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From Maciej Miklas <mac.mik...@googlemail.com>
Subject Data Model Design for Login Servie
Date Thu, 17 Nov 2011 21:08:24 GMT
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.tester@xyz.de {
          id: 1122
          gender: MALE
          birthdate: 1987.11.09
          name: Alfred Tester
          pwd: e72c504dc16c8fcd2fe8c74bb492affa
        },
        alfred@aad.de {
          id: 1122
          gender: MALE
          birthdate: 1987.11.09
          name: Alfred Tester
          pwd: e72c504dc16c8fcd2fe8c74bb492affa
        },
        alf@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
        manfred@xyz.de {
          id: 1133
          gender: MALE
          birthdate: 1997.02.01
          name: Manfredus Maximus
          pwd: e44c504ff16c8fcd2fe8c74bb492adda
        },
        roberrto@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.tester@xyz.de:"1122;MALE;1987.11.09;
                                 Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa",

        alfred@aad.de@xyz.de:"1122;MALE;1987.11.09;
                                 Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa",

        alf@dd.de@xyz.de:"1122;MALE;1987.11.09;
                                 Alfred
Tester;e72c504dc16c8fcd2fe8c74bb492affa"
      },

    m {
        manfred@xyz.de:"1133;MALE;1997.02.01;
                  Manfredus Maximus;e44c504ff16c8fcd2fe8c74bb492adda"
      },

    r {
        roberrto@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

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