Database Normalization and Optimization


  • Describe “normalization” of a database
  • Describe some best practices around optimization of tables
  • Describe how indexing mechanics work at a high level


  • Normalization
  • B-Tree


Available here


  • Read this article on database normalization.
  • In your own words summarize what database normalization is.

Defining Key Terms

  • Normalization - An optimization and reorganization of database tables that removes data duplication
  • B-Tree - A data structure, a generalized version of a “binary tree”, sometimes called a “trie”, which is commonly used for storing indexes within PostgreSQL


“Normalization” is usually done by examining our database table structure to look for duplicated data, usually strings, and find ways to replace those values with something which is faster to store and search.

For example, let’s take a look at one potential schema for a database linking students and courses.

ActiveRecord::Schema.define(version: 20171204033005) do

  # These are extensions that must be enabled in order to support this database
  enable_extension "plpgsql"

  create_table "courses", force: :cascade do |t|
    t.string "title"
    t.string "description"

  create_table "students", force: :cascade do |t|
    t.string "first_name"
    t.string "last_name"
    t.bigint "course_id"
    t.integer "score"
    t.index ["course_id"], name: "index_students_on_course_id"


Given that course_id exists on the students table, we might assume a one-to-many relationship between courses and students. What if the actual relationship was many-to-many? Without changing the database, how would we record the fact that a student was enrolled in multiple courses?

We could potentially put multiple course ids in the course_id column. We could also have multiple course_id columns (e.g. course_1_id, course_2_id, etc.). Or we could have multiple rows that had the same first/last name for a student. However, none of these solutions would be normalized.

How could we adjust the structure of the database to record a many-to-many relationship between students?

Why Normalize

Imagine for a moment we did not normalize the database, but instead pursued one of the other solutions described above. How would we find all of the students enrolled in a particular course? What opportunities for error/corrupted information would exist?

How does normalization help resolve these potential issues?


  • Imagine you were going to create a database to store the information in the JSON hash below. How might you structure your database?
payload = '{
  "requestedAt":"2013-02-16 21:38:28 -0700",
  "eventName": "socialLogin",
  "userAgent":"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_2) AppleWebKit/537.17 (KHTML, like Gecko) Chrome/24.0.1309.0 Safari/537.17",
  • Review this commodity trade data. How might you structure a normalized database to store this data?

  • Review this New York Times article data. How might you structure a normlalized database to store this data?

How are tables and indexes actually stored in PostgreSQL

Clone (or re-use) the roster repo. Run bundle to install any missing gems, then run rake db:{create,migrate,seed}.

From a terminal prompt, run psql roster-development. Use \q within the psql shell to exit back to your terminal prompt.

Based on the belongs_to and has_many attributes in our /app/models/student.rb and /app/models/course.rb, we can see how ActiveRecord constructs our tables. But what do these actually look like in PostgreSQL? Let’s take a look.

Run psql roster-development in a new terminal window. Here, we can execute a SQL command to list all of our students:

roster-development=# select * from students;
id | first_name |  last_name  | course_id | score
 1 | Brian      | Zanti       |         1 |     3
 2 | Megan      | McMahon     |         1 |     4
 3 | Josh       | Mejia       |         3 |     2
 4 | Mike       | Dao         |         3 |     3
 5 | Dione      | Wilson      |         2 |     2
 6 | Ian        | Douglas     |         2 |     4
 7 | Cory       | Westerfield |         4 |     3
 8 | Sal        | Espinosa    |         1 |     2
(8 rows)

This, however, doesn’t tell us very much about the table itself, only the data within it. Let’s examine the structure of the table:

roster-development=# \d students
                                   Table "public.students"
   Column   |       Type        | Collation | Nullable |               Default
 id         | bigint            |           | not null | nextval('students_id_seq'::regclass)
 first_name | character varying |           |          |
 last_name  | character varying |           |          |
 course_id  | bigint            |           |          |
 score      | integer           |           |          |
    "students_pkey" PRIMARY KEY, btree (id)
    "index_students_on_course_id" btree (course_id)

This view allows us to see how ActiveRecord’s schema actually built the table in PostgreSQL. Other databases like SQLite and MySQL will use different ‘types’ for the fields, and may use different index types, but let’s break this down into its components.

Pair up and examine the following:

  • we see the id field and course_id fields are a type called bigint – what is a bigint data type?
  • a “varying” character type used for the student’s first and last names means the database will accept a string of changing length, instead of a fixed-length string (eg, this field is always 15-characters long)
  • the score field is an integer – how is that different from a bigint?
  • we can also see that the id field is marked as not null – what does this mean?
  • the “default” value for an id, if not provided, will use a sequence (“seq”) – what is a sequence in PostgreSQL?

What are “btree” indexes?

We can also see from the output that we have a single PRIMARY KEY on our (id) field, which uses a btree type, and that our course_id field also uses a btree index type.

A b-tree is like the “prefix” tree that you may have used in the Complete Me project in Mod 1, where each node in the tree can have multiple children. We won’t dive into the theory of it, but this is the most-used index type within PostgreSQL.

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