complaints regarding this tool would be much appreciated. Contributions are most welcome as well, of course.
Linkedin: Harel Ben Attia
Twitter @harelba
Email [email protected]
q on twitter: #qtextasdata
Patreon: harelba - All the money received is donated to the Center for the Prevention and Treatment of Domestic Violence in my hometown - Ramla, Israel.