ALTER query is only supported for
*MergeTree tables, as well as
Distributed. The query has several variations.
Changing the table structure.
ALTER TABLE [db].name [ON CLUSTER cluster] ADD|DROP|MODIFY COLUMN ...
In the query, specify a list of one or more comma-separated actions. Each action is an operation on a column.
The following actions are supported:
ADD COLUMN name [type] [default_expr] [AFTER name_after]
Adds a new column to the table with the specified name, type, and
default_expr (see the section "Default expressions"). If you specify
AFTER name_after (the name of another column), the column is added after the specified one in the list of table columns. Otherwise, the column is added to the end of the table. Note that there is no way to add a column to the beginning of a table. For a chain of actions, 'name_after' can be the name of a column that is added in one of the previous actions.
Adding a column just changes the table structure, without performing any actions with data. The data doesn't appear on the disk after ALTER. If the data is missing for a column when reading from the table, it is filled in with default values (by performing the default expression if there is one, or using zeros or empty strings). If the data is missing for a column when reading from the table, it is filled in with default values (by performing the default expression if there is one, or using zeros or empty strings). The column appears on the disk after merging data parts (see MergeTree).
This approach allows us to complete the ALTER query instantly, without increasing the volume of old data.
DROP COLUMN name
Deletes the column with the name 'name'. Deletes data from the file system. Since this deletes entire files, the query is completed almost instantly.
MODIFY COLUMN name [type] [default_expr]
Changes the 'name' column's type to 'type' and/or the default expression to 'default_expr'. When changing the type, values are converted as if the 'toType' function were applied to them.
If only the default expression is changed, the query doesn't do anything complex, and is completed almost instantly.
Changing the column type is the only complex action – it changes the contents of files with data. For large tables, this may take a long time.
There are several processing stages:
- Preparing temporary (new) files with modified data.
- Renaming old files.
- Renaming the temporary (new) files to the old names.
- Deleting the old files.
Only the first stage takes time. If there is a failure at this stage, the data is not changed. If there is a failure during one of the successive stages, data can be restored manually. The exception is if the old files were deleted from the file system but the data for the new files did not get written to the disk and was lost.
There is no support for changing the column type in arrays and nested data structures.
ALTER query lets you create and delete separate elements (columns) in nested data structures, but not whole nested data structures. To add a nested data structure, you can add columns with a name like
name.nested_name and the type
Array(T). A nested data structure is equivalent to multiple array columns with a name that has the same prefix before the dot.
There is no support for deleting columns in the primary key or the sampling key (columns that are in the
ENGINE expression). Changing the type for columns that are included in the primary key is only possible if this change does not cause the data to be modified (for example, it is allowed to add values to an Enum or change a type with
ALTER query is not sufficient for making the table changes you need, you can create a new table, copy the data to it using the
INSERT SELECT query, then switch the tables using the
RENAME query and delete the old table.
ALTER query blocks all reads and writes for the table. In other words, if a long
SELECT is running at the time of the
ALTER query, the
ALTER query will wait for it to complete. At the same time, all new queries to the same table will wait while this
ALTER is running.
For tables that don't store data themselves (such as
ALTER just changes the table structure, and does not change the structure of subordinate tables. For example, when running ALTER for a
Distributed table, you will also need to run
ALTER for the tables on all remote servers.
ALTER query for changing columns is replicated. The instructions are saved in ZooKeeper, then each replica applies them. All
ALTER queries are run in the same order. The query waits for the appropriate actions to be completed on the other replicas. However, a query to change columns in a replicated table can be interrupted, and all actions will be performed asynchronously.
Manipulations With Partitions and Parts
It only works for tables in the
MergeTree family. The following operations are available:
DETACH PARTITION– Move a partition to the 'detached' directory and forget it.
DROP PARTITION– Delete a partition.
ATTACH PART|PARTITION– Add a new part or partition from the
detacheddirectory to the table.
FREEZE PARTITION– Create a backup of a partition.
FETCH PARTITION– Download a partition from another server.
Each type of query is covered separately below.
A partition in a table is data for a single calendar month. This is determined by the values of the date key specified in the table engine parameters. Each month's data is stored separately in order to simplify manipulations with this data.
A "part" in the table is part of the data from a single partition, sorted by the primary key.
You can use the
system.parts table to view the set of table parts and partitions:
SELECT * FROM system.parts WHERE active
active – Only count active parts. Inactive parts are, for example, source parts remaining after merging to a larger part – these parts are deleted approximately 10 minutes after merging.
Another way to view a set of parts and partitions is to go into the directory with table data. Data directory:
/var/lib/clickhouse/ is the path to the ClickHouse data, 'database' is the database name, and 'table' is the table name. Example:
$ ls -l /var/lib/clickhouse/data/test/visits/ total 48 drwxrwxrwx 2 clickhouse clickhouse 20480 May 5 02:58 20140317_20140323_2_2_0 drwxrwxrwx 2 clickhouse clickhouse 20480 May 5 02:58 20140317_20140323_4_4_0 drwxrwxrwx 2 clickhouse clickhouse 4096 May 5 02:55 detached -rw-rw-rw- 1 clickhouse clickhouse 2 May 5 02:58 increment.txt
20140317_20140323_4_4_0 are the directories of data parts.
Let's break down the name of the first part:
20140317is the minimum date of the data in the chunk.
20140323is the maximum date of the data in the chunk.
2is the minimum number of the data block.
2is the maximum number of the data block.
0is the chunk level (the depth of the merge tree it is formed from).
Each piece relates to a single partition and contains data for just one month.
201403 is the name of the partition. A partition is a set of parts for a single month.
On an operating server, you can't manually change the set of parts or their data on the file system, since the server won't know about it. For non-replicated tables, you can do this when the server is stopped, but we don't recommended it. For replicated tables, the set of parts can't be changed in any case.
detached directory contains parts that are not used by the server - detached from the table using the
ALTER ... DETACH query. Parts that are damaged are also moved to this directory, instead of deleting them. You can add, delete, or modify the data in the 'detached' directory at any time – the server won't know about this until you make the
ALTER TABLE ... ATTACH query.
ALTER TABLE [db.]table DETACH PARTITION 'name'
Move all data for partitions named 'name' to the 'detached' directory and forget about them. The partition name is specified in YYYYMM format. It can be indicated in single quotes or without them.
After the query is executed, you can do whatever you want with the data in the 'detached' directory — delete it from the file system, or just leave it.
The query is replicated – data will be moved to the 'detached' directory and forgotten on all replicas. The query can only be sent to a leader replica. To find out if a replica is a leader, perform SELECT to the 'system.replicas' system table. Alternatively, it is easier to make a query on all replicas, and all except one will throw an exception.
ALTER TABLE [db.]table DROP PARTITION 'name'
The same as the
DETACH operation. Deletes data from the table. Data parts will be tagged as inactive and will be completely deleted in approximately 10 minutes. The query is replicated – data will be deleted on all replicas.
ALTER TABLE [db.]table ATTACH PARTITION|PART 'name'
Adds data to the table from the 'detached' directory.
It is possible to add data for an entire partition or a separate part. For a part, specify the full name of the part in single quotes.
The query is replicated. Each replica checks whether there is data in the 'detached' directory. If there is data, it checks the integrity, verifies that it matches the data on the server that initiated the query, and then adds it if everything is correct. If not, it downloads data from the query requestor replica, or from another replica where the data has already been added.
So you can put data in the 'detached' directory on one replica, and use the ALTER ... ATTACH query to add it to the table on all replicas.
ALTER TABLE [db.]table FREEZE PARTITION 'name'
Creates a local backup of one or multiple partitions. The name can be the full name of the partition (for example, 201403), or its prefix (for example, 2014): then the backup will be created for all the corresponding partitions.
The query does the following: for a data snapshot at the time of execution, it creates hardlinks to table data in the directory
/var/lib/clickhouse/ is the working ClickHouse directory from the config.
N is the incremental number of the backup.
The same structure of directories is created inside the backup as inside
/var/lib/clickhouse/. It also performs 'chmod' for all files, forbidding writes to them.
The backup is created almost instantly (but first it waits for current queries to the corresponding table to finish running). At first, the backup doesn't take any space on the disk. As the system works, the backup can take disk space, as data is modified. If the backup is made for old enough data, it won't take space on the disk.
After creating the backup, data from
/var/lib/clickhouse/shadow/ can be copied to the remote server and then deleted on the local server. The entire backup process is performed without stopping the server.
ALTER ... FREEZE PARTITION query is not replicated. A local backup is only created on the local server.
As an alternative, you can manually copy data from the
/var/lib/clickhouse/data/database/table directory. But if you do this while the server is running, race conditions are possible when copying directories with files being added or changed, and the backup may be inconsistent. You can do this if the server isn't running – then the resulting data will be the same as after the
ALTER TABLE t FREEZE PARTITION query.
ALTER TABLE ... FREEZE PARTITION only copies data, not table metadata. To make a backup of table metadata, copy the file
To restore from a backup:
- Use the CREATE query to create the table if it doesn't exist. The query can be taken from an .sql file (replace
ATTACHin it with
- Copy the data from the data/database/table/ directory inside the backup to the
ALTER TABLE ... ATTACH PARTITION YYYYMMqueries, where
YYYYMMis the month, for every month.
In this way, data from the backup will be added to the table. Restoring from a backup doesn't require stopping the server.
Backups and Replication
Replication provides protection from device failures. If all data disappeared on one of your replicas, follow the instructions in the "Restoration after failure" section to restore it.
For protection from device failures, you must use replication. For more information about replication, see the section "Data replication".
Backups protect against human error (accidentally deleting data, deleting the wrong data or in the wrong cluster, or corrupting data). For high-volume databases, it can be difficult to copy backups to remote servers. In such cases, to protect from human error, you can keep a backup on the same server (it will reside in
ALTER TABLE [db.]table FETCH PARTITION 'name' FROM 'path-in-zookeeper'
This query only works for replicatable tables.
It downloads the specified partition from the shard that has its
ZooKeeper path specified in the
FROM clause, then puts it in the
detached directory for the specified table.
Although the query is called
ALTER TABLE, it does not change the table structure, and does not immediately change the data available in the table.
Data is placed in the
detached directory. You can use the
ALTER TABLE ... ATTACH query to attach the data.
FROM clause specifies the path in
ZooKeeper. For example,
/clickhouse/tables/01-01/visits. Before downloading, the system checks that the partition exists and the table structure matches. The most appropriate replica is selected automatically from the healthy replicas.
ALTER ... FETCH PARTITION query is not replicated. The partition will be downloaded to the 'detached' directory only on the local server. Note that if after this you use the
ALTER TABLE ... ATTACH query to add data to the table, the data will be added on all replicas (on one of the replicas it will be added from the 'detached' directory, and on the rest it will be loaded from neighboring replicas).
Synchronicity of ALTER Queries
For non-replicatable tables, all
ALTER queries are performed synchronously. For replicatable tables, the query just adds instructions for the appropriate actions to
ZooKeeper, and the actions themselves are performed as soon as possible. However, the query can wait for these actions to be completed on all the replicas.
ALTER ... ATTACH|DETACH|DROP queries, you can use the
replication_alter_partitions_sync setting to set up waiting. Possible values:
0 – do not wait;
1 – only wait for own execution (default);
2 – wait for all.
Mutations are an ALTER query variant that allows changing or deleting rows in a table. In contrast to standard
DELETE queries that are intended for point data changes, mutations are intended for heavy operations that change a lot of rows in a table.
The functionality is in beta stage and is available starting with the 1.1.54388 version. Currently *MergeTree table engines are supported (both replicated and unreplicated).
Existing tables are ready for mutations as-is (no conversion necessary), but after the first mutation is applied to a table, its metadata format becomes incompatible with previous server versions and falling back to a previous version becomes impossible.
Currently available commands:
ALTER TABLE [db.]table DELETE WHERE filter_expr
filter_expr must be of type UInt8. The query deletes rows in the table for which this expression takes a non-zero value.
ALTER TABLE [db.]table UPDATE column1 = expr1 [, ...] WHERE filter_expr
filter_expr must be of type UInt8. This query updates values of specified columns to the values of corresponding expressions in rows for which the
filter_expr takes a non-zero value. Values are casted to the column type using the
CAST operator. Updating columns that are used in the calculation of the primary or the partition key is not supported.
One query can contain several commands separated by commas.
For *MergeTree tables mutations execute by rewriting whole data parts. There is no atomicity - parts are substituted for mutated parts as soon as they are ready and a
SELECT query that started executing during a mutation will see data from parts that have already been mutated along with data from parts that have not been mutated yet.
Mutations are totally ordered by their creation order and are applied to each part in that order. Mutations are also partially ordered with INSERTs - data that was inserted into the table before the mutation was submitted will be mutated and data that was inserted after that will not be mutated. Note that mutations do not block INSERTs in any way.
A mutation query returns immediately after the mutation entry is added (in case of replicated tables to ZooKeeper, for nonreplicated tables - to the filesystem). The mutation itself executes asynchronously using the system profile settings. To track the progress of mutations you can use the
system.mutations table. A mutation that was successfully submitted will continue to execute even if ClickHouse servers are restarted. There is no way to roll back the mutation once it is submitted.
Entries for finished mutations are not deleted right away (the number of preserved entries is determined by the
finished_mutations_to_keep storage engine parameter). Older mutation entries are deleted.
The table contains information about mutations of MergeTree tables and their progress. Each mutation command is represented by a single row. The table has the following columns:
database, table - The name of the database and table to which the mutation was applied.
mutation_id - The ID of the mutation. For replicated tables these IDs correspond to znode names in the
<table_path_in_zookeeper>/mutations/ directory in ZooKeeper. For unreplicated tables the IDs correspond to file names in the data directory of the table.
command - The mutation command string (the part of the query after
ALTER TABLE [db.]table).
create_time - When this mutation command was submitted for execution.
block_numbers.partition_id, block_numbers.number - A Nested column. For mutations of replicated tables contains one record for each partition: the partition ID and the block number that was acquired by the mutation (in each partition only parts that contain blocks with numbers less than the block number acquired by the mutation in that partition will be mutated). Because in non-replicated tables blocks numbers in all partitions form a single sequence, for mutatations of non-replicated tables the column will contain one record with a single block number acquired by the mutation.
parts_to_do - The number of data parts that need to be mutated for the mutation to finish.
is_done - Is the mutation done? Note that even if
parts_to_do = 0 it is possible that a mutation of a replicated table is not done yet because of a long-running INSERT that will create a new data part that will need to be mutated.