This document discusses strategies for shrinking production databases to use in test and development environments. It presents a case study of how Paperless Post creates a composite slice of their production data including application schemas, static content tables, a subset of user data, and mutated email addresses. The strategies allow for daily fresh data while protecting sensitive information and limiting resource usage on non-production machines.

1. Honey, I Shrunk the DatabaseFor Test and Development EnvironmentsVanessa HurstPaperless PostPostgres Open, September 2011

3. User Data

4. Why Shrink?AccuracyYou don’t truly know how your app will behave in production unless you use real data.Production data is the ultimate in accuracy.

5. Why Shrink?AccuracyFreshnessNew data should be available regularly.Full database refreshes should be timely.

6. Why Shrink?AccuracyFreshnessResource LimitationsStaging and developer machines cannot handle production load.

7. Why Shrink?AccuracyFreshnessResource LimitationsData ProtectionLimit spread of sensitive user or client data.

8. Why Shrink?AccuracyFreshnessResource LimitationsData Protection

9. Case Study: Paperless PostRequirementsFreshness – Daily, On command for non-developersShrinkage – Slices, Mutations

10. Case Study: Paperless PostRequirementsFreshness – Daily, On command for non-developersShrinkage – Slices, MutationsResourcesSource – extra disk space, RAM, and CPUsDestination – limited, often entirely un-optimizedDevelopment -- constrained DBA resources

11. Shrink StrategiesCopiesRestored backups or live replicas of entire production database

12. Shrink StrategiesCopiesSlicesSelect portions of exact data

13. Shrink StrategiesCopiesSlicesMutationsSanitized, anonymized, or otherwise changed data

14. Shrink StrategiesCopiesSlicesMutationsAssumptionsSeed databases, fixtures, test data

15. Shrink StrategiesCopiesSlicesMutationsAssumptions

16. SlicesVertical SliceDifficult to obtain a valid, useful subset of data.Example: Include some entire tables, exclude others

17. SlicesVertical SliceDifficult to obtain a valid, useful subset of data.Example: Include some entire tables, exclude othersHorizontal SliceDifficult to write and maintain.Example: SQL or application code to determine subset of data

18. PG Tools – Vertical SliceFlexibility at Source (Production)pg_dumpInclude data only [-a --data-only]Include table schema only [-s --schema-only]Select tables [-t table1 table2 --table table1 table2]Select schemas [-nschema --schema=schema]Exclude schemas [-N schema --exclude-schema=schema]

19. PG Tools – Vertical SliceFlexibility at Destination (Staging, Development)pg_restoreInclude data only [-a --data-only]Select indexes [-iindex --index=index]Tune processing [-jnumber-of-jobs --jobs=number-of-jobs]Select schemas [-nschema --schema=schema]Select triggers[-T trigger --trigger=trigger]Exclude privileges [-x --no-privileges --no-acl]

21. MutationsExternal Data ProtectionHIPAA RegulationsPCI ComplianceAPI Terms of Use

22. MutationsExternal Data ProtectionHIPAA RegulationsPCI ComplianceAPI Terms of UseInternal Data ProtectionProtecting your users’ personal dataProtecting your users from accidents, e.g. staging emailsYour Terms of Service

23. User Data

24. Case Study: Paperless PostComposite Slice includingVertical Slice – All application object schemasVertical Slice – Entire tables of static contentHorizontal Slice – Subset of users and their dataMutation – Changed user email addresses

25. Case Study: Paperless PostComposite Slice includingVertical Slice – All application object schemaspg_dump --clean --schema-only --schema public db-01 > slice.sql

26. Case Study: Paperless PostComposite Slice includingVertical Slice – All application object schemaspg_dump --clean --schema-only --schema public db-01 > slice.sqlVertical Slice – Entire tables of static contentpg_dump --data-only --schema public -t cards db-01 >> slice.sql

27. Case Study: Paperless PostComposite Slice includingVertical Slice – All application object schemaspg_dump --clean --schema-only --schema public db-01 > slice.sqlVertical Slice – Entire tables of static contentpg_dump --data-only --schema public -t cards db-01 >> slice.sql Horizontal Slice – Subset of users and their dataMutation – Changed user email addresses

28. Case Study: Paperless PostCREATE SCHEMA staging;

29. Case Study: Paperless PostHorizontal SliceCustom SQLSELECT * INTO staging.usersFROM usersWHERE EXISTS (subset of users);

30. Case Study: Paperless PostHorizontal SliceCustom SQLSELECT * INTO staging.usersFROM usersWHERE EXISTS (subset of users);Dynamic relative to full data set or newly created sliceSELECT * INTO staging.stuffFROM stuffWHERE EXISTS (stuff per staging.users);

31. Case Study: Paperless PostHorizontal SliceCustom SQLDynamic relative to full data set or newly created sliceMutationsEmail AddressesUse regular expressions to clean non-admin addressese.g. dude@gmail.com => staging+dudegmailcom@paperlesspost.comCached DataClear cached short link from link-shortening API

32. Case Study: Paperless PostComposite Slice includingVertical Slice – All application object schemaspg_dump --clean --schema-only --schema public db-01 > slice.sqlVertical Slice – Entire tables of static contentpg_dump --data-only --schema public -t cards db-01 >> slice.sql Horizontal Slice – Subset of users and their dataMutation – Changed user email addressespg_dump --data-only --schema staging db-01 >> slice.sql

33. Case Study: Paperless PostRebuildPrepare new database as standbyGracefully close connectionsRotate by renaming databasesSecurity Dedicated database build userMembership in application user roleApplication user role & privileges remain

34. Case Study: Paperless PostRebuild$ bzcat slice.sql.bz2 | psql db-newStaging schema has not been created, so all data loads to default schema

35. Case Study: Paperless PostWe hacked our rebuild by importing across schemas!Now our sequences are wrong, causing duplicate data errors every time we try to insert into tables.

36. Secret Weapon --Updates all serial sequences for ID columns onlyBEGINFOR table_record IN SELECT pc.relname FROM pg_class pc WHERE pc.relkind = 'r' AND EXISTS (SELECT 1 FROM pg_attribute pa WHERE pa.attname = 'id' AND pa.attrelid = pc.oid) LOOPtable_name = table_record.relname::text; EXECUTE 'SELECT setval(pg_get_serial_sequence(' || quote_literal(table_name) || ', ' || quote_literal('id')::text || '), MAX(id)) FROM ' || table_name || ' WHERE EXISTS (SELECT 1 FROM ' || table_name || ')';END LOOP;

37. Case Study: Paperless PostRebuild$ bzcat slice.sql.bz2 | psql db-newStaging schema has not been created, so all data loads to default schemaecho “select 1 from update_id_sequences();” >> slice.sqlVacuumReindex

38. Case Study: Paperless PostSecurity Database build userCREATE DB privilegesMember of Application user roleApplication user remains database ownerApplication user privileges remain limitedBuild only works in predetermined environments

39. Case Study: Paperless PostRequirementsFreshness – Daily, On command for non-developersShrinkage – Slices, MutationsResourcesSource – extra disk space, RAM, and CPUsDestination – limited, often entirely un-optimizedDevelopment -- constrained DBA resources

40. Questions?Vanessa HurstPaperless Post@DBNessPostgres Open, September 2011

41. More ToolsCopies -- LVMSnapshotsSee talk by Jon Erdman at PG Conf EUGreat for all readsData stays virtualized & doesn’t take up space until changedIdeal for DDL changes without actual data changes

42. More ToolsCopies, Slices-- pg_staging by dmitrihttp://github.com/dimitri/pg_stagingSimple -- pauses pgbouncer & restores backupEfficient -- leverage bulk loadingFlexible -- supports varying psql filesCustom -- limitedSlices -- replicate by rtomayko of Github http://github.com/rtomayko/replicateSimple - Preserves object relations via ActiveRecordInefficient -- Creates text-based .dumpInflexible -- Corrupts id sequences on data insertCustom -- highly