grokking techtalk #20: postgresql internals 101

Huy Nguyen

CTO, Cofounder - Holistics SoftwareCofounder, Grokking Vietnam

PostgreSQL Internals 101

/post:gres:Q:L/

About Me

Education:

● Pho Thong Nang Khieu, Tin 04-07

● National University of Singapore (NUS), Computer Science Major.

Work:

● Software Engineer Intern, SenseGraphics (Stockholm, Sweden)

● Software Engineer Intern, Facebook (California, US)

● Data Infrastructure Engineer, Viki (Singapore)

Now:

● Co-founder & CTO, Holistics Software

● Co-founder, Grokking Vietnam

[email protected] facebook.com/huy bit.ly/huy-linkedin

mailto:[email protected]

http://fb.com/huy

http://bit.ly/huy-linkedin

● This talk covers a very small part of PostgreSQL concepts/internals

● As with any RDBMS, PostgreSQL is a complex system, and it’s still evolving.

● Mainly revolve around explaining “Uber’s MySQL vs PostgreSQL” article.

● Not Covered: Memory Management, Query Planning, Replication, etc...

Agenda

● Uber’s Article

● Table Heap

● B-Tree Index

● MVCC

● MySQL Structure

● PostgreSQL vs MySQL (Uber Use-case)

● Index-only Scan

● Heap-only Tuple (HOT)

Uber migrating from PostgreSQL to MySQL

Uber’s Use Case● Table with lots of indexes (cover almost/all columns)● Lots of UPDATEs

⇒ MySQL handles this better than PostgreSQL

● Read more here

https://www.facebook.com/huy/posts/10154901251333163?

● Everything is under base directory ($PGDATA). /var/lib/postgresql/9.x/main

● Each database is a folder name after its oid

Physical Structure

http://www.interdb.jp/pg/pgsql01.html

demodb=# select oid, relname, relfilenode from pg_class where relname = 'test';

oid | relname | relfilenode --------+---------+------------- 416854 | test | 416854(1 row)

Physical Structure

Each table’s data is in 1 or multiple files (max 1GB each)

TRUNCATE table;

vs

DELETE FROM table;

Tuple Address (ctid)

ctid id name

(0, 2) 1 Alice

(0, 5) 2 Bob

(1, 3) 3 Charlie

ctid (tuple ID): a pair of (block, location) to position the tuple in the data file.

Heap Table Structure

Page: a block of content, default to 8KB each.

Line pointers: 4-byte number address, holds pointer to each tuple.

For tuple with size > 2KB, a special storage method called TOAST is used.

● Problem: Someone reading data, while someone else is writing to it

● Reader might see inconsistent piece of data

● MVCC: Allow reads and writes to happen concurrently

MVCC - Multi-version Concurrency Control

MVCC - Table

xmin xmax id name

1 5 1 Alice

2 3 2 Bob

3 2 Robert

4 3 Charlie

1. INSERT Alice

2. INSERT Bob

3. UPDATE Bob → Robert

4. INSERT Charlie

5. DELETE Alice

● xmin: transaction ID that inserts this tuple

● xmax: transaction that removes this tuple

INSERT

1


DELETE

1


UPDATE


Because each UPDATE creates new tuple (and marks old tuple deleted), lots of UPDATEs will soon increase the table’s physical

size.

Table Bloat

Index (B-tree)

H

B

A C

Balanced search tree.

Root node and inner nodes contain keys and pointers to lower level nodes

Leaf nodes contain keys and pointers to the heap (ctid)

When table has new tuples, new tuple is added to index tree.Heap

ctid

D

A1

…. ….

Write Amplifications

● Each UPDATE inserts new tuple.

● New index tuples● ⇒ multiple writes

● Extra overhead to Write-ahead Log (WAL)

● Carried over through network

● Applied on Slave

H

B

A C

Heap

ctid

D

A1

…. ….

MySQL / InnoDB

● MVCC: Inline update of tuples

● Table Layout: B+ tree on Primary Key

● Index: points to primary key

MySQL data is B+ Tree (on primary key)

Leaf nodes contain actual rows data

MySQL Table (B+ tree)

H

B

A Crow data

...

primary key

MySQL Index

● MySQL: the node’s value store primary key

● A lookup on secondary index requires 2 index traversals: secondary index + primary index.

H

B

A C

Table

D

A1

…. ….

primary key

https://blog.jcole.us/2013/01/10/btree-index-structures-in-innodb/

PostgreSQL vs MySQL (Uber case)

PostgreSQL MySQL

MVCC New Tuple Per UPDATE Inline update of tuple (with rollback segments)

Index Lookup Store physical address (ctid) By primary key

Table Layout Heap-table structure Primary-key table structure

PostgreSQL vs MySQL (Uber case)

PostgreSQL MySQL

select on primary key log(N) + heap read log(n) + direct read

update Update all indexes;1 data write

Do not update indexes;2 data writes

select on index key log(n) + O(1) heap read log(n) + log(n) primary index read

sequential scan Page sequential scan Index-order scan

Index-only Scan (Covering Index)

Index on (product_id, revenue)

SELECT SUM(revenue) FROM table WHERE product_id = 123

If the index itself has all the data needed, no Heap Table lookup is required.

Visibility Map

Per table’s page

VM[i] is set: all tuples in page i are visible to current transactions

VM is only updated by VACUUM

https://www.slideshare.net/pgdayasia/introduction-to-vacuum-freezing-and-xid

Heap-only Tuple (HOT)

● No new index needs to be updated

Conditions:● Must not update a column that’s

indexed● New tuple must be in the same

page

http://slideplayer.com/slide/9883483/

● Clean up dead tuples

● Freeze old tuples (prevent transactions wraparound)

● VACUUM only frees old tuples

● VACUUM FULL reclaims old disk spaces, but blocks writes

VACUUM

● Add a new column (safe)

● Add a column with a default (unsafe)

● Add a column that is non-nullable (unsafe)

● Drop a column (safe)

● Add a default value to an existing column (safe)

● Add an index (unsafe)

Safe & Unsafe Operations In PostgreSQL

http://leopard.in.ua/2016/09/20/safe-and-unsafe-operations-postgresql

References

● Why Uber Engineering switched from PostgreSQL to MySQL - https://eng.uber.com/mysql-migration/

● PostgreSQL Documentations - https://www.postgresql.org/docs/current/static/

● The Internals of PostgreSQLhttp://www.interdb.jp/pg/

● http://leopard.in.ua/2016/09/20/safe-and-unsafe-operations-postgresql

● http://slideplayer.com/slide/9883483/

● https://www.slideshare.net/pgdayasia/introduction-to-vacuum-freezing-and-xid

https://eng.uber.com/mysql-migration/

https://www.postgresql.org/docs/current/static/

http://www.interdb.jp/pg/

http://leopard.in.ua/2016/09/20/safe-and-unsafe-operations-postgresql

http://slideplayer.com/slide/9883483/



Huy Nguyen

Physical Structure

https://www.postgresql.org/docs/current/static/storage-file-layout.html

Transaction Isolation

BEGIN TRANSACTION;

SELECT * FROM table;

SELECT pg_sleep(10);

SELECT * FROM table;

COMMIT;

under READ COMMITTED, the second SELECT may return any data. A concurrent transaction may update the record, delete it, insert new records. The second select will always see the new data.

under REPEATABLE READ the second SELECT is guaranteed to see the rows that has seen at first select unchanged. New rows may be added by a concurrent transaction in that one minute, but the existing rows cannot be deleted nor changed.

under SERIALIZABLE reads the second select is guaranteed to see exactly the same rows as the first. No row can change, nor deleted, nor new rows could be inserted by a concurrent transaction.

https://stackoverflow.com/questions/4034976/difference-between-read-commit-and-repeatable-read

PostgreSQL ProcessesThere are multiple processes handling different use cases.

● postmaster process: handles database cluster management.

● Many backend processes (one for each connection)

● Background processes: stats collector, autovacuum, checkpoint, WAL writer, etc.


Database Cluster

● database cluster: a database instance in a single machine.

● A database contains many database objects (schema, table, index, view, function, etc)

● Each object is represented by an oid

Database Cluster

Database 1 Database 2 Database n...

tables indexesviews,

materialized views

functions

schema

sequences...

role (user/group

grokking techtalk #20: postgresql internals 101

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