First we load our extension and configure matplotlib to display graphs inline.
Before using this notebook, be sure to run:
cqlsh -f setup_tutorial.cql
In [ ]:
%load_ext cql
%reload_ext cql
%matplotlib inline
%keyspace tutorial
In [ ]:
%tables
In [ ]:
%desc sensor_data
In [ ]:
%%cql
CREATE TABLE user (
user_id uuid primary key,
name text
);
In [ ]:
%cql insert into user (user_id, name) values (cf76125b-9353-4df1-a208-319885d0b888, 'Jon')
%cql select * from user;
In [ ]:
%cql truncate sensor_data;
%cql INSERT INTO sensor_data (sensor_id, date_created, reading) values (cf76125b-9353-4df1-a208-319885d0b888, now(), 1)
%cql INSERT INTO sensor_data (sensor_id, date_created, reading) values (cf76125b-9353-4df1-a208-319885d0b888, now(), 3)
%cql INSERT INTO sensor_data (sensor_id, date_created, reading) values (cf76125b-9353-4df1-a208-319885d0b888, now(), 10)
%cql select * from sensor_data where sensor_id = cf76125b-9353-4df1-a208-319885d0b888;
In [ ]:
%trace select reading from sensor_data where sensor_id = cf76125b-9353-4df1-a208-319885d0b888;
In [ ]:
%%cql
select *
from
sensor_data
where sensor_id = cf76125b-9353-4df1-a208-319885d0b888;
In [ ]:
%%histogram
select reading
from
sensor_data
where sensor_id = cf76125b-9353-4df1-a208-319885d0b888;
This notebook is available in the repo!