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Error 48: NOT_IMPLEMENTED

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This error occurs when you attempt to use a feature, function, or operation that is not implemented in your ClickHouse version, not supported for your specific table engine or configuration, or requires enabling experimental settings to use.

Most common causes​

  1. Table engine limitations

    • ALTER operations not supported on specific table engines (View, Memory, File, URL tables)
    • Mutations (UPDATE/DELETE) not available for certain engines
    • OPTIMIZE or other maintenance operations unavailable for read-only or external engines
    • Missing replication features on non-Replicated table engines

  2. Experimental or preview features not enabled

    • An experimental or beta feature has not been enabled through a setting
    • The feature is not yet available in ClickHouse Cloud
    • The feature is in private preview and access needs to be provided by Cloud support

  3. Version-specific features

    • Using features from newer ClickHouse versions on older installations
    • Functions or syntax not backported to your version
    • Cloud vs self-managed feature differences
    • Deprecated features removed in newer versions

  4. Data type or operation incompatibilities

    • Operations not supported for specific data types (Array, Map, Tuple operations)
    • Type conversions that don't have implementations
    • Mathematical operations on incompatible types
    • Special column operations (ephemeral, alias columns)

  5. Distributed and replicated table limitations

    • Certain ALTER operations not supported on Distributed tables
    • Global joins or subqueries not fully implemented
    • Cross-cluster operations with limited support
    • Replication features unavailable in standalone mode

  6. Storage and integration limitations

    • S3/HDFS operations not fully implemented
    • Table function limitations (URL, S3, MySQL, PostgreSQL engines)
    • Backup/restore operations unavailable for certain engines
    • External dictionary refresh operations not supported

Common solutions​

1. Enable required experimental settings

-- Error: Window functions not available (older versions)
SELECT 
    user_id,
    row_number() OVER (PARTITION BY user_id ORDER BY timestamp) as rn
FROM events;

-- Solution: Enable experimental window functions (< v21.12)
SET allow_experimental_window_functions = 1;

SELECT 
    user_id,
    row_number() OVER (PARTITION BY user_id ORDER BY timestamp) as rn
FROM events;
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See "Beta and experimental features" page for a list of experimental and beta flags.

2. Use supported table engine for operations

-- Error: Cannot ALTER a View table
ALTER TABLE my_view ADD COLUMN new_column String;

-- Solution: ALTER the underlying table instead
ALTER TABLE underlying_table ADD COLUMN new_column String;

-- Then recreate the view if needed
CREATE OR REPLACE VIEW my_view AS
SELECT *, new_column
FROM underlying_table;

3. Switch from non-replicated to Replicated table engine

-- Error: Replication features not available on MergeTree
-- Operations like SYNC REPLICA, FETCH PARTITION fail

-- Solution: Migrate to ReplicatedMergeTree
CREATE TABLE new_table
(
    date Date,
    user_id UInt64,
    value Float64
)
ENGINE = ReplicatedMergeTree('/clickhouse/tables/{shard}/new_table', '{replica}')
PARTITION BY toYYYYMM(date)
ORDER BY (date, user_id);

-- Migrate data
INSERT INTO new_table SELECT * FROM old_table;

-- Rename tables
RENAME TABLE old_table TO old_table_backup, new_table TO old_table;

4. Upgrade ClickHouse version for newer features

-- Error: Feature not implemented in version 21.3
SELECT quantileTDigestWeighted(0.95)(response_time, weight) FROM requests;

-- Solution: Upgrade to version 21.8+ or use alternative
-- Alternative for older versions:
SELECT quantileWeighted(0.95)(response_time, weight) FROM requests;

-- Or upgrade ClickHouse:
-- Check current version
SELECT version();

-- Plan upgrade to newer version with required features

6. Work around Distributed table limitations

-- Error: ALTER on Distributed table not fully supported
ALTER TABLE distributed_table DROP COLUMN old_column;

-- Solution: ALTER each underlying shard table
-- On each shard:
ALTER TABLE local_table DROP COLUMN old_column;

-- Recreate Distributed table if needed
DROP TABLE distributed_table;
CREATE TABLE distributed_table AS local_table
ENGINE = Distributed(cluster_name, database_name, local_table, rand());

7. Use supported operations for external table engines

-- Error: OPTIMIZE not supported for URL table engine
OPTIMIZE TABLE url_table FINAL;

-- Solution: For URL/File/external engines, recreate or use appropriate engine
-- If you need optimization, import to MergeTree first:
CREATE TABLE local_copy ENGINE = MergeTree() ORDER BY id AS
SELECT * FROM url_table;

OPTIMIZE TABLE local_copy FINAL;

8. Enable ClickHouse Cloud preview features

-- Error: Feature not available in ClickHouse Cloud
-- Check if feature requires enablement

-- Solution: Contact support or check Cloud console for preview features
-- Some features need to be enabled via Cloud console settings
-- Example: Advanced compute-compute separation, certain integrations

-- Alternatively, use feature flags in query settings:
SET allow_experimental_analyzer = 1;
SET enable_optimize_predicate_expression = 1;

SELECT * FROM table WHERE complex_condition;

Prevention tips​

  1. Check compatibility before using new features: Review ClickHouse release notes and documentation to verify feature availability in your version and deployment type (Cloud vs self-managed)
  2. Choose appropriate table engines: Select table engines that support the operations you need (use ReplicatedMergeTree for replication, MergeTree family for mutations, etc.)
  3. Test experimental features in development first: Always test experimental features in non-production environments before enabling in production, and monitor ClickHouse changelogs for when features become stable
  4. Keep ClickHouse versions updated: Regularly upgrade to newer ClickHouse versions to access new features and improvements, following a testing → staging → production upgrade path
  5. Use Cloud-compatible patterns: When using ClickHouse Cloud, design queries and schemas using features documented as Cloud-compatible to avoid surprises
  6. Review engine-specific limitations: Before choosing a table engine, review its documentation for supported and unsupported operations (especially for Kafka, MaterializedView, Distributed engines)
  7. Monitor deprecation warnings: Pay attention to deprecation notices in release notes to avoid using features that may be removed in future versions
  8. Use alternative implementations: When a specific operation isn't implemented, look for alternative approaches using supported features (e.g., using INSERT INTO SELECT instead of UPDATE)