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Clickhouse Migrations Agent Skill

ClickHouse migration patterns and rules. Use when creating or modifying ClickHouse migrations.

1k tokens
context cost
the whole folder, loaded on every use
1
files
instructions only
0
copies elsewhere
how many repositories repackaged it
690
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/PostHog/posthog --skill clickhouse-migrations

The instruction itself

9 sections, as written by the author

ClickHouse Migrations

Read posthog/clickhouse/migrations/AGENTS.md for comprehensive patterns, cluster setup, examples, and ingestion layer details.

Quick reference

Migration structure

operations = [
    run_sql_with_exceptions(
        SQL_FUNCTION(),
        node_roles=[...],
        sharded=False,  # True for sharded tables
        is_alter_on_replicated_table=False  # True for ALTER on replicated tables
    ),
]

Node roles (choose based on table type)

  • [NodeRole.DATA]: Sharded tables (data nodes only)
  • [NodeRole.DATA, NodeRole.COORDINATOR]: Non-sharded data tables, distributed read tables, replicated tables, views, dictionaries
  • [NodeRole.INGESTION_SMALL]: Writable tables, Kafka tables, materialized views on ingestion layer

Table engines quick reference

MergeTree engines:

  • AggregatingMergeTree(table, replication_scheme=ReplicationScheme.SHARDED) for sharded tables
  • ReplacingMergeTree(table, replication_scheme=ReplicationScheme.REPLICATED) for non-sharded
  • Other variants: CollapsingMergeTree, ReplacingMergeTreeDeleted

Distributed engine:

  • Sharded: Distributed(data_table="sharded_events", sharding_key="sipHash64(person_id)")
  • Non-sharded: Distributed(data_table="my_table", cluster=settings.CLICKHOUSE_SINGLE_SHARD_CLUSTER)

Critical rules

  • NEVER use ON CLUSTER clause in SQL statements
  • Always use IF EXISTS / IF NOT EXISTS clauses
  • When dropping and recreating replicated table in same migration, use DROP TABLE IF EXISTS ... SYNC
  • If a function generating SQL has on_cluster param, always set on_cluster=False
  • Use sharded=True when altering sharded tables
  • Use is_alter_on_replicated_table=True when altering non-sharded replicated tables
  • Never write a DROP COLUMN migration yourselfDROP COLUMN can get stuck in ClickHouse and block releases. Column removal is a two-step process: (1) the ClickHouse team drops the column directly on the cluster, then (2) you write a migration with the matching DROP COLUMN so the codebase schema stays in sync. Never initiate the drop from a migration without the ClickHouse team having done step 1 first.
  • Never drop or recreate kafka_events_json_ws or events_json_ws_mv — these tables are a no-go zone. The MV definition differs significantly between US prod, EU prod, and dev (dozens of environment-specific mat_* columns) and those differences are not reflected in the repo. Dropping and recreating from repo SQL would destroy the environment-specific schema and break event ingestion. Any change must go through the ClickHouse team.

PR scope

A PR that contains a ClickHouse migration must be migration-only. Do not mix migration files with feature code, API changes, model changes, or frontend changes in the same PR. Migration-related files are:

  • The migration file itself (posthog/clickhouse/migrations/0NNN_*.py)
  • SQL definition files the migration depends on (e.g. posthog/clickhouse/sql/*.py, table engine helpers)
  • Tests that directly exercise the migration or the SQL definitions it touches

If you need both a schema change and application code that uses the new schema, ship the migration first in its own PR and merge it before the application-code PR.

Local setup parity

No table should exist only in the cloud. Every table created via migration must also exist in a local dev environment.

Some migrations are cloud-guarded and skipped in local/hobby dev:

operations = (
    []
    if settings.CLOUD_DEPLOYMENT not in ("US", "EU", "DEV")
    else [...]
)

If you create a new table inside such a guard, you must also add its SQL function to posthog/clickhouse/schema.py in the appropriate tuple so the table gets created locally:

| Table type | Tuple in schema.py |

| ---------------------- | ---------------------------------- |

| MergeTree / base table | CREATE_MERGETREE_TABLE_QUERIES |

| Distributed / writable | CREATE_DISTRIBUTED_TABLE_QUERIES |

| Kafka consumer | CREATE_KAFKA_TABLE_QUERIES |

| Materialized view | CREATE_MV_TABLE_QUERIES |

| Non-materialized view | CREATE_VIEW_QUERIES |

| Dictionary | CREATE_DICTIONARY_QUERIES |

The only exception is tables whose definition intentionally differs per environment and is not tracked in the repo (e.g. the no-go zone events_json_ws_mv table).

Dictionary credentials: when a dictionary uses a SOURCE(CLICKHOUSE(...)), resolve the source user/password via get_clickhouse_creds(ClickHouseUser.DICT_READER) and interpolate them into the USER/PASSWORD clause — do not hardcode default/CLICKHOUSE_USER or omit credentials. This keeps dictionary auth on the dedicated low-privilege dict_reader user, decoupled from default; it falls back to default creds when the env vars are unset. See posthog/models/exchange_rate/sql.py for the pattern.

Testing

Delete entry from infi_clickhouse_orm_migrations table to re-run a migration.

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How to use it

Copy the folder

Take posthog/clickhouse-migrations from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

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