Django postgresql backend that apply migrations with respect to database locks
Switch branches/tags
Nothing to show
Clone or download
tbicr Merge pull request #4 from tbicr/minor-fixes
delete unused code, add improvements to readme, fix tests
Latest commit fcfa879 Oct 10, 2018

README.md

Build Status

django-pg-zero-downtime-migrations

Django postgresql backend that apply migrations with respect to database locks.

Installation

pip install django-pg-zero-downtime-migrations

NOTE: this package works with django 2.0+.

Usage

To enable zero downtime migrations for postgres just setup django backend provided by this package:

DATABASES = {
    'default': {
        'ENGINE': 'django_zero_downtime_migrations_postgres_backend',
        ...
    }
}

NOTE: this backend brings zero downtime improvements only for migrations (schema and RunSQL operations, but not for RunPython operation), for other purpose it works the same as standard django backend.

NOTE: this package is in beta, please check your migrations SQL before applying on production and submit issue for any question.

Differences with standard django backend

This backend provides same result state (instead NOT NULL constraint replacement), but different way and with additional guarantees for avoiding stuck tables lock.

This backend doesn't use transactions for migrations (except RunPython operation), because not all fixed SQL can be run in transaction and it allows to avoid deadlocks for complex migration. So when your migration will down in middle of transaction you need fix it manually (instead potential downtime).

Deployment flow

There ara main rules for zero downtime deployment:

  1. We have one database;
  2. We have several instances with application - application always should be available, even you restart one of instances;
  3. We have balancer before instances;
  4. Our application works fine before, on and after migration - old application works fine with old and new database schema version;
  5. Our application works fine before, on and after instance updating - old and new application versions work fine with new database schema version.

Flow:

  1. apply migrations
  2. disconnect instance form balancer, restart it and back to balancer - repeat this operation one by one for all instances

If our deployment don't satisfy zero downtime deployment rules, then we split it to smaller deployments.

Additional settings

ZERO_DOWNTIME_MIGRATIONS_LOCK_TIMEOUT

Apply statement_timeout:

ZERO_DOWNTIME_MIGRATIONS_LOCK_TIMEOUT = '2s'

ZERO_DOWNTIME_MIGRATIONS_STATEMENT_TIMEOUT

Apply lock_timeout:

ZERO_DOWNTIME_MIGRATIONS_STATEMENT_TIMEOUT = '2s'

ZERO_DOWNTIME_MIGRATIONS_FLEXIBLE_STATEMENT_TIMEOUT

Set statement_timeout to 0ms in case when statement_timeout enabled globally and you try run long-running operation like index creation or constraint validation:

ZERO_DOWNTIME_MIGRATIONS_FLEXIBLE_STATEMENT_TIMEOUT = True

ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE

Enabled option doesn't allow run potential unsafe migration.

ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE = True

ZERO_DOWNTIME_MIGRATIONS_USE_NOT_NULL

Set policy for avoiding NOT NULL constraint creation long lock.

ZERO_DOWNTIME_MIGRATIONS_USE_NOT_NULL = 10 ** 7

Allowed values:

  • None - standard django's behaviour (raise for ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE = True)
  • True - always replace NOT NULL constraint with CHECK (field IS NOT NULL) (don't raise for ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE = True)
  • False - always use NOT NULL constraint (don't raise for ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE = True)
  • int value - use CHECK (field IS NOT NULL) instead NOT NULL constraint if table has more than value rows (approximate rows count used) otherwise use NOT NULL constraint (don't raise for ZERO_DOWNTIME_MIGRATIONS_RAISE_FOR_UNSAFE = True)

Dealing with partial indexes

If you using https://github.com/mattiaslinnap/django-partial-index package for partial indexes in postgres, then you can easily make this package also safe for migrations:

from django_zero_downtime_migrations_postgres_backend.schema import PGShareUpdateExclusive
from partial_index import PartialIndex

PartialIndex.sql_create_index['postgresql'] = PGShareUpdateExclusive(
    'CREATE%(unique)s INDEX CONCURRENTLY %(name)s ON %(table)s%(using)s (%(columns)s)%(extra)s WHERE %(where)s',
    disable_statement_timeout=True
)

How it works

Postgres table level locks

Postgres has different locks on table level that can conflict with each other https://www.postgresql.org/docs/current/static/explicit-locking.html#LOCKING-TABLES:

ACCESS SHARE ROW SHARE ROW EXCLUSIVE SHARE UPDATE EXCLUSIVE SHARE SHARE ROW EXCLUSIVE EXCLUSIVE ACCESS EXCLUSIVE
ACCESS SHARE X
ROW SHARE X X
ROW EXCLUSIVE X X X X
SHARE UPDATE EXCLUSIVE X X X X X
SHARE X X X X X
SHARE ROW EXCLUSIVE X X X X X X
EXCLUSIVE X X X X X X X
ACCESS EXCLUSIVE X X X X X X X X

Migration and business logic locks

Lets split this lock to migration and business logic operations.

  • Migration operations work synchronously in one thread and cover schema migrations (data migrations conflict with business logic operations same as business logic conflict concurrently).
  • Business logic operations work concurrently.

Migration locks

lock operations
ACCESS EXCLUSIVE CREATE SEQUENCE, DROP SEQUENCE, CREATE TABLE, DROP TABLE *, ALTER TABLE **, DROP INDEX
SHARE CREATE INDEX
SHARE UPDATE EXCLUSIVE CREATE INDEX CONCURRENTLY, DROP INDEX CONCURRENTLY ***, ALTER TABLE VALIDATE CONSTRAINT ****

*: CREATE SEQUENCE, DROP SEQUENCE, CREATE TABLE, DROP TABLE shouldn't have conflicts, because your logic shouldn't operate with it

**: Not all ALTER TABLE operations take ACCESS EXCLUSIVE lock, but all current django's migrations take it https://github.com/django/django/blob/master/django/db/backends/base/schema.py, https://github.com/django/django/blob/master/django/db/backends/postgresql/schema.py and https://www.postgresql.org/docs/current/static/sql-altertable.html

***: Django currently doesn't support CONCURRENTLY operations

****: Django doesn't have VALIDATE CONSTRAINT logic, but we will use it for some cases

Business logic locks

lock operations conflict with lock conflict with operations
ACCESS SHARE SELECT ACCESS EXCLUSIVE ALTER TABLE, DROP INDEX
ROW SHARE SELECT FOR UPDATE ACCESS EXCLUSIVE, EXCLUSIVE ALTER TABLE, DROP INDEX
ROW EXCLUSIVE INSERT, UPDATE, DELETE ACCESS EXCLUSIVE, EXCLUSIVE, SHARE ROW EXCLUSIVE, SHARE ALTER TABLE, DROP INDEX, CREATE INDEX

So you can find that all django schema changes for exist table conflicts with business logic, but fortunately they are safe or has safe alternative in general.

Postgres row level locks

As business logic mostly works with table rows it's also important to understand lock conflicts on row level https://www.postgresql.org/docs/current/static/explicit-locking.html#LOCKING-ROWS:

lock FOR KEY SHARE FOR SHARE FOR NO KEY UPDATE FOR UPDATE
FOR KEY SHARE X
FOR SHARE X X
FOR NO KEY UPDATE X X X
FOR UPDATE X X X X

Main point there is if you have two transactions that update one row, then second transaction will wait until first will be completed. So for business logic and data migrations better to avoid updates for whole table and use batch operations instead.

NOTE: batch operations also can work faster because it helps postgres make more optimal execution plan.

Transactions FIFO waiting

postgres FIFO

Found same diagram in interesting article http://pankrat.github.io/2015/django-migrations-without-downtimes/.

In this diagram we can extract several metrics:

  1. operation time - time what you spend for schema change, so there is issue for long running operation on many rows tables like CREATE INDEX or ALTER TABLE ADD COLUMN SET DEFAULT, so you need use more save equivalents instead.
  2. waiting time - your migration will wait until all transactions will be completed, so there is issue for long running operations/transactions like analytic, so you need avoid it or disable on migration time.
  3. queries per second + execution time and connections pool - if you too many queries to table and this queries take long time then this queries can just take all available connections to database until wait for release lock, so look like you need different optimizations there: run migrations when load minimal, decrease queries count and execution time, split you data.
  4. too many operations in one transaction - you have issues in all previous points for one operation so if you have many operations in one transaction then you have more chances to get this issues, so you should avoid many operations in one transactions (or event don't run it in transactions at all but you should be more careful when some operation will fail).

Dealing with timeouts

Postgres has two settings to dealing with waiting time and operation time presented in diagram: lock_timeout and statement_timeout.

SET lock_timeout TO '2s' allow you to avoid downtime when you have long running query/transaction before run migration (https://www.postgresql.org/docs/current/static/runtime-config-client.html#GUC-LOCK-TIMEOUT).

SET statement_timeout TO '2s' allow you to avoid downtime when you have long running migration query (https://www.postgresql.org/docs/current/static/runtime-config-client.html#GUC-STATEMENT-TIMEOUT).

Deadlocks

There no downtime issues for deadlocks, but too many operations in one transaction will take most conflictable lock and release it only after transaction commit or rollback. So it's a good idea to avoid ACCESS EXCLUSIVE lock operations and long time operations in one transaction. Deadlocks also can make you migration stuck on production deployment when different tables will be locked, for example, for FOREIGN KEY that take ACCESS EXCLUSIVE lock for two tables.

Rows and values storing

Postgres store values of different types different ways https://www.postgresql.org/docs/current/static/storage-toast.html#STORAGE-TOAST-ONDISK. When you try to convert one type to another and it stored different way postgres will rewrite all values. Fortunately some types stored same way and postgres need to do nothing to change type, but in some cases postgres need to check that all values have same with new type limitations.

Multiversion Concurrency Control

Regarding documentation https://www.postgresql.org/docs/current/static/mvcc-intro.html data consistency in postgres is maintained by using a multiversion model. This means that each SQL statement sees a snapshot of data. It has advantage that adding and deleting columns without any indexes, constrains and defaults do not change exist data, new version of data will be create on INSERT and UPDATE, delete just mark you record expired. All garbage will be collected later by VACUUM or AUTO VACUUM.

Django migrations hacks

Any schema changes can be processed with creation of new table and copy data to it, so just mark unsafe operations that don't have another safe way without downtime as NO.

# name safe safe alternative description
1 CREATE SEQUENCE X safe operation, because your business logic shouldn't operate with new sequence on migration time *
2 DROP SEQUENCE X safe operation, because your business logic shouldn't operate with this sequence on migration time *
3 CREATE TABLE X safe operation, because your business logic shouldn't operate with new table on migration time *
4 DROP TABLE X safe operation, because your business logic shouldn't operate with this table on migration time *
5 ALTER TABLE RENAME TO NO unsafe operation, it's too hard write business logic that operate with two tables simultaneously, so propose CREATE TABLE and then copy all data to new table *
6 ALTER TABLE SET TABLESPACE NO unsafe operation, but probably you don't need it at all or often *
7 ALTER TABLE ADD COLUMN X safe operation if without SET NOT NULL, SET DEFAULT, PRIMARY KEY, UNIQUE *
8 ALTER TABLE ADD COLUMN SET DEFAULT add column and set default unsafe operation, because you spend time in migration to populate all values in table, so propose ALTER TABLE ADD COLUMN and then populate column and then SET DEFAULT *
9 ALTER TABLE ADD COLUMN SET NOT NULL +/- unsafe operation, because doesn't work without SET DEFAULT, so propose ALTER TABLE ADD COLUMN and then populate column and then ALTER TABLE ALTER COLUMN SET NOT NULL * and **
10 ALTER TABLE ADD COLUMN PRIMARY KEY add index and add constraint unsafe operation, because you spend time in migration to CREATE INDEX, so propose ALTER TABLE ADD COLUMN and then CREATE INDEX CONCURRENTLY and then ALTER TABLE ADD CONSTRAINT PRIMARY KEY USING INDEX ***
11 ALTER TABLE ADD COLUMN UNIQUE add index and add constraint unsafe operation, because you spend time in migration to CREATE INDEX, so propose ALTER TABLE ADD COLUMN and then CREATE INDEX CONCURRENTLY and then ALTER TABLE ADD CONSTRAINT UNIQUE USING INDEX ***
12 ALTER TABLE ALTER COLUMN TYPE +/- unsafe operation, because you spend time in migration to check that all items in column valid or to change type, but some operations can be safe ****
13 ALTER TABLE ALTER COLUMN SET NOT NULL +/- unsafe operation, because you spend time in migration to check that all items in column NOT NULL **
14 ALTER TABLE ALTER COLUMN DROP NOT NULL X safe operation
15 ALTER TABLE ALTER COLUMN SET DEFAULT X safe operation
16 ALTER TABLE ALTER COLUMN DROP DEFAULT X safe operation
17 ALTER TABLE DROP COLUMN X safe operation, because you business logic shouldn't operate with this column on migration time, however better ALTER TABLE ALTER COLUMN DROP NOT NULL, ALTER TABLE DROP CONSTRAINT and DROP INDEX before * and *****
18 ALTER TABLE RENAME COLUMN new column and copy unsafe operation, it's too hard write business logic that operate with two columns simultaneously, so propose ALTER TABLE CREATE COLUMN and then copy all data to new column *
19 ALTER TABLE ADD CONSTRAINT CHECK add as not valid and validate unsafe operation, because you spend time in migration to check constraint
20 ALTER TABLE DROP CONSTRAINT (CHECK) X safe operation
21 ALTER TABLE ADD CONSTRAINT FOREIGN KEY add as not valid and validate unsafe operation, because you spend time in migration to check constraint, lock two tables
22 ALTER TABLE DROP CONSTRAINT (FOREIGN KEY) X safe operation, lock two tables
23 ALTER TABLE ADD CONSTRAINT PRIMARY KEY add index and add constraint unsafe operation, because you spend time in migration to create index ***
24 ALTER TABLE DROP CONSTRAINT (PRIMARY KEY) X safe operation ***
25 ALTER TABLE ADD CONSTRAINT UNIQUE add index and add constraint unsafe operation, because you spend time in migration to create index ***
26 ALTER TABLE DROP CONSTRAINT (UNIQUE) X safe operation ***
27 CREATE INDEX CREATE INDEX CONCURRENTLY unsafe operation, because you spend time in migration to create index
28 DROP INDEX X DROP INDEX CONCURRENTLY safe operation ***

*: main point with migration on production without downtime that your code should correctly work before and after migration, lets look this point closely below

**: postgres will check that all items in column NOT NULL that take time, lets look this point closely below

***: postgres will have same behaviour when you skip ALTER TABLE ADD CONSTRAINT UNIQUE USING INDEX and still unclear difference with CONCURRENTLY except difference in locks, lets look this point closely below

****: lets look this point closely below

*****: if you check migration on CI with python manage.py makemigrations --check you can't drop column in code without migration creation, so in this case you can be useful back migration flow: apply code on all instances and then migrate database

Dealing with logic that should work before and after migration

New and removing models and columns

Migrations: CREATE SEQUENCE, DROP SEQUENCE, CREATE TABLE, DROP TABLE, ALTER TABLE ADD COLUMN, ALTER TABLE DROP COLUMN.

This migrations are pretty safe, because your logic doesn't work with this data before migration

Changes for working logic

Migrations: ALTER TABLE RENAME TO, ALTER TABLE SET TABLESPACE, ALTER TABLE RENAME COLUMN.

For this migration too hard implement logic that will work correctly for all instances, so there are two ways to dealing with it:

  1. create new table/column, copy exist data, drop old table/column
  2. downtime
Create column with default

Migrations: ALTER TABLE ADD COLUMN SET DEFAULT.

Standard django's behaviour for creation column with default is populate all values with default. Django don't use database defaults permanently, so when you add new column with default django will create column with default and drop this default at once, eg. new default will come from django code. In this case you can have a gap when migration applied by not all instances has updated and at this moment new rows in table will be without default and probably you need update nullable values after that. So to avoid this case best way is avoid creation column with default and split column creation (with default for new rows) and data population to two migrations (with deployments).

Dealing with NOT NULL constraint

Postgres check that all column items NOT NULL when you applying NOT NULL constraint, unfortunately you can't defer this check as for NOT VALID. But we have some hacks and alternatives there.

  1. Run migrations when load minimal to avoid negative affect of locking.
  2. SET statement_timeout and try to set NOT NULL constraint for small tables.
  3. Use CHECK (column IS NOT NULL) constraint instead that support NOT VALID option with next VALIDATE CONSTRAINT, see article for details https://medium.com/doctolib-engineering/adding-a-not-null-constraint-on-pg-faster-with-minimal-locking-38b2c00c4d1c.

Dealing with UNIQUE constraint

Postgres has two approaches for uniqueness: CREATE UNIQUE INDEX and ALTER TABLE ADD CONSTRAINT UNIQUE - both use unique index inside. Difference that I see that you cannot apply DROP INDEX CONCURRENTLY for constraint. However still unclear what difference for DROP INDEX and DROP INDEX CONCURRENTLY except difference in locks, but as you see before both marked as safe - you don't spend time in DROP INDEX, just wait for lock. So as django use constraint for uniqueness we also have a hacks to use constraint safely.

Dealing with ALTER TABLE ALTER COLUMN TYPE

Next operations are safe:

  1. varchar(LESS) to varchar(MORE) where LESS < MORE
  2. varchar(ANY) to text
  3. numeric(LESS, SAME) to numeric(MORE, SAME) where LESS < MORE and SAME == SAME

For other operations propose to create new column and copy data to it. Eg. some types can be also safe, but you should check yourself.