I have read here that for a table like:
CREATE TABLE user (
username text,
password text,
email text,
company text,
PRIMARY KEY (username)
);
We can create a table like:
CREATE TABLE user_by_company (
company text,
username text,
email text,
PRIMARY KEY (company)
);
In order to support query by the company. But what about primary key uniqueness for the second table?
Modify your table's PRIMARY KEY definition and add username
as a clustering key:
CREATE TABLE user_by_company (
company text,
username text,
email text,
PRIMARY KEY (company,username)
);
That will enforce uniqueness, as well as return all usernames for a particular company. Additionally, your result set will be sorted in ascending order by username
.
data will be partitioned by the company name over nodes. What if there is a lot of users from one company and less from other one. Data will be partition'ed in a non balanced way
That's the balance that you have to figure out on your own. PRIMARY KEY definition in Cassandra is a give-and-take between data distribution and query flexibility. And unless the cardinality of company
is very low (like single digits), you shouldn't have to worry about creating hot spots in your cluster.
Also, if one particular company gets too big, you can use a modeling technique known as "bucketing." If I was going to "bucket" your user_by_company
table, I would first add a company_bucket
column, and it as an additional (composite) partitioning key:
CREATE TABLE user_by_company (
company text,
company_bucket text,
username text,
email text,
PRIMARY KEY ((company,company_bucket),username)
);
As for what to put into that bucket, it's up to you. Maybe that particular company has East and West locations, so something like this might work:
INSERT INTO user_by_company (company,company_bucket,username,email)
VALUES ('Acme','West','Jayne','[email protected]');
The drawback here, is that you would then have to provide company_bucket
whenever querying that table. But it is a solution that could help you if a company should get too big.
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