![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](https://image.slidesharecdn.com/aug2017-postgresqlinternals-170803141531/85/Grokking-TechTalk-20-PostgreSQL-Internals-101-27-320.jpg)
Grokking TechTalk #20: PostgreSQL Internals 101
- 1. Huy Nguyen CTO, Cofounder - Holistics Software Cofounder, Grokking Vietnam PostgreSQL Internals 101 /post:gres:Q:L/
- 2. 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
- 3. ● 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)
- 4. Uber migrating from PostgreSQL to MySQL
- 5. 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
- 6. ● 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
- 7. 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)
- 8. TRUNCATE table; vs DELETE FROM table;
- 9. demodb=# select oid, relname, relfilenode from pg_class where relname = 'test'; oid | relname | relfilenode --------+---------+------------- 416854 | test | 416854 (1 row) demodb=# truncate test; TRUNCATE TABLE INSERT 0 1 demodb=# select oid, relname, relfilenode from pg_class where relname = 'test'; oid | relname | relfilenode --------+---------+------------- 416854 | test | 416857 (1 row)
- 10. 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.
- 11. 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.
- 12. ● 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
- 13. 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
- 17. Because each UPDATE creates new tuple (and marks old tuple deleted), lots of UPDATEs will soon increase the table’s physical size. Table Bloat
- 18. 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 …. ….
- 19. 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 …. ….
- 20. MySQL / InnoDB ● MVCC: Inline update of tuples ● Table Layout: B+ tree on Primary Key ● Index: points to primary key
- 21. MySQL data is B+ Tree (on primary key) Leaf nodes contain actual rows data MySQL Table (B+ tree) H B A C row data ... primary key
- 22. 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
- 24. 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
- 25. 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
- 26. 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.
- 27. 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
- 28. 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/
- 29. ● 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
- 30. ● 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
- 31. 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 PostgreSQL http://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
- 32. Huy Nguyen
- 34. 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
- 35. PostgreSQL Processes There 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. http://www.interdb.jp/pg/pgsql02.html
- 36. 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 indexes views, materialized views functions schema sequences ... role (user/group