Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
How Postgres Could Index Itself
Search
Andrew Kane
September 08, 2017
Programming
0
3.2k
How Postgres Could Index Itself
Andrew Kane
September 08, 2017
Tweet
Share
Other Decks in Programming
See All in Programming
私達はmodernize packageに夢を見るか feat. go/analysis, go/ast / Go Conference 2025
kaorumuta
2
540
Django Ninja による API 開発効率化とリプレースの実践
kashewnuts
0
1.3k
私はどうやって技術力を上げたのか
yusukebe
43
18k
CSC509 Lecture 04
javiergs
PRO
0
300
Le côté obscur des IA génératives
pascallemerrer
0
140
登壇は dynamic! な営みである / speech is dynamic
da1chi
0
300
詳しくない分野でのVibe Codingで困ったことと学び/vibe-coding-in-unfamiliar-area
shibayu36
3
4.9k
「ちょっと古いから」って避けてた技術書、今だからこそ読もう
mottyzzz
10
6.6k
CSC509 Lecture 06
javiergs
PRO
0
260
ポスターセッション: 「まっすぐ行って、右!」って言ってラズパイカーを動かしたい 〜生成AI × Raspberry Pi Pico × Gradioの試作メモ〜
komofr
0
1.3k
いま中途半端なSwift 6対応をするより、Default ActorやApproachable Concurrencyを有効にしてからでいいんじゃない?
yimajo
2
400
Android16 Migration Stories ~Building a Pattern for Android OS upgrades~
reoandroider
0
100
Featured
See All Featured
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.1k
Building Flexible Design Systems
yeseniaperezcruz
329
39k
Designing Experiences People Love
moore
142
24k
Designing for humans not robots
tammielis
254
26k
Visualization
eitanlees
149
16k
Keith and Marios Guide to Fast Websites
keithpitt
411
23k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
31
9.7k
Practical Orchestrator
shlominoach
190
11k
The World Runs on Bad Software
bkeepers
PRO
72
11k
Docker and Python
trallard
46
3.6k
How GitHub (no longer) Works
holman
315
140k
"I'm Feeling Lucky" - Building Great Search Experiences for Today's Users (#IAC19)
danielanewman
229
22k
Transcript
How Postgres Could Index Itself
None
github.com/ankane
None
Read speed vs Write speed Space
None
v1
Collect queries Analyze queries
pg_stat_statements Query Total Time (ms) Calls Average Time (ms) SELECT
… 40,000 80,000 0.5 SELECT … 30,000 300 100
SELECT * FROM products WHERE store_id = 1
pg query github.com/lfittl/pg_query _
SELECT * FROM products WHERE store_id = 1
SELECT * FROM products WHERE store_id = 1 AND brand_id
= 2
Stores have many products Brands have a few products
id store_id brand_id 1 1 2 2 4 8 3
1 9 4 1 3 fetch store_id = 1 id store_id brand_id 1 1 2 2 4 8 3 1 9 4 1 3 filter brand_id = 2 id store_id brand_id 1 1 2 2 4 8 3 1 9 4 1 3 id store_id brand_id 1 1 2 2 4 8 3 1 9 4 1 3 filter store_id = 1 fetch brand_id = 2
pg_stats n_distinct null_frac
store_id brand_id Rows 100,000 100,000 null_frac 0 0.10 n_distinct 100
9,000 Estimated Rows 1,000 10
store_id brand_id Rows 100,000,000 100,000,000 null_frac 0 0.10 n_distinct 100
9,000 Estimated Rows 1,000,000 10,000
store_id Rows 10,000 null_frac 0 n_distinct 100 Estimated Rows 100
SELECT * FROM products ORDER BY created_at DESC LIMIT 10
SELECT * FROM products WHERE store_id = 1 ORDER BY
created_at DESC LIMIT 10
None
Shortcomings
Single table plus Simple WHERE clause and/or Simple ORDER BY
clause
Duplicating planner logic
pg_stats n_distinct null_frac ✗ most_common_vals ✗ most_common_freqs ✗ histogram_bounds
most_common_vals {2, 5, 1} most_common_freqs {0.9, 0.05, 0.01} store_id =
1 vs store_id = 2
histogram_bounds {0, 9, 25, 60, 99} qty < 5 vs
qty > 5
SELECT * FROM products WHERE store_id = ?
v2
log_min_statement_duration duration: 100 ms statement: SELECT * FROM products WHERE
store_id = 1
Given a query and a set of indexes best indexes
to use
Given a query and all possible indexes best indexes possible
/* Allow a plugin to editorialize on the info we
obtained from the catalogs. Actions might include altering the assumed relation size, removing an index, or adding a hypothetical index to the indexlist. */ get_relation_info_hook 604ffd2
hypopg github.com/dalibo/hypopg
SELECT * FROM products WHERE store_id = 1 AND brand_id
= 2
EXPLAIN Seq Scan on products (cost=0.00..1000.00 rows=100 width=108) Filter: (store_id
= 1 AND brand_id = 2) Final Cost
Cost Hypothetical Indexes Original 1000
Add hypothetical indexes store_id brand_id
EXPLAIN Index Scan using <41072>hypo_btree on products (cost=0.28..50.29 rows=1 width=108)
Index Cond: (brand_id = 2) Filter: (store_id = 1) Final Cost Index
Cost Hypothetical Indexes Original 1000 Single Column 50 brand_id
Add hypothetical indexes store_id, brand_id brand_id, store_id (does not try
different sort orders right now)
Cost Hypothetical Indexes Original 1000 Single Column 50 brand_id Multi
Column 45 brand_id, store_id
Dexter github.com/ankane/dexter
tail -F -n +1 <log-file> | dexter <conn-opts>
--create --exclude big_table --min-time 10
Shortcomings
SELECT * FROM products WHERE a = 1 AND b
= 2 SELECT * FROM products WHERE b = 2
B-TREE Only No Expressions No Partial
SELECT * FROM products WHERE qty = 0
DROP INDEX Unused indexes
HypoPG Extension Support
None
pg_query HypoPG
Get Involved github.com/ankane/dexter