In several places it's advised to design our Cassandra tables according to the queries we are going to perform on them. In this article by DataScale they state this:
The truth is that having many similar tables with similar data is a good thing in Cassandra. Limit the primary key to exactly what you’ll be searching with. If you plan on searching the data with a similar, but different criteria, then make it a separate table. There is no drawback for having the same data stored differently. Duplication of data is your friend in Cassandra.
[...]
If you need to store the same piece of data in 14 different tables, then write it out 14 times. There isn’t a handicap against multiple writes.
I have understood this, and now my question is: provided that I have an existing table, say
CREATE TABLE invoices (
id_invoice int PRIMARY KEY,
year int,
id_client int,
type_invoice text
)
But I want to query by year and type instead, so I'd like to have something like
CREATE TABLE invoices_yr (
id_invoice int,
year int,
id_client int,
type_invoice text,
PRIMARY KEY (type_invoice, year)
)
With id_invoice
as the partition key and year
as the clustering key, what's the preferred way to copy the data from one table to another to perform optimized queries later on?
My Cassandra version:
user@cqlsh> show version;
[cqlsh 5.0.1 | Cassandra 3.5.0 | CQL spec 3.4.0 | Native protocol v4]
You can use cqlsh COPY command :
To copy your invoices data into csv file use :
COPY invoices(id_invoice, year, id_client, type_invoice) TO 'invoices.csv';
And Copy back from csv file to table in your case invoices_yr use :
COPY invoices_yr(id_invoice, year, id_client, type_invoice) FROM 'invoices.csv';
If you have huge data you can use sstable writer to write and sstableloader to load data faster. http://www.datastax.com/dev/blog/using-the-cassandra-bulk-loader-updated