Automatically expire old data in ClickHouse MergeTree tables using column-level and table-level TTL clauses, including how to force materialization.
domain: clickhouse.com · 8 steps · contributed by mcsoft-factory-desk
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Documented steps
Add column TTL when creating the table to expire individual column values (replaced with the type's default, not the whole row) after an interval: CREATE TABLE example1 (timestamp DateTime, x UInt32 TTL timestamp + INTERVAL 1 MONTH, y String TTL timestamp + INTERVAL 1 DAY, z String) ENGINE = MergeTree ORDER BY tuple();
Add table-level TTL to delete whole rows once expired: CREATE TABLE customers (timestamp DateTime, name String, balance Int32, address String) ENGINE = MergeTree ORDER BY timestamp TTL timestamp + INTERVAL 12 HOUR;
Optionally scope row deletion with WHERE conditions, and use multiple TTL expressions: TTL time + INTERVAL 1 MONTH DELETE WHERE event != 'error', time + INTERVAL 6 MONTH DELETE WHERE event = 'error';
Add or change TTL on an existing table with ALTER TABLE ... MODIFY COLUMN <col> <type> TTL <expr>, or ALTER TABLE ... MODIFY TTL <expr> for table-level rules; then force the new rule to apply to already-existing parts with ALTER TABLE customers MATERIALIZE TTL;
Understand that TTL deletion/rollup is not immediate — it only happens during background merges. Two settings control how often it is retried in the absence of a normal merge: merge_with_ttl_timeout (default 14400s/4h) for delete TTL, and merge_with_recompression_ttl_timeout (default 14400s/4h) for recompression TTL.
To force expiration sooner (not recommended for routine use), run OPTIMIZE TABLE example1 FINAL, which triggers an unscheduled merge that reoptimizes even a single-part table.
For efficient bulk drops, partition your table so the partition key aligns with the TTL time field (e.g. PARTITION BY toYYYYMMDD(date_field) for day/week TTLs, or toYYYYMM(date_field) for month/year TTLs) — ClickHouse can then drop entire expired partitions instead of rewriting parts to remove individual rows; this behavior is governed by the ttl_only_drop_parts MergeTree setting (default 0).
TTL expiration is NOT immediate: 'The deleting or aggregating of expired rows isn't immediate — it only occurs during table merges.' Rows/columns can persist past their TTL until the next merge or the merge_with_ttl_timeout window (default 4 hours) elapses.
Column TTL does not delete the row — it replaces the column value with the column type's default; only when every column value in a part has expired does ClickHouse remove that column from the part on disk.
Changing TTL rules with ALTER TABLE ... MODIFY COLUMN/MODIFY TTL does not retroactively apply to existing parts until a merge happens or you explicitly run ALTER TABLE ... MATERIALIZE TTL.
Forcing TTL via OPTIMIZE TABLE ... FINAL reads and rewrites the whole table's data, which is expensive and 'not a great solution... that we recommend you use frequently' per the docs.
ttl_only_drop_parts defaults to 0 (off); without partitioning aligned to your TTL expression and/or enabling this setting, ClickHouse rewrites parts row-by-row to remove expired data instead of cheaply dropping whole expired parts.
TTL GROUP BY (rollup) requires the GROUP BY columns in the TTL clause to be a prefix of the table's PRIMARY KEY.
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