sorting key value).
Data deduplication occurs only during a merge. Merging occurs in the background at an unknown time, so you can’t plan for it. Some of the data may remain unprocessed. Although you can run an unscheduled merge using the
OPTIMIZE query, don’t count on using it, because the
OPTIMIZE query will read and write a large amount of data.
ReplacingMergeTree is suitable for clearing out duplicate data in the background in order to save space, but it doesn’t guarantee the absence of duplicates.
CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster] ( name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1], name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2], ... ) ENGINE = ReplacingMergeTree([ver]) [PARTITION BY expr] [ORDER BY expr] [PRIMARY KEY expr] [SAMPLE BY expr] [SETTINGS name=value, ...]
For a description of request parameters, see request description.
ver — column with version. Type
DateTime. Optional parameter.
ReplacingMergeTree from all the rows with the same primary key leaves only one:
When creating a
ReplacingMergeTree table the same clauses are required, as when creating a
Deprecated Method for Creating a Table
Do not use this method in new projects and, if possible, switch the old projects to the method described above.
CREATE TABLE [IF NOT EXISTS] [db.]table_name [ON CLUSTER cluster] ( name1 [type1] [DEFAULT|MATERIALIZED|ALIAS expr1], name2 [type2] [DEFAULT|MATERIALIZED|ALIAS expr2], ... ) ENGINE [=] ReplacingMergeTree(date-column [, sampling_expression], (primary, key), index_granularity, [ver])
All of the parameters excepting
ver have the same meaning as in
ver- column with the version. Optional parameter. For a description, see the text above.