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Denormalization

Learn the deliberate repeat scenario.

Denormalization

Denormalization adds deliberately copied columns to a normalized table to speed up reads. Writes get more costly but read queries simplify.

-- orders tablosuna customer_name ekle
-- JOIN gereği azalır, okuma hızlanır

Denormalization speeds up reads.

Denormalization — details

Denormalization helps in reporting and OLAP workloads. In OLTP systems it is used with care due to write anomaly risk.

Practice Denormalization

Add a customer_name TEXT column to orders for denormalization.

Starter code

query.sql
-- denormalization
ALTER TABLE orders

Sample solution

query.sql
ALTER TABLE orders
ADD COLUMN customer_name TEXT;

Expected output

ALTER TABLE

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 Add a column to the table

Question 
ALTER TABLE orders ADD COLUMN ____ TEXT
Answer 
ALTER TABLE orders ADD COLUMN customer_name TEXT

Explanation: customer_name is the right answer.

2 Denormalization: match the terms

Term Meaning
normalize split
denormalize merge
OLAP report
OLTP transaction

3 What does denormalization increase?

  • Write speed
  • The number of tables
  • Read speed Correct answer
  • It reduces disk size

Explanation: Denormalization increases read speed.

All lessons in Expert

1 Database design

  1. ER model
  2. Cardinality
  3. Surrogate keys
  4. Natural keys
  5. Denormalization
  6. Summary - Design

2 Index tuning

  1. B-tree structure
  2. Covering index
  3. Partial index
  4. Index selectivity
  5. Index maintenance
  6. Summary - Index tuning

3 Query optimizer

  1. What is an optimizer?
  2. Statistics
  3. Cost model
  4. Join strategies
  5. Plan cache
  6. Summary - Optimizer

4 Project: Performance tuning

  1. Scenario design
  2. Reading plans
  3. Adding indexes
  4. Rewriting queries
  5. Comparing results

5 Replication and sharding

  1. What is replication?
  2. Master-slave
  3. Sync vs async
  4. What is sharding?
  5. Shard key
  6. Summary - Replication and sharding

6 Distributed and big data

  1. Distributed queries
  2. MPP
  3. Columnar storage
  4. SQL on Hadoop
  5. SQL vs NoSQL
  6. Summary - Distributed and big data

7 Security and backup

  1. SQL injection
  2. Parameterised queries
  3. Authorisation
  4. Backup
  5. Recovery
  6. Summary - Security and backup

8 Expert final

  1. Design challenge
  2. Optimization challenge
  3. Security challenge
  4. Backup challenge