Database design and normalization

I would like to compare and contrast two options for the design of customer contact information for a relational database.

This is the first option, a “fat” customer table.

create table t_fat_customer (
  customer_id bigint not null primary key,
  customer_name varchar(255) not null,
  customer_phone_1 varchar(255) not null default '',
  customer_phone_2 varchar(255) not null default '',
  customer_tollfree_1 varchar(255) not null default '',
  customer_tollfree_2 varchar(255) not null default '',
  customer_mobile_1 varchar(255) not null default '',
  customer_mobile_2 varchar(255) not null default '',
  customer_record_created_on timestamp default current_timestamp,
  customer_record_updated_on timestamp default current_timestamp on update current_timestamp
);

insert into t_fat_customer (
  customer_id,
  customer_name,
  customer_phone_1,
  customer_phone_2,
  customer_tollfree_1,
  customer_tollfree_2,
  customer_mobile_1,
  customer_mobile_2
)
values (
  1,
  'John Doe',
  '123-456-7890',
  '123-456-7891',
  '800-123-4567',
  '',
  '123-456-7892',
  ''
), (
  2,
  'Jane Doe',
  '123-456-7894',
  '123-456-7895',
  '800-123-4569',
  '',
  '123-456-7896',
  ''
);

This is the second option, a “skinny” and “properly normalized” option. It has lots of skinny tables, which some will claim are the hallmarks of “good design”.

create table t_skinny_customer (
  customer_id bigint not null primary key,
  customer_name varchar(255) not null,
  customer_record_created_on timestamp default current_timestamp,
  customer_record_updated_on timestamp default current_timestamp on update current_timestamp
);

create table t_skinny_customer_phone (
  customer_phone_id bigint not null primary key,
  customer_id bigint not null references t_skinny_customer( customer_id ) on delete cascade,
  phone_number varchar(255) not null,
  phone_type enum( 'phone', 'tollfree', 'mobile' ) not null default 'phone',
  phone_type_order tinyint unsigned not null default 0,
  phone_record_created_on timestamp default current_timestamp,
  phone_record_updated_on timestamp default current_timestamp on update current_timestamp
);

insert into t_skinny_customer (
  customer_id,
  customer_name
)
values (
  1,
  'John Doe'
), (
  2,
  'Jane Doe'
);

insert into t_skinny_customer_phone (
  customer_phone_id,
  customer_id,
  phone_number,
  phone_type,
  phone_type_order
)
values (
  11,
  1,
  '123-456-7890',
  'phone',
  1
), (
  12,
  1,
  '123-456-7891',
  'phone',
  2
), (
  13,
  1,
  '800-123-4567',
  'tollfree',
  1
), (
  14,
  1,
  '123-456-7892',
  'mobile',
  1
), (
  21,
  2,
  '123-456-7894',
  'phone',
  1
), (
  22,
  2,
  '123-456-7895',
  'phone',
  2
), (
  23,
  2,
  '800-123-4569',
  'tollfree',
  1
), (
  24,
  2,
  '123-456-7896',
  'mobile',
  1
);

Here are some stats from the design options:

Fat option Skinny option
Lines of code: 42 85
Tables: 1 2
Columns: 10 11
Records: 2 10

The first option is simpler than the second option by every measure.

I know, you want to create a more general solution. I know, they say a hallmark of good database design and “proper normalization” is lots of skinny tables. I remind you: the first option is simpler than the second option by every measure.

My advice is don’t rush toward general solutions in an effort to solve problems you don’t have.

The UI isn’t coupled to the database design in any way. You could implement any type of UI on top of either database design alternative, such as:

Primary Secondary Operations
Phone:
Tollfree:
Mobile:

Or:

Phone Type Phone Number Operations

(My opinion is that the first UI option above is superior to the second UI option, it’s also exceedingly easy to implement with the “fat” customer table.)

Here are some implementation exercises to compare the difficulty of working with the database options:

  • given a customer ID get the primary tollfree number or the primary phone number if there’s no tollfree number on record
  • for each customer, fix the phone number records so that the secondary contact option is promoted to the primary contact option if there isn’t already a primary option on record, for each phone type (phone, tollfree, mobile).
  • implement user interface option A above
  • implement user interface option B above
  • create a view to present the “fat” customer contact options as a table like in the “skinny” t_skinny_customer_phone table
  • create a view to present the “skinny” customer contact options as a table like in the “fat” t_fat_customer table
  • enforce a business rule which says that not more than two contact options for each phone type should be stored in the database for each customer
  • check for duplicate contact phone numbers and remove them when found
  • put the customer contact information into a spreadsheet and email to marketing by COB

Keyspace on the back of an envelope

One question that always plagues me: should I use 32-bit or 64-bit keys. I can never make a firm decision on this point. But I’ve just done some back of the envelope calculations in thinking about it.

If you issued one identity per second, every second of every day, it would take 136 years to exhaust the keyspace.

If you issued one thousand identities per second, it would take 50 days to exhaust the keyspace.

Things You Should Know About Databases

This one popped up in my feed today: Things You Should Know About Databases. My favourite quote was this one:

The SQL standard defines 4 standard isolation levels these can and should be configured globally (insidious things can happen if we can’t reliably reason about isolation levels).

It’s so important to know what isolation level is applicable to your connection/transaction.

The Database Relational Fuckup

In his book The Database Relational Model on page 25 Date says:

Here I would just comment–here comes the hindsight once again–that if as suggested earlier the database is to be regarded as a (correct!) logical system, it must never be allowed to contain any inconsistencies, at least from the user’s point of view. In other words, “remedying inconsistencies” needs to be done on an individual statement-by-statement basis (not even on a transaction-by-transaction basis). See reference [52] for further elaboration on this point.

Reference [52] is then:

C. J. Date and Hugh Darwen: Foundation for Object/Relational Databases: The Third Manifesto. Reading, Mass.: Addison-Wesley (1998). A second edition of this book, under the revised title Foundation for Future Database Systems: The Third Manifesto, is due to appear concurrently with the present book.

I think Date did a lot of harm with this comment. The classic example of a transaction is taking $100 from my account and depositing it in your account. So there’s one statement to take the money out, and another statement to put the money in, and after the first statement but before the second statement the database will always go through an invalid state. If RDBMS integrity facilities were on a transaction-by-transaction basis we could actually use them, as they’re not we suffer. Either we need to do more work than necessary or we have to under specify our constraints, or some awkward combination of both.