Almost all the restrictions only apply to `SELECT`. For distributed query processing, restrictions are applied on each server separately.
ClickHouse checks the restrictions for data parts, not for each row. It means that you can exceed the value of restriction with a size of the data part.
Memory usage is not monitored for the states of certain aggregate functions.
Memory usage is not fully tracked for states of the aggregate functions `min`, `max`, `any`, `anyLast`, `argMin`, `argMax` from `String` and `Array` arguments.
Memory consumption is also restricted by the parameters `max_memory_usage_for_user` and `max_memory_usage_for_all_queries`.
## max_memory_usage_for_user
The maximum amount of RAM to use for running a user's queries on a single server.
Default values are defined in [Settings.h](https://github.com/ClickHouse/ClickHouse/blob/master/dbms/src/Core/Settings.h#L288). By default, the amount is not restricted (`max_memory_usage_for_user = 0`).
Default values are defined in [Settings.h](https://github.com/ClickHouse/ClickHouse/blob/master/dbms/src/Core/Settings.h#L289). By default, the amount is not restricted (`max_memory_usage_for_all_queries = 0`).
Enables or disables execution of `GROUP BY` clauses in external memory. See [GROUP BY in external memory](../../query_language/select.md#select-group-by-in-external-memory).
Minimal execution speed in rows per second. Checked on every data block when 'timeout_before_checking_execution_speed' expires. If the execution speed is lower, an exception is thrown.
Minimum number of execution bytes per second. Checked on every data block when 'timeout_before_checking_execution_speed' expires. If the execution speed is lower, an exception is thrown.
## max_execution_speed
Maximum number of execution rows per second. Checked on every data block when 'timeout_before_checking_execution_speed' expires. If the execution speed is high, the execution speed will be reduced.
Maximum number of execution bytes per second. Checked on every data block when 'timeout_before_checking_execution_speed' expires. If the execution speed is high, the execution speed will be reduced.
Maximum number of columns that can be read from a table in a single query. If a query requires reading a greater number of columns, it throws an exception.
Maximum number of temporary columns that must be kept in RAM at the same time when running a query, including constant columns. If there are more temporary columns than this, it throws an exception.
Maximum pipeline depth. Corresponds to the number of transformations that each data block goes through during query processing. Counted within the limits of a single server. If the pipeline depth is greater, an exception is thrown. By default, 1000.
Maximum nesting depth of a query syntactic tree. If exceeded, an exception is thrown.
At this time, it isn't checked during parsing, but only after parsing the query. That is, a syntactic tree that is too deep can be created during parsing, but the query will fail. By default, 1000.
This settings applies to [SELECT ... JOIN](../../query_language/select.md#select-join) operations and the [Join](../table_engines/join.md) table engine.
ClickHouse can proceed with different actions when the limit is reached. Use the [join_overflow_mode](#settings-join_overflow_mode) setting to choose the action.
ClickHouse can proceed with different actions when the limit is reached. Use [join_overflow_mode](#settings-join_overflow_mode) settings to choose the action.
When inserting data, ClickHouse calculates the number of partitions in the inserted block. If the number of partitions is more than `max_partitions_per_insert_block`, ClickHouse throws an exception with the following text:
> "Too many partitions for single INSERT block (more than " + toString(max_parts) + "). The limit is controlled by 'max_partitions_per_insert_block' setting. Large number of partitions is a common misconception. It will lead to severe negative performance impact, including slow server startup, slow INSERT queries and slow SELECT queries. Recommended total number of partitions for a table is under 1000..10000. Please note, that partitioning is not intended to speed up SELECT queries (ORDER BY key is sufficient to make range queries fast). Partitions are intended for data manipulation (DROP PARTITION, etc)."