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Index selectivity

Learn selectivity and cardinality.

Index selectivity

Selectivity is the ratio of rows matching a condition. High selectivity (few rows) uses the index well; low selectivity (many rows) skips the index and scans the table.

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High selectivity is good for indexes.

Index selectivity — details

The optimizer computes selectivity from statistics gathered by ANALYZE. Stale statistics give wrong plans; that is why ANALYZE runs after big changes.

Practice Index selectivity

Run ANALYZE to refresh statistics for the products table.

Starter code

query.sql
-- gather statistics
ANALYZE

Sample solution

query.sql
ANALYZE products;

Expected output

ANALYZE

Questions and answers

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

1 What does high selectivity mean?

  • Many rows match
  • The whole table is scanned
  • The index is skipped
  • Few rows match Correct answer

Explanation: High selectivity means few rows match.

2 Gather statistics

Question 
ANALYZE ____
Answer 
ANALYZE products

Explanation: products is the right answer.

3 Index selectivity: match the terms

Term Meaning
selectivity selectivity
high high
few rows few rows
ANALYZE statistics

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