If you want to reduce the number of columns, you could pack all the data
for a product into one column, as in
composite column name-> product_id_1:12.44:1.00:3.00
On 04/12/2012 03:03 PM, Philip Shon wrote:
I am currently working on a data model where the purpose is to look up
multiple products for given days of the year. Right now, that model
involves the usage of a super column family. e.g.
"2012-04-12": {
"product_id_1": {
price: 12.44,
tax: 1.00,
fees: 3.00,
},
"product_id_2": {
price: 50.00,
tax: 4.00,
fees: 10.00
}
}
I should note that for a given day/key, we are expecting in the range
of 2 million to 4 million products (subcolumns).
With this model, I am able to retrieve any of the products for a given
day using hector's MultigetSuperSliceQuery.
I am looking into changing this model to use Composite column names.
How would I go about modeling this? My initial thought is to migrate
the above model into something more like the following.
"2012-04-12": {
"product_id_1:price": 12.44,
"product_id_1:tax": 1.00,
"product_id_1:fees": 3.00,
"product_id_2:price": 50.00,
"product_id_2:tax": 4.00,
"product_id_2:fees": 10.00,
}
The one thing that stands out to me with this approach is the number
of additonal columns that will be created for a single key. Will the
increase in columns, create new issues I will need to deal with?
Are there any other thoughts about if I should actually move forward
(or not) with migration this super column family to the model with the
component column names?
Thanks,
Phil
