CodeBlanks Logo Icon CodeBlanks
Login Register

Summary - Optimizer

Refresh statistics with ANALYZE.

Summary - Optimizer

The optimizer: EXPLAIN builds plans, statistics and histogram set the cost, a join strategy is picked, the plan cache speeds repeats. The right plan gives the right speed.

-- EXPLAIN -> ANALYZE -> plan cache
-- nested loop / hash join / merge join

The optimizer weaves four parts.

Practice Summary - Optimizer

Summary task: compare the join plan of orders and customers with EXPLAIN ANALYZE.

Starter code

query.sql
-- summary optimizer
EXPLAIN

Sample solution

query.sql
EXPLAIN ANALYZE SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id;

Expected output

Hash Join on orders x customers (actual time=0.020..0.035 rows=5)

Questions and answers

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

1 See plan and time

Question 
EXPLAIN ____ SELECT * FROM orders;
Answer 
EXPLAIN ANALYZE SELECT * FROM orders;

Explanation: ANALYZE is the right answer.

2 Which join suits a large equality join?

  • Cross join
  • Nested loop
  • Seq scan
  • A hash join Correct answer

Explanation: A hash join suits a large equality join.

3 Summary - Optimizer: match the terms

Term Meaning
EXPLAIN plan
ANALYZE stats
hash join hash
plan cache cache

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