These are some very basic and unscientific benchmarks of various commands
provided by `xsv`. Please see below for more information.
These benchmarks were run with
[worldcitiespop_mil.csv](http://burntsushi.net/stuff/worldcitiespop_mil.csv),
which is a random 1,000,000 row subset of the world city population dataset
from the [Data Science Toolkit](https://github.com/petewarden/dstkdata).
These benchmarks were run on an Intel i7-6900K (8 CPUs, 16 threads) with 64GB
of memory.
```
count 0.11 seconds 413.76 MB/sec
flatten 4.54 seconds 10.02 MB/sec
flatten_condensed 4.45 seconds 10.22 MB/sec
frequency 1.82 seconds 25.00 MB/sec
index 0.12 seconds 379.28 MB/sec
sample_10 0.18 seconds 252.85 MB/sec
sample_1000 0.18 seconds 252.85 MB/sec
sample_100000 0.29 seconds 156.94 MB/sec
search 0.27 seconds 168.56 MB/sec
select 0.14 seconds 325.09 MB/sec
search 0.13 seconds 350.10 MB/sec
select 0.13 seconds 350.10 MB/sec
sort 2.18 seconds 20.87 MB/sec
slice_one_middle 0.08 seconds 568.92 MB/sec
slice_one_middle_index 0.01 seconds 4551.36 MB/sec
stats 1.09 seconds 41.75 MB/sec
stats_index 0.15 seconds 303.42 MB/sec
stats_everything 1.94 seconds 23.46 MB/sec
stats_everything_index 0.93 seconds 48.93 MB/sec
```
### Details
The purpose of these benchmarks is to provide a rough ballpark estimate of how
fast each command is. My hope is that they can also catch significant
performance regressions.
The `count` command can be viewed as a sort of baseline of the fastest possible
command that parses every record in CSV data.
The benchmarks that end with `_index` are run with indexing enabled.