With CQL data modeling, everything is called a "row". But really in CQL, a
row is just a logical concept. So if you think of "wide partition" instead
of "wide row" (partition is what is determined by the has index of the
partition key), it will help the understanding a bit: one wide-partition
may contain multiple logical CQL rows - each CQL row just represents one
actual storage column of the partition.
Time-series data is usually a good fit for "wide-partition" data modeling,
but please remember that don't go too crazy with it.
On Tue, Oct 18, 2016 at 11:23 AM, DuyHai Doan <doanduy...@gmail.com> wrote:
> // user table: skinny partition
> CREATE TABLE user (
> user_id uuid,
> firstname text,
> lastname text,
> PRIMARY KEY ((user_id))
> // sensor_data table: wide partition
> CREATE TABLE sensor_data (
> sensor_id uuid,
> date timestamp,
> value double,
> PRIMARY KEY ((sensor_id), date)
> On Tue, Oct 18, 2016 at 5:07 PM, S Ahmed <sahmed1...@gmail.com> wrote:
>> Can someone clarify how you would model a "wide" row cassandra table?
>> From what I understand, a wide row table is where you keep appending
>> columns to a given row.
>> The other way to model a table would be the "regular" style where each
>> row contains data so you would during a SELECT you would want multiple rows
>> as oppose to a wide row where you would get a single row, but a subset of
>> Can someone show a simple data model that compares both styles?