Hallo all,
I need your help to design structure for simple login service. It contains
about 100.000.000 customers and each one can have about 10 different logins
- this results 1.000.000.000 different logins.
Each customer contains following data:
- one to many login names as string, max 20 UTF-8 characters long
- ID as long - one customer has only one ID
- gender
- birth date
- name
- password as MD5
Login process needs to find user by login name.
Data in Cassandra is replicated - this is necessary to obtain all required
login data in single call. Also usually we expect low write traffic and
heavy read traffic - round trips for reading data should be avoided.
Below I've described two possible cassandra data models based on example:
we have two users, first user has two logins and second user has three
logins
A) Skinny rows
- row key contains login name - this is the main search criteria
- login data is replicated - each possible login is stored as single row
which contains all user data - 10 logins for single customer create 10
rows, where each row has different key and the same content
// first 3 rows has different key and the same replicated data
alfred.tes...@xyz.de {
id: 1122
gender: MALE
birthdate: 1987.11.09
name: Alfred Tester
pwd: e72c504dc16c8fcd2fe8c74bb492affa
},
alf...@aad.de {
id: 1122
gender: MALE
birthdate: 1987.11.09
name: Alfred Tester
pwd: e72c504dc16c8fcd2fe8c74bb492affa
},
a...@dd.de {
id: 1122
gender: MALE
birthdate: 1987.11.09
name: Alfred Tester
pwd: e72c504dc16c8fcd2fe8c74bb492affa
},
// two following rows has again the same data for second customer
manf...@xyz.de {
id: 1133
gender: MALE
birthdate: 1997.02.01
name: Manfredus Maximus
pwd: e44c504ff16c8fcd2fe8c74bb492adda
},
rober...@xyz.de {
id: 1133
gender: MALE
birthdate: 1997.02.01
name: Manfredus Maximus
pwd: e44c504ff16c8fcd2fe8c74bb492adda
}
B) Rows grouped by alphabetical prefix
- Number of rows is limited - for example first letter from login name
- Each row contains all logins which benign with row key - row with key 'a'
contains all logins which begin with 'a'
- Data might be unbalanced, but we avoid skinny rows - this might have
positive performance impact (??)
- to avoid super columns each row contains directly columns, where column
name is the user login and column value is corresponding data in kind of
serialized form (I would like to have is human readable)
a {
alfred.tes...@xyz.de:"1122;MALE;1987.11.09;
Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa",
alf...@aad.de@xyz.de:"1122;MALE;1987.11.09;
Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa",
a...@dd.de@xyz.de:"1122;MALE;1987.11.09;
Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa"
},
m {
manf...@xyz.de:"1133;MALE;1997.02.01;
Manfredus Maximus;e44c504ff16c8fcd2fe8c74bb492adda"
},
r {
rober...@xyz.de:"1133;MALE;1997.02.01;
Manfredus Maximus;e44c504ff16c8fcd2fe8c74bb492adda"
}
Which solution is better, especially for better read performance? Do you
have better idea?
Thanks,
Maciej
