Grep 2G source tree in 0.23 seconds. A speed up of more than 10 fold.
It uses a search engine before using grep. The search engine is beagle, thus the name beagrep.
For more details, visit my github page (man page included).
Ag (AKA the silver searcher) claims to be very fast, beating ack and GNU grep.
I compared ag and beagrep on my laptop:
| Model | CPU | Memory |
|---|---|---|
| Thinkpad T420 | Intel(R) Core(TM) i5-2520M CPU @ 2.50GHz | 8G |
cd ~/src/android
# One nice thing about ag is that it filters
# VCS and binary files automatically.
time ag readlink .
The first time it took 3 minutes, the second time it took 8 seconds, very impressive! I think if I had learned about it earlier I probably wouldn’t have started working on beagrep in the first place, because I would have thought it is quick enough already.
time beagrep -e readlink
The first time it took 30 seconds, the second time it took 0.42 second.
Another test is done on Linux kernel source code, where ag takes 1m35s/1.8s for cache hot/cold, while beagrep takes 15s/0.25s respectively.
(The claim that it took 0.23 second to grep 2G Android source code is achieved on my Dell Optiplex 960).
- Very fast
- Output format compatibility with grep, so it can be used by, for e.g., Emacs grep-mode directly.
- Match not only file content, file names too, like locate(1).
- You need build the search engine database beforehand (the first time you do this will take a long while, but subsequent updating is reasonably fast)
- Works on whole words only: can not use partial word (
beagrep -e readli) to findreadlink.
Ack’s author Andy Lester has written a nice intro about all kinds of tools for searching source code.
Of particular interest to beagrep is Google’s Code Search tool.
- Push beagrep into Debian distribution.
Thank the Beagle project for making the original engine. And of course, the Apache Lucene project.
Thank LDD’s author for saying “(LDD) is the result of hours of grepping” and getting me hooked to grep forever.
Last but not least, I submitted this README on reddit, and has refined it several times according to the comments there. To those who commented: thanks, I have learned from you!