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Query Cache

The query cache allows to compute SELECT queries just once and to serve further executions of the same query directly from the cache. Depending on the type of the queries, this can dramatically reduce latency and resource consumption of the ClickHouse server.

Background, Design and Limitations

Query caches can generally be viewed as transactionally consistent or inconsistent.

  • In transactionally consistent caches, the database invalidates (discards) cached query results if the result of the SELECT query changes or potentially changes. In ClickHouse, operations which change the data include inserts/updates/deletes in/of/from tables or collapsing merges. Transactionally consistent caching is especially suitable for OLTP databases, for example MySQL (which removed query cache after v8.0) and Oracle.
  • In transactionally inconsistent caches, slight inaccuracies in query results are accepted under the assumption that all cache entries are assigned a validity period after which they expire (e.g. 1 minute) and that the underlying data changes only little during this period. This approach is overall more suitable for OLAP databases. As an example where transactionally inconsistent caching is sufficient, consider an hourly sales report in a reporting tool which is simultaneously accessed by multiple users. Sales data changes typically slowly enough that the database only needs to compute the report once (represented by the first SELECT query). Further queries can be served directly from the query cache. In this example, a reasonable validity period could be 30 min.

Transactionally inconsistent caching is traditionally provided by client tools or proxy packages interacting with the database. As a result, the same caching logic and configuration is often duplicated. With ClickHouse's query cache, the caching logic moves to the server side. This reduces maintenance effort and avoids redundancy.

Configuration Settings and Usage

Setting use_query_cache can be used to control whether a specific query or all queries of the current session should utilize the query cache. For example, the first execution of query

SELECT some_expensive_calculation(column_1, column_2)
FROM table
SETTINGS use_query_cache = true;

will store the query result in the query cache. Subsequent executions of the same query (also with parameter use_query_cache = true) will read the computed result from the cache and return it immediately.


Setting use_query_cache and all other query-cache-related settings only take an effect on stand-alone SELECT statements. In particular, the results of SELECTs to views created by CREATE VIEW AS SELECT [...] SETTINGS use_query_cache = true are not cached unless the SELECT statement runs with SETTINGS use_query_cache = true.

The way the cache is utilized can be configured in more detail using settings enable_writes_to_query_cache and enable_reads_from_query_cache (both true by default). The former setting controls whether query results are stored in the cache, whereas the latter setting determines if the database should try to retrieve query results from the cache. For example, the following query will use the cache only passively, i.e. attempt to read from it but not store its result in it:

SELECT some_expensive_calculation(column_1, column_2)
FROM table
SETTINGS use_query_cache = true, enable_writes_to_query_cache = false;

For maximum control, it is generally recommended to provide settings "use_query_cache", "enable_writes_to_query_cache" and "enable_reads_from_query_cache" only with specific queries. It is also possible to enable caching at user or profile level (e.g. via SET use_query_cache = true) but one should keep in mind that all SELECT queries including monitoring or debugging queries to system tables may return cached results then.

The query cache can be cleared using statement SYSTEM DROP QUERY CACHE. The content of the query cache is displayed in system table system.query_cache. The number of query cache hits and misses since database start are shown as events "QueryCacheHits" and "QueryCacheMisses" in system table Both counters are only updated for SELECT queries which run with setting use_query_cache = true, other queries do not affect "QueryCacheMisses". Field query_log_usage in system table system.query_log shows for each executed query whether the query result was written into or read from the query cache. Asynchronous metrics "QueryCacheEntries" and "QueryCacheBytes" in system table system.asynchronous_metrics show how many entries / bytes the query cache currently contains.

The query cache exists once per ClickHouse server process. However, cache results are by default not shared between users. This can be changed (see below) but doing so is not recommended for security reasons.

Query results are referenced in the query cache by the Abstract Syntax Tree (AST) of their query. This means that caching is agnostic to upper/lowercase, for example SELECT 1 and select 1 are treated as the same query. To make the matching more natural, all query-level settings related to the query cache are removed from the AST.

If the query was aborted due to an exception or user cancellation, no entry is written into the query cache.

The size of the query cache in bytes, the maximum number of cache entries and the maximum size of individual cache entries (in bytes and in records) can be configured using different server configuration options.

It is also possible to limit the cache usage of individual users using settings profiles and settings constraints. More specifically, you can restrict the maximum amount of memory (in bytes) a user may allocate in the query cache and the the maximum number of stored query results. For that, first provide configurations query_cache_max_size_in_bytes and query_cache_max_entries in a user profile in users.xml, then make both settings readonly:

<!-- The maximum cache size in bytes for user/profile 'default' -->
<!-- The maximum number of SELECT query results stored in the cache for user/profile 'default' -->
<!-- Make both settings read-only so the user cannot change them -->

To define how long a query must run at least such that its result can be cached, you can use setting query_cache_min_query_duration. For example, the result of query

SELECT some_expensive_calculation(column_1, column_2)
FROM table
SETTINGS use_query_cache = true, query_cache_min_query_duration = 5000;

is only cached if the query runs longer than 5 seconds. It is also possible to specify how often a query needs to run until its result is cached - for that use setting query_cache_min_query_runs.

Entries in the query cache become stale after a certain time period (time-to-live). By default, this period is 60 seconds but a different value can be specified at session, profile or query level using setting query_cache_ttl.

Entries in the query cache are compressed by default. This reduces the overall memory consumption at the cost of slower writes into / reads from the query cache. To disable compression, use setting query_cache_compress_entries.

ClickHouse reads table data in blocks of max_block_size rows. Due to filtering, aggregation, etc., result blocks are typically much smaller than 'max_block_size' but there are also cases where they are much bigger. Setting query_cache_squash_partial_results (enabled by default) controls if result blocks are squashed (if they are tiny) or split (if they are large) into blocks of 'max_block_size' size before insertion into the query result cache. This reduces performance of writes into the query cache but improves compression rate of cache entries and provides more natural block granularity when query results are later served from the query cache.

As a result, the query cache stores for each query multiple (partial) result blocks. While this behavior is a good default, it can be suppressed using setting query_cache_squash_partial_results.

Also, results of queries with non-deterministic functions are not cached by default. Such functions include

Finally, entries in the query cache are not shared between users due to security reasons. For example, user A must not be able to bypass a row policy on a table by running the same query as another user B for whom no such policy exists. However, if necessary, cache entries can be marked accessible by other users (i.e. shared) by supplying setting query_cache_share_between_users.