Maximum number of data rows between the marks of an index.
Default value: 8192.
## index_granularity_bytes
Maximum size of data granules in bytes.
Default value: 10Mb.
To restrict the granule size only by number of rows, set to 0 (not recommended).
## min_index_granularity_bytes
Min allowed size of data granules in bytes.
Default value: 1024b.
To provide a safeguard against accidentally creating tables with very low index_granularity_bytes.
## enable_mixed_granularity_parts
Enables or disables transitioning to control the granule size with the `index_granularity_bytes` setting. Before version 19.11, there was only the `index_granularity` setting for restricting granule size. The `index_granularity_bytes` setting improves ClickHouse performance when selecting data from tables with big rows (tens and hundreds of megabytes). If you have tables with big rows, you can enable this setting for the tables to improve the efficiency of `SELECT` queries.
## use_minimalistic_part_header_in_zookeeper
Storage method of the data parts headers in ZooKeeper. If enabled, ZooKeeper stores less data. For details, see [here](../server-configuration-parameters/settings.md/#server-settings-use_minimalistic_part_header_in_zookeeper).
## min_merge_bytes_to_use_direct_io
The minimum data volume for merge operation that is required for using direct I/O access to the storage disk.
When merging data parts, ClickHouse calculates the total storage volume of all the data to be merged.
If the volume exceeds `min_merge_bytes_to_use_direct_io` bytes, ClickHouse reads and writes the data to the storage disk using the direct I/O interface (`O_DIRECT` option).
If `min_merge_bytes_to_use_direct_io = 0`, then direct I/O is disabled.
Default value: `10 * 1024 * 1024 * 1024` bytes.
## merge_with_ttl_timeout
Minimum delay in seconds before repeating a merge with delete TTL.
Default value: `14400` seconds (4 hours).
## merge_with_recompression_ttl_timeout
Minimum delay in seconds before repeating a merge with recompression TTL.
Default value: `14400` seconds (4 hours).
## write_final_mark
Enables or disables writing the final index mark at the end of data part (after the last byte).
Default value: 1.
Don’t change or bad things will happen.
## storage_policy
Storage policy.
## min_bytes_for_wide_part
Minimum number of bytes/rows in a data part that can be stored in `Wide` format.
You can set one, both or none of these settings.
## max_compress_block_size
Maximum size of blocks of uncompressed data before compressing for writing to a table.
You can also specify this setting in the global settings (see [max_compress_block_size](/docs/en/operations/settings/settings.md/#max-compress-block-size) setting).
The value specified when table is created overrides the global value for this setting.
## min_compress_block_size
Minimum size of blocks of uncompressed data required for compression when writing the next mark.
You can also specify this setting in the global settings (see [min_compress_block_size](/docs/en/operations/settings/settings.md/#min-compress-block-size) setting).
The value specified when table is created overrides the global value for this setting.
## max_partitions_to_read
Limits the maximum number of partitions that can be accessed in one query.
You can also specify setting [max_partitions_to_read](/docs/en/operations/settings/merge-tree-settings.md/#max-partitions-to-read) in the global setting.
## max_suspicious_broken_parts
If the number of broken parts in a single partition exceeds the `max_suspicious_broken_parts` value, automatic deletion is denied.
If the number of active parts in a single partition exceeds the `parts_to_throw_insert` value, `INSERT` is interrupted with the `Too many parts (N). Merges are processing significantly slower than inserts` exception.
To achieve maximum performance of `SELECT` queries, it is necessary to minimize the number of parts processed, see [Merge Tree](../../development/architecture.md#merge-tree).
Prior to 23.6 this setting was set to 300. You can set a higher different value, it will reduce the probability of the `Too many parts` error, but at the same time `SELECT` performance might degrade. Also in case of a merge issue (for example, due to insufficient disk space) you will notice it later than it could be with the original 300.
If the number of inactive parts in a single partition more than the `inactive_parts_to_throw_insert` value, `INSERT` is interrupted with the "Too many inactive parts (N). Parts cleaning are processing significantly slower than inserts" exception.
If the number of inactive parts in a single partition in the table at least that many the `inactive_parts_to_delay_insert` value, an `INSERT` artificially slows down. It is useful when a server fails to clean up parts quickly enough.
The value in seconds, which is used to calculate the `INSERT` delay, if the number of active parts in a single partition exceeds the [parts_to_delay_insert](#parts-to-delay-insert) value.
For example, if a partition has 299 active parts and parts_to_throw_insert = 300, parts_to_delay_insert = 150, max_delay_to_insert = 1, `INSERT` is delayed for `pow( 1 * 1000, (1 + 299 - 150) / (300 - 150) ) = 1000` milliseconds.
For example, if a partition has 224 active parts and parts_to_throw_insert = 300, parts_to_delay_insert = 150, max_delay_to_insert = 1, min_delay_to_insert_ms = 10, `INSERT` is delayed for `max( 10, 1 * 1000 * (224 - 150 + 1) / (300 - 150) ) = 500` milliseconds.
If the total number of active parts in all partitions of a table exceeds the `max_parts_in_total` value `INSERT` is interrupted with the `Too many parts (N)` exception.
A large number of parts in a table reduces performance of ClickHouse queries and increases ClickHouse boot time. Most often this is a consequence of an incorrect design (mistakes when choosing a partitioning strategy - too small partitions).
The `Insert` command creates one or more blocks (parts). For [insert deduplication](../../engines/table-engines/mergetree-family/replication.md), when writing into replicated tables, ClickHouse writes the hash sums of the created parts into ClickHouse Keeper. Hash sums are stored only for the most recent `replicated_deduplication_window` blocks. The oldest hash sums are removed from ClickHouse Keeper.
The number of the most recently inserted blocks in the non-replicated [MergeTree](../../engines/table-engines/mergetree-family/mergetree.md) table for which hash sums are stored to check for duplicates.
A deduplication mechanism is used, similar to replicated tables (see [replicated_deduplication_window](#replicated-deduplication-window) setting). The hash sums of the created parts are written to a local file on a disk.
Similar to [replicated_deduplication_window](#replicated-deduplication-window), `replicated_deduplication_window_seconds` specifies how long to store hash sums of blocks for insert deduplication. Hash sums older than `replicated_deduplication_window_seconds` are removed from ClickHouse Keeper, even if they are less than ` replicated_deduplication_window`.
The [Async Insert](./settings.md#async-insert) command will be cached in one or more blocks (parts). For [insert deduplication](../../engines/table-engines/mergetree-family/replication.md), when writing into replicated tables, ClickHouse writes the hash sums of each insert into ClickHouse Keeper. Hash sums are stored only for the most recent `replicated_deduplication_window_for_async_inserts` blocks. The oldest hash sums are removed from ClickHouse Keeper.
Similar to [replicated_deduplication_window_for_async_inserts](#replicated-deduplication-window-for-async-inserts), `replicated_deduplication_window_seconds_for_async_inserts` specifies how long to store hash sums of blocks for async insert deduplication. Hash sums older than `replicated_deduplication_window_seconds_for_async_inserts` are removed from ClickHouse Keeper, even if they are less than ` replicated_deduplication_window_for_async_inserts`.
The time is relative to the time of the most recent record, not to the wall time. If it's the only record it will be stored forever.
A block bearing multiple async inserts will generate multiple hash sums. When some of the inserts are duplicated, keeper will only return one duplicated hash sum in one RPC, which will cause unnecessary RPC retries. This cache will watch the hash sums path in Keeper. If updates are watched in the Keeper, the cache will update as soon as possible, so that we are able to filter the duplicated inserts in the memory.
Normally, the `use_async_block_ids_cache` updates as soon as there are updates in the watching keeper path. However, the cache updates might be too frequent and become a heavy burden. This minimum interval prevents the cache from updating too fast. Note that if we set this value too long, the block with duplicated inserts will have a longer retry time.
Keep about this number of last records in ZooKeeper log, even if they are obsolete. It doesn't affect work of tables: used only to diagnose ZooKeeper log before cleaning.
If the time passed since a replication log (ClickHouse Keeper or ZooKeeper) entry creation exceeds this threshold, and the sum of the size of parts is greater than `prefer_fetch_merged_part_size_threshold`, then prefer fetching merged part from a replica instead of doing merge locally. This is to speed up very long merges.
If the sum of the size of parts exceeds this threshold and the time since a replication log entry creation is greater than `prefer_fetch_merged_part_time_threshold`, then prefer fetching merged part from a replica instead of doing merge locally. This is to speed up very long merges.
When this setting has a value greater than zero, only a single replica starts the merge immediately, and other replicas wait up to that amount of time to download the result instead of doing merges locally. If the chosen replica doesn't finish the merge during that amount of time, fallback to standard behavior happens.
When this setting has a value greater than zero only a single replica starts the merge immediately if merged part on shared storage and `allow_remote_fs_zero_copy_replication` is enabled.
Timeout (in seconds) before starting merge with recompression. During this time ClickHouse tries to fetch recompressed part from replica which assigned this merge with recompression.
Recompression works slow in most cases, so we don't start merge with recompression until this timeout and trying to fetch recompressed part from replica which assigned this merge with recompression.
HTTP connection timeout (in seconds) for part fetch requests. Inherited from default profile [http_connection_timeout](./settings.md#http_connection_timeout) if not set explicitly.
HTTP send timeout (in seconds) for part fetch requests. Inherited from default profile [http_send_timeout](./settings.md#http_send_timeout) if not set explicitly.
HTTP receive timeout (in seconds) for fetch part requests. Inherited from default profile [http_receive_timeout](./settings.md#http_receive_timeout) if not set explicitly.
Limits the maximum speed of data exchange over the network in bytes per second for [replicated](../../engines/table-engines/mergetree-family/replication.md) fetches. This setting is applied to a particular table, unlike the [max_replicated_fetches_network_bandwidth_for_server](settings.md#max_replicated_fetches_network_bandwidth_for_server) setting, which is applied to the server.
You can limit both server network and network for a particular table, but for this the value of the table-level setting should be less than server-level one. Otherwise the server considers only the `max_replicated_fetches_network_bandwidth_for_server` setting.
Limits the maximum speed of data exchange over the network in bytes per second for [replicated](../../engines/table-engines/mergetree-family/replication.md) sends. This setting is applied to a particular table, unlike the [max_replicated_sends_network_bandwidth_for_server](settings.md#max_replicated_sends_network_bandwidth_for_server) setting, which is applied to the server.
You can limit both server network and network for a particular table, but for this the value of the table-level setting should be less than server-level one. Otherwise the server considers only the `max_replicated_sends_network_bandwidth_for_server` setting.
`fsync` is not called for new parts, so for some time new parts exist only in the server's RAM (OS cache). If the server is rebooted spontaneously, new parts can be lost or damaged.
To protect data inactive parts are not deleted immediately.
During startup ClickHouse checks the integrity of the parts.
If the merged part is damaged ClickHouse returns the inactive parts to the active list, and later merges them again. Then the damaged part is renamed (the `broken_` prefix is added) and moved to the `detached` folder.
If the merged part is not damaged, then the original inactive parts are renamed (the `ignored_` prefix is added) and moved to the `detached` folder.
The default `dirty_expire_centisecs` value (a Linux kernel setting) is 30 seconds (the maximum time that written data is stored only in RAM), but under heavy loads on the disk system data can be written much later. Experimentally, a value of 480 seconds was chosen for `old_parts_lifetime`, during which a new part is guaranteed to be written to disk.
The merge scheduler periodically analyzes the sizes and number of parts in partitions, and if there is enough free resources in the pool, it starts background merges. Merges occur until the total size of the source parts is larger than `max_bytes_to_merge_at_max_space_in_pool`.
Merges initiated by [OPTIMIZE FINAL](../../sql-reference/statements/optimize.md) ignore `max_bytes_to_merge_at_max_space_in_pool` and merge parts only taking into account available resources (free disk's space) until one part remains in the partition.
`max_bytes_to_merge_at_min_space_in_pool` defines the maximum total size of parts which can be merged despite the lack of available disk space (in pool). This is necessary to reduce the number of small parts and the chance of `Too many parts` errors.
Merges book disk space by doubling the total merged parts sizes. Thus, with a small amount of free disk space, a situation may happen that there is free space, but this space is already booked by ongoing large merges, so other merges unable to start, and the number of small parts grows with every insert.
Merge reads rows from parts in blocks of `merge_max_block_size` rows, then merges and writes the result into a new part. The read block is placed in RAM, so `merge_max_block_size` affects the size of the RAM required for the merge. Thus, merges can consume a large amount of RAM for tables with very wide rows (if the average row size is 100kb, then when merging 10 parts, (100kb * 10 * 8192) = ~ 8GB of RAM). By decreasing `merge_max_block_size`, you can reduce the amount of RAM required for a merge but slow down a merge.
When there is less than specified number of free entries in pool (or replicated queue), start to lower maximum size of merge to process (or to put in queue).
The value of the `number_of_free_entries_in_pool_to_execute_mutation` setting should be less than the value of the [background_pool_size](/docs/en/operations/server-configuration-parameters/settings.md/#background_pool_size) * [background_merges_mutations_concurrency_ratio](/docs/en/operations/server-configuration-parameters/settings.md/#background_merges_mutations_concurrency_ratio). Otherwise, ClickHouse throws an exception.
During startup ClickHouse reads all parts of all tables (reads files with metadata of parts) to build a list of all parts in memory. In some systems with a large number of parts this process can take a long time, and this time might be shortened by increasing `max_part_loading_threads` (if this process is not CPU and disk I/O bound).
When there is less than specified number of free entries in pool, do not execute optimizing entire partition in the background (this task generated when set `min_age_to_force_merge_seconds` and enable `min_age_to_force_merge_on_partition_only`). This is to leave free threads for regular merges and avoid "Too many parts".
The value of the `number_of_free_entries_in_pool_to_execute_optimize_entire_partition` setting should be less than the value of the [background_pool_size](/docs/en/operations/server-configuration-parameters/settings.md/#background_pool_size) * [background_merges_mutations_concurrency_ratio](/docs/en/operations/server-configuration-parameters/settings.md/#background_merges_mutations_concurrency_ratio). Otherwise, ClickHouse throws an exception.
Enables the check at table creation, that the data type of a column for sampling or sampling expression is correct. The data type must be one of unsigned [integer types](../../sql-reference/data-types/int-uint.md): `UInt8`, `UInt16`, `UInt32`, `UInt64`.
By default, the ClickHouse server checks at table creation the data type of a column for sampling or sampling expression. If you already have tables with incorrect sampling expression and do not want the server to raise an exception during startup, set `check_sample_column_is_correct` to `false`.
Sets minimal amount of bytes to enable balancing when distributing new big parts over volume disks [JBOD](https://en.wikipedia.org/wiki/Non-RAID_drive_architectures).
The value of the `min_bytes_to_rebalance_partition_over_jbod` setting should not be less than the value of the [max_bytes_to_merge_at_max_space_in_pool](../../operations/settings/merge-tree-settings.md#max-bytes-to-merge-at-max-space-in-pool) / 1024. Otherwise, ClickHouse throws an exception.
Enables or disables detaching a data part on a replica after a merge or a mutation, if it is not byte-identical to data parts on other replicas. If disabled, the data part is removed. Activate this setting if you want to analyze such parts later.
The minimal number of marks read by the query for applying the [max_concurrent_queries](#max-concurrent-queries) setting. Note that queries will still be limited by other `max_concurrent_queries` settings.
Minimal ratio of the number of _default_ values to the number of _all_ values in a column. Setting this value causes the column to be stored using sparse serializations.
If a column is sparse (contains mostly zeros), ClickHouse can encode it in a sparse format and automatically optimize calculations - the data does not require full decompression during queries. To enable this sparse serialization, define the `ratio_of_defaults_for_sparse_serialization` setting to be less than 1.0. If the value is greater than or equal to 1.0, then the columns will be always written using the normal full serialization.
Notice the `s` column in the following table is an empty string for 95% of the rows. In `my_regular_table` we do not use sparse serialization, and in `my_sparse_table` we set `ratio_of_defaults_for_sparse_serialization` to 0.95:
The maximal length of the file name to keep it as is without hashing. Takes effect only if setting `replace_long_file_name_to_hash` is enabled. The value of this setting does not include the length of file extension. So, it is recommended to set it below the maximum filename length (usually 255 bytes) with some gap to avoid filesystem errors. Default value: 127.
If enabled, estimated actual size of data parts (i.e., excluding those rows that have been deleted through `DELETE FROM`) will be used when selecting parts to merge. Note that this behavior is only triggered for data parts affected by `DELETE FROM` executed after this setting is enabled.
If enabled along with [exclude_deleted_rows_for_part_size_in_merge](#exclude_deleted_rows_for_part_size_in_merge), deleted rows count for existing data parts will be calculated during table starting up. Note that it may slow down start up table loading.
Used to regulate how resources are utilized and shared between merges and other workloads. Specified value is used as `workload` setting value for background merges of this table. If not specified (empty string), then server setting `merge_workload` is used instead.
Used to regulate how resources are utilized and shared between mutations and other workloads. Specified value is used as `workload` setting value for background mutations of this table. If not specified (empty string), then server setting `mutation_workload` is used instead.
If this setting is enabled, ClickHouse attempts to store the data in newly inserted parts in a row order that minimizes the number of equal-value runs across the columns of the new table part.
It is generally possible to shuffle the rows of a table (or table part) freely as SQL considers the same table (table part) in different row order equivalent.
In ClickHouse, a primary key `C1, C2, ..., CN` enforces that the table rows are sorted by columns `C1`, `C2`, ... `Cn` ([clustered index](https://en.wikipedia.org/wiki/Database_index#Clustered)).
As a result, rows can only be shuffled within "equivalence classes" of row, i.e. rows which have the same values in their primary key columns.
The intuition is that primary keys with high-cardinality, e.g. primary keys involving a `DateTime64` timestamp column, lead to many small equivalence classes.
Likewise, tables with a low-cardinality primary key, create few and large equivalence classes.
The heuristics applied to find the best row order within each equivalence class is suggested by D. Lemire, O. Kaser in [Reordering columns for smaller indexes](https://doi.org/10.1016/j.ins.2011.02.002) and based on sorting the rows within each equivalence class by ascending cardinality of the non-primary key columns.