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Statistics

Learn statistics and histograms.

Statistics

Statistics are table and column facts the optimizer uses to choose a plan. They include row count, most common values (MCV) and a histogram.

ANALYZE orders;
-- pg_stats görünümünde histogram görünür

This query statistics drive plan choice.

Statistics — details

A histogram splits column values into equal-width buckets. It reflects skewed data correctly and prevents wrong plans.

Practice Statistics

Refresh statistics for the orders table: ANALYZE orders.

Starter code

query.sql
-- gather statistics
ANALYZE

Sample solution

query.sql
ANALYZE orders;

Expected output

ANALYZE

Questions and answers

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

1 Gather statistics

Question 
ANALYZE ____
Answer 
ANALYZE orders

Explanation: ANALYZE orders collects the table's statistics; the optimizer picks plans based on them.

2 What does the optimizer use?

  • A procedure
  • A trigger
  • A view
  • Statistics Correct answer

Explanation: The optimizer uses statistics.

3 Statistics: match the terms

Term Meaning
statistics statistics
histogram histogram
MCV most common
skewed skewed

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