Added note on performance
ci/woodpecker/push/woodpecker Pipeline was successful Details

main
parent c16b9cfb4d
commit 9f7b3605f4

@ -41,6 +41,75 @@ shape: (3, 2)
## Performance
`dr` is implemented in Rust with the goal of achieving the highest possible performance. Take for instance a simple read, groupby, and aggregate operation with ~30MB of data:
```bash
$ time cat data/walmart_train.csv | ./target/release/dr sql "select Dept, avg("Weekly_Sales") from this group by Dept" | ./target/release/dr print
shape: (81, 2)
┌──────┬──────────────┐
│ Dept ┆ Weekly_Sales │
│ --- ┆ --- │
│ i64 ┆ f64 │
╞══════╪══════════════╡
│ 30 ┆ 4118.197208 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 16 ┆ 14245.63827 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 56 ┆ 3833.706211 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 24 ┆ 6353.604562 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ ... ┆ ... │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 31 ┆ 2339.440287 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 59 ┆ 694.463564 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 27 ┆ 1583.437727 │
├╌╌╌╌╌╌┼╌╌╌╌╌╌╌╌╌╌╌╌╌╌┤
│ 77 ┆ 328.9618 │
└──────┴──────────────┘
real 0m0.089s
user 0m0.116s
sys 0m0.036s
```
Let's compare that with the followint Python script that leverages Pandas to read the data, and compute the aggregation:
```python
#!/usr/bin/env python3
import sys
import pandas as pd
df = pd.read_csv(sys.stdin)
print(df.groupby("Dept", sort=False, as_index=False).Weekly_Sales.mean())
```
```bash
$ time cat data/walmart_train.csv | ./python/group.py
Dept Weekly_Sales
0 1 19213.485088
1 2 43607.020113
2 3 11793.698516
3 4 25974.630238
4 5 21365.583515
.. ... ...
76 99 415.487065
77 39 11.123750
78 50 2658.897010
79 43 1.193333
80 65 45441.706224
[81 rows x 2 columns]
real 0m0.717s
user 0m0.627s
sys 0m0.282s
```
Note that there's roughly a 6x speedup. This considering that this operation in particular is heavily optimized in Pandas and most of the run time is spent in parsing and reading from stdin.
## Built standing on the shoulders of giants

Loading…
Cancel
Save