infi.clickhouse_orm/README.md

56 lines
1.8 KiB
Markdown
Raw Permalink Normal View History

2017-04-28 19:03:34 +03:00
Introduction
============
This project is simple ORM for working with the [ClickHouse database](https://clickhouse.yandex/).
It allows you to define model classes whose instances can be written to the database and read from it.
Let's jump right in with a simple example of monitoring CPU usage. First we need to define the model class,
connect to the database and create a table for the model:
```python
2020-05-28 19:18:10 +03:00
from infi.clickhouse_orm import Database, Model, DateTimeField, UInt16Field, Float32Field, Memory, F
2017-04-28 19:03:34 +03:00
class CPUStats(Model):
timestamp = DateTimeField()
cpu_id = UInt16Field()
cpu_percent = Float32Field()
engine = Memory()
db = Database('demo')
db.create_table(CPUStats)
```
Now we can collect usage statistics per CPU, and write them to the database:
```python
import psutil, time, datetime
psutil.cpu_percent(percpu=True) # first sample should be discarded
while True:
time.sleep(1)
stats = psutil.cpu_percent(percpu=True)
timestamp = datetime.datetime.now()
db.insert([
CPUStats(timestamp=timestamp, cpu_id=cpu_id, cpu_percent=cpu_percent)
for cpu_id, cpu_percent in enumerate(stats)
])
```
Querying the table is easy, using either the query builder or raw SQL:
```python
# Calculate what percentage of the time CPU 1 was over 95% busy
2020-05-28 19:18:10 +03:00
queryset = CPUStats.objects_in(db)
total = queryset.filter(CPUStats.cpu_id == 1).count()
busy = queryset.filter(CPUStats.cpu_id == 1, CPUStats.cpu_percent > 95).count()
print('CPU 1 was busy {:.2f}% of the time'.format(busy * 100.0 / total))
2017-04-28 19:03:34 +03:00
# Calculate the average usage per CPU
2020-05-28 19:18:10 +03:00
for row in queryset.aggregate(CPUStats.cpu_id, average=F.avg(CPUStats.cpu_percent)):
print('CPU {row.cpu_id}: {row.average:.2f}%'.format(row=row))
2017-04-28 19:03:34 +03:00
```
To learn more please visit the [documentation](docs/toc.md).