ClickHouse checks the restrictions for data parts, not for each row. It means that you can exceed the value of restriction with the 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_server_memory_usage](../../operations/server-configuration-parameters/settings.md#max_server_memory_usage).
Default values are defined in [Settings.h](https://github.com/ClickHouse/ClickHouse/blob/master/src/Core/Settings.h#L288). By default, the amount is not restricted (`max_memory_usage_for_user = 0`).
Enables or disables execution of `GROUP BY` clauses in external memory. See [GROUP BY in external memory](../../sql-reference/statements/select/group-by.md#select-group-by-in-external-memory).
- Maximum volume of RAM (in bytes) that can be used by the single [GROUP BY](../../sql-reference/statements/select/group-by.md#select-group-by-clause) operation.
Enables or disables execution of `ORDER BY` clauses in external memory. See [ORDER BY Implementation Details](../../sql-reference/statements/select/order-by.md#implementation-details)
- Maximum volume of RAM (in bytes) that can be used by the single [ORDER BY](../../sql-reference/statements/select/order-by.md) operation. Recommended value is half of available system memory
Using ‘break’ is similar to using LIMIT. `Break` interrupts execution only at the block level. This means that amount of returned rows is greater than [max_result_rows](#setting-max_result_rows), multiple of [max_block_size](../../operations/settings/settings.md#setting-max_block_size) and depends on [max_threads](../../operations/settings/settings.md#settings-max_threads).
It operates based on interpolation relative to the current query execution speed (this behaviour is controlled by [timeout_before_checking_execution_speed](#timeout-before-checking-execution-speed)).
By default, the timeout_before_checking_execution_speed is set to 10 seconds. This means that after 10 seconds of query execution, ClickHouse will begin estimating the total execution time.
If, for example, `max_execution_time` is set to 3600 seconds (1 hour), ClickHouse will terminate the query if the estimated time exceeds this 3600-second limit.
What to do if the query is run longer than `max_execution_time`: `throw` or `break`. By default, `throw`.
# max_execution_time_leaf
Similar semantic to `max_execution_time` but only apply on leaf node for distributed or remote queries.
For example, if we want to limit execution time on leaf node to `10s` but no limit on the initial node, instead of having `max_execution_time` in the nested subquery settings:
``` sql
SELECT count() FROM cluster(cluster, view(SELECT * FROM t SETTINGS max_execution_time = 10));
```
We can use `max_execution_time_leaf` as the query settings:
``` sql
SELECT count() FROM cluster(cluster, view(SELECT * FROM t)) SETTINGS max_execution_time_leaf = 10;
```
# timeout_overflow_mode_leaf
What to do when the query in leaf node run longer than `max_execution_time_leaf`: `throw` or `break`. By default, `throw`.
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.
A 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.
A 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.
A 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.
A 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.
A 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.
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](../../sql-reference/statements/select/join.md#select-join) operations and the [Join](../../engines/table-engines/special/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.
This setting applies to [SELECT … JOIN](../../sql-reference/statements/select/join.md#select-join) operations and [Join table engine](../../engines/table-engines/special/join.md).
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 either logs a warning or throws an exception based on `throw_on_max_partitions_per_insert_block`. Exceptions have the following text:
> “Too many partitions for a single INSERT block (`partitions_count` partitions, limit is ” + toString(max_partitions) + “). The limit is controlled by the ‘max_partitions_per_insert_block’ setting. A 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).”