CREATE TABLE

Creates a new table.

As of version 7.3 of SingleStore, Columnstore is the default table storage format. Columnstore is also known as Universal Storage. See the Columnstore section for more information.

Syntax

CREATE [ROWSTORE] [REFERENCE | TEMPORARY | GLOBAL TEMPORARY] TABLE [IF NOT EXISTS] <table_name>
(<create_definition>,...)
[<table_options>]
[[AS] SELECT ...]
CREATE TABLE [IF NOT EXISTS] new_tbl_name
{ LIKE original_tbl_name | (LIKE original_tbl_name) }
[WITH DEEP | SHALLOW COPY]
<create_definition>:
<column_name> { <column_definition> | AS <computed_column_definition> }
| [CONSTRAINT [symbol]] PRIMARY KEY [<index_type>] (<index_column_name>,...)
[<index_option>] ...
| { INDEX | KEY } [<index_name>] [<index_type>] (<index_col_name>,...)
[<index_option>] ...
| [CONSTRAINT [symbol]] UNIQUE [INDEX | KEY]
[<index_name>] [<index_type>] (<index_column_name>,...)
[<index_option>] ...
| [CONSTRAINT [symbol]] SHARD KEY [<index_type>] (<index_column_name>,...) [METADATA_ONLY]
[<index_option>] ...
| SORT KEY (<index_column_name>,... [DESC])
| COLUMN GROUP [column_group_name] ( * )
| FULLTEXT[USING VERSION 1][<index_name>] (<index_column_name>,...)
| FULLTEXT USING VERSION 2 [<index_name>] (<index_column_name>,...)
| FOREIGN KEY [foreign_key_name](col1,..., coln) REFERENCES table_referenced (col_referenced))
<column_definition>:
<data_type> [NOT NULL | NULL] [DEFAULT <default_value>] [ON UPDATE <update_value>]
[AUTO_INCREMENT] [UNIQUE [KEY] | [PRIMARY] KEY] [SPARSE] [SERIES TIMESTAMP]
<computed_column_definition>:
computed_column_expression PERSISTED [data_type | AUTO]
<data_type>:
BIT[(<length>)]
| TINYINT[(<length>)] [UNSIGNED]
| SMALLINT[(<length>)] [UNSIGNED]
| INT[(<length>)] [UNSIGNED]
| INTEGER[(<length>)] [UNSIGNED]
| BIGINT[(<length>)] [UNSIGNED]
| REAL[(<length>,<decimals>)] [UNSIGNED]
| DOUBLE[(<length>,<decimals>)] [UNSIGNED]
| DECIMAL[(<length>[,<decimals>])] [UNSIGNED]
| NUMERIC[(<length>[,<decimals>])] [UNSIGNED]
| DATETIME
| DATETIME(6)
| TIMESTAMP
| TIMESTAMP(6)
| DATE
| TIME
| CHAR[(<length>)]
[CHARACTER SET <character_set_name>] [COLLATE <collation_name>]
| VARCHAR(<length>)
[CHARACTER SET <character_set_name>] [COLLATE <collation_name>]
| TINYBLOB
| BLOB
| MEDIUMBLOB
| LONGBLOB
| TINYTEXT [BINARY]
| TEXT [BINARY]
| MEDIUMTEXT [BINARY]
| LONGTEXT [BINARY]
| ENUM(<value1>,<value2>,<value3>,...)
| SET(<value1>,<value2>,<value3>,...)
| JSON [COLLATE <collation_name>]
| GEOGRAPHY
| GEOGRAPHYPOINT
<index_column_name>:
<column_name> [(<length>)] [ASC | DESC]
<index_type>:
| USING { BTREE | HASH }
<index_option>:
KEY_BLOCK_SIZE [=] <value>
| <index_type>
| COMMENT '<string>'
| BUCKET_COUNT [=] <value>
| WITH (<index_kv_options>)
| UNENFORCED [RELY | NORELY]
<index_kv_options>:
<index_kv_option> [, <index_kv_option>] ...
<index_kv_option>:
RESOLUTION = <value>
| COLUMNSTORE_SEGMENT_ROWS = <value>
| COLUMNSTORE_FLUSH_BYTES = <value>
<table_options>:
<table_option> [[,] <table_option>] ...
<table_option>:
AUTO_INCREMENT [=] <value>
| COMMENT [=] '<string>'
| AUTOSTATS_ENABLED = { TRUE | FALSE }
| AUTOSTATS_CARDINALITY_MODE = {INCREMENTAL|PERIODIC|OFF}
| AUTOSTATS_HISTOGRAM_MODE = {CREATE|UPDATE|OFF}
| AUTOSTATS_SAMPLING = {ON|OFF}
| COMPRESSION = SPARSE

CREATE { TABLE | TABLES } AS INFER PIPELINE

CREATE TABLE [IF NOT EXISTS] <table_name>
AS INFER PIPELINE AS LOAD DATA
{ LINK <link_name> |
MONGODB "<collection>" CONFIG '<config_json>' CREDENTIALS '<credentials_json>' |
MYSQL "<source_db>.<source_table>" CONFIG '<config_json>' CREDENTIALS '<credentials_json>' }
FORMAT AVRO;
CREATE TABLES [IF NOT EXISTS]
AS INFER PIPELINE AS LOAD DATA
{ LINK <link_name> |
MONGODB '*' CONFIG '<conf_json>' CREDENTIALS '<cred_json>' |
MYSQL "*" CONFIG '<config_json>' CREDENTIALS '<credentials_json>' }
FORMAT AVRO;

SingleStore supports replicating data from MongoDB® and MySQL data sources using Change Data Capture (CDC) pipelines. Refer to the following for replicating data from the respective data source:

Remarks

Note

Unless CREATE ROWSTORE TABLE ... or SORT KEY() are specified, the value of the default_table_type engine variable determines the type of table (columnstore or rowstore) that is created.

When default_table_type is set to columnstore, you can create a columnstore table using standard CREATE TABLE syntax.

default_table_type is set to columnstore by default.

The setting of default_table_type applies to temporary tables. When creating GLOBAL TEMPORARY tables, if default_table_type is set to columnstore, you must use CREATE ROWSTORE GLOBAL TEMPORARY TABLE. GLOBAL TEMPORARY is not supported on columnstore tables.

  • For more information about the data types listed above, and for an explanation of UNSIGNED, refer to the Data Types topic.

  • The SET data type restricts the values that can be inserted for a table column. Only the set of strings that are listed for a column at the time of table creation can be inserted.

  • <table_name> is the name of the table to create in the SingleStore database.

  • The following note applies when the engine variable table_name_case_sensitivity is set to OFF: After you create a table, you cannot create another table having the same table name with a different case. Refer to the Database Object Case Sensitivity topic for more information.

  • CREATE TABLE is slower in SingleStore than in MySQL. See Code Generation for more information.

  • The KEY syntax is equivalent to using INDEX syntax when used in CREATE TABLE . The convention is to use the KEY syntax. INDEX syntax is generally used when creating an index on an existing table. See CREATE INDEX for more information.

  • Foreign key referential integrity enforcement is not supported by SingleStore, but FOREIGN KEY syntax can be supported in SingleStore by setting the ignore_foreign_keys engine variable to ON. The default value for ignore_foreign_keys is OFF. See the Specifying Unenforced Unique Constraints page for more information.

  • The BTREE index type creates a skip list index in SingleStore. This index has very similar characteristics to a BTREE index.

  • If you do not want to specify a column (or columns) to sort on, or do not care about the sort order for your data, you can specify an empty key (e.g. SORT KEY()).

  • The SORT KEY() order can be specified as ascending (SORT KEY(index_column_name)) or descending (SORT KEY(index_column_name DESC)). SingleStore does not support scanning a SORT KEY() in reverse order to its sort order:

    CREATE TABLE ct_sort (col1 int, SORT KEY(col1 DESC));
    EXPLAIN SELECT * FROM ct_sort ORDER BY col1 DESC;
    +-------------------------------------------------------------------------------------------+
    | EXPLAIN                                                                                   |
    +-------------------------------------------------------------------------------------------+
    | Project [remote_0.col1]                                                                  
    | TopSort limit:[@@SESSION.`sql_select_limit`] [remote_0.col1 DESC]                         |
    | Gather partitions:all alias:remote_0 parallelism_level:sub_partition                      |
    | Project [t1.col1]                                                                         |
    | Top limit:[?]                                                                             |
    | ColumnStoreFilter [<after per-thread scan begin> AND <before per-thread scan end>]        |
    | OrderedColumnStoreScan test1.t1, SORT KEY col1 (col1 DESC) table_type:sharded_columnstore |
    +-------------------------------------------------------------------------------------------+
    EXPLAIN SELECT * FROM ct_sort ORDER BY col1;
    +------------------------------------------------------------------------------------+
    | EXPLAIN                                                                            |
    +------------------------------------------------------------------------------------+
    | Project [remote_0.col1]                                                            |
    | TopSort limit:[@@SESSION.`sql_select_limit`] [remote_0.col1]                       |
    | Gather partitions:all alias:remote_0 parallelism_level:segment                     |
    | Project [t1.col1]                                                                  |
    | TopSort limit:[?] [t1.col1]                                                        |
    | ColumnStoreScan test1.t1, SORT KEY col1 (col1 DESC) table_type:sharded_columnstore |
    +------------------------------------------------------------------------------------+
  • SORT KEY() is not allowed when using CREATE ROWSTORE TABLE ....

  • KEY() USING CLUSTERED COLUMNSTORE is a legacy syntax that is equivalent to SORT KEY(). SingleStore recommends using SORT KEY().

  • BUCKET_COUNT is specific to the HASH index type. It controls the bucket count of the hash table. It applies to rowstore hash indexes only and does not effect columnstore hash indexes.

  • The UNENFORCED index option can be used on a UNIQUE constraint to specify that the unique constraint is unenforced. See Unenforced Unique Constraints.

  • RESOLUTION is specific to index on geospatial columns. See Working with Geospatial Features for more information.

  • COLUMNSTORE_SEGMENT_ROWS, COLUMNSTORE_FLUSH_BYTES controls configuration variables specific to columnstore tables. See Advanced Columnstore Configuration Options) for more information.

  • SingleStore supports binary, utf8, and utf8mb4 character sets. The COLLATE clause in the CREATE TABLE statement can be used to override the server character set and collation, which are used as default values for the table.

    For more information, see Character Set and Collation Override.

  • AUTOSTATS_ENABLED controls if automatic statistics should be collected on this table. There are three categories of autostats - AUTOSTATS_CARDINALITY_MODE, AUTOSTATS_HISTOGRAM_MODE, and AUTOSTATS_SAMPLING. SingleStore allows you to independently control how each category of statistics is automatically gathered. Multiple autostats settings can be combined in a single CREATE TABLE statement. See Automatic Statistics for more information.

  • This command can be run on the master aggregator node, or a child aggregator node (see Node Requirements for SingleStore Commands ).

  • This command causes implicit commits. Refer to COMMIT for more information.

  • Specify the AUTO option instead of the <data_type> in the <computed_column_definition> clause to automatically infer the data type of the column from the <computed_column_expression>.

  • <computed_column_expression> defines the value of a computed column using other columns in the table, constants, built-in functions, operators, and combinations thereof. For more information see Persistent Computed Columns.

  • Temporary tables, created with the TEMPORARY option, will be deleted when the client session terminates. For ODBC/JDBC, this is when the connection closes. For interactive client sessions, it is when the user terminates the client program.

  • Global temporary tables, created with the GLOBAL TEMPORARY option, exist beyond the duration of a client session. If failover occurs, the global temporary tables lose data and enter an errored state; they need to be dropped and recreated. This command can be run only on the master aggregator. See Global Temporary Tables for details.

  • The SERIES TIMESTAMP clause specifies a table column as the default column defining time order for implicit use by time series functions. This setting can be specified only for a single table column. The column can be one of the following data types: DATE,TIME,DATETIME, DATETIME(6), TIMESTAMP or TIMESTAMP(6). SingleStore recommends to use either of the DATETIME or DATETIME(6) types instead of one of the TIMESTAMP types because the automatic update behavior of TIMESTAMP is subject to change. See Timestamp Behavior for details.

  • The SERIES TIMESTAMP clause does not affect the data type of a table column, rather it specifies the behavior of the column in the time-series-specific functions like FIRST(), LAST(), and TIME_BUCKET().

  • Keyless sharding distributes data across partitions uniformly at random but with the limitation that it does not allow single partition queries or local joins since rows are not assigned to specific partitions. Keyless sharding is the default for tables that do not have primary key or explicit shard key. You can explicitly declare a table as keyless sharded by specifying a shard key with an empty list of columns in the SHARD KEY() constraint in the table definition.

  • The METADATA_ONLY option on the SHARD KEY syntax prevents an index being created on the shard key. It will decrease overall memory usage. It can cause queries to run slower. It can only be used when creating your table.

  • The optional COLUMN GROUP clause creates a materialized copy of each row as a separate index. It is supported on columnstore tables only. This structure can be used to accelerate full-row retrievals and updates for wide columnstore tables.

    Column group indexes use less RAM than rowstore tables which can reduce operation costs. Using column group indexes on columnstores can allow you to get both fast lookups and fast analytics on the same table. The column group index improves the performance of lookups, and the standard columnar representation is available to give fast analytics. Using a column group index on a columnstore table is easier to manage than having to move data between rowstore and columnstore tables.

    The find the size of a column group index, refer to the How the Columnstore Works page.

    The column_group_name argument is optional. If a column group name is not specified when creating a table, one is chosen by the engine. Using COLUMN GROUP [column_group_name] (*) creates a column group index on all columns in the table. Column group indexes created on a subset of table columns are not supported.

    The following is an syntax example of a columnstore table that creates a column group on all columns:

    CREATE TABLE col_group_1(id BIGINT, col1 VARCHAR(10), col2 VARCHAR(10), ..., coln INT, COLUMN GROUP col_gp_inx (*));
  • The WITH DEEP COPY argument of the CREATE TABLE new_tbl_name LIKE original_tbl_name statement copies an existing table (original_tbl_name) and creates a new table that will have the same definition as the original table - including all of the data and metadata (such as indexes) in the original table. Users must have SELECT permissions to be able to execute SQL statements against the new table. Computed columns will be recomputed during the WITH DEEP COPY process.

  • The WITH SHALLOW COPY argument of the CREATE TABLE new_tbl_name LIKE original_tbl_name statement copies an existing table (original_tbl_name) and creates a new table that will have the same definition as the original table. The data is not physically copied to the new table, but referenced against the original table. So any SELECT query made against either table produces the same result, until one of them is updated. Users must have SELECT permissions to be able to execute SQL statements against the new table.

  • Refer to the Permission Matrix for the required permission.

MySQL Compatibility

SingleStore’s syntax differs from MySQL mainly in the data types and storage it supports, and some specific index hints.

  • KEY_BLOCK_SIZE [=] <value> : value is currently ignored.

DEFAULT Behavior

If DEFAULT <default_value> is specified in <column_definition>, and no value is inserted in the column, then <default_value> will be placed in the column during an INSERT operation.

ON UPDATE Behavior

If ON UPDATE <update_value> is specified in <column_definition>, and if any other column is updated but the specified column is not explicitly updated, then update_value will be placed in the column during an UPDATE operation. If the column is of the type TIMESTAMP, TIMESTAMP(6), DATETIME , or DATETIME(6), then you can update <update_value> to one of the following values: CURRENT_TIMESTAMP(), CURRENT_TIMESTAMP(6), NOW(), or NOW(6).

ON UPDATE can be used with these TIMESTAMP/DATETIME[(6)] types only, and you can only use one of the time functions as the argument. For more information, see Data Types.

Storage of CHAR(<length>) as VARCHAR(<length>)

For a column defined as type CHAR of length len, store the column as a VARCHAR of length len if len greater than or equal to the value of the engine variable varchar_column_string_optimization_length. If the value of the variable is 0, the column is not stored as a VARCHAR.

Storing a CHAR of length len as a VARCHAR of length len will allow the column to realize the performance benefit of a VARCHAR, in many cases. For example, CHARs use 3 bytes of memory, and VARCHARs use 1 byte. VARCHAR can have better performance and use less memory during query execution because SingleStore does not need to allocate and process full-length strings with 3 bytes per char, as it does when using CHAR.

Suppose the value of varchar_column_string_optimization_length is 3 and you run:

CREATE TABLE ct_char(a CHAR(4));

The column a is stored as a VARCHAR(4).

Example(s)

CREATE TEMPORARY

CREATE TEMPORARY or CREATE ROWSTORE TEMPORARY (if default_table_type is set to columnstore, you must use the latter syntax) creates a table that will be deleted when the client session terminates.

CREATE TEMPORARY TABLE IF NOT EXISTS ct_temp_1 (id INT AUTO_INCREMENT PRIMARY KEY, a INT, b INT, SHARD KEY(id));
CREATE ROWSTORE TEMPORARY TABLE IF NOT EXISTS ct_temp_1 (id INT AUTO_INCREMENT PRIMARY KEY, a INT, b INT, SHARD KEY(id));

CREATE ROWSTORE GLOBAL TEMPORARY

CREATE ROWSTORE GLOBAL TEMPORARY creates a table that exists beyond the duration of a client session. If a failover occurs, a global temporary table loses data and enters an errored state; the global temporary table needs to be dropped and recreated.

CREATE ROWSTORE GLOBAL TEMPORARY TABLE IF NOT EXISTS ct_temp_2 (id INT AUTO_INCREMENT PRIMARY KEY, a INT, b INT, SHARD KEY(id));

CREATE TABLE with an AUTO_INCREMENT Column

AUTO_INCREMENT can be used to automatically generate a unique value for new rows. When you insert a new row, and the AUTO_INCREMENT field is DEFAULT, NULL, or 0, SingleStore will automatically assign a value. It’s important to understand that AUTO_INCREMENT only guarantees that automatically-generated values are unique. In general, it does not guarantee that they:

  • are consecutive or sequential

  • are monotonically increasing

  • start from any particular value

  • are distinct from explicitly-set values

If you explicitly set a value in an INSERT or UPDATE statement, it may collide with past or future automatically-generated values. For example, in the following example, a value is added explicitly to the AUTO_INCREMENT column. This will break the table unless AGGREGATOR SYNC AUTO_INCREMENT is run by the end user (which will reset the auto-increment counter to a value higher than 10). In this case, a duplicate key will not be generated when the AUTO_INCREMENT value reaches 10 eventually on its own as additional rows are added to the table.

CREATE TABLE ct_auto (c1 INT AUTO_INCREMENT PRIMARY KEY);
INSERT INTO ct_auto (c1) VALUES (10);

A table can have only one AUTO_INCREMENT column. The AUTO_INCREMENT column must be included in an index (not necessarily a PRIMARY or UNIQUE key, a regular key is also allowed).

If syntax such as CREATE TABLE table_1 SELECT * FROM table_2 is used to create table_1 where table_2 has an AUTO_INCREMENT column, it will be created as a non-auto-increment column in table_1.

See LAST_INSERT_ID for more information on AUTO_INCREMENT behavior.

If the AUTO_INCREMENT behavior described here does not satisfy your requirements you can create your own sequence generator using LAST_INSERT_ID. See the sequence generator stored procedure example.

Warning

Restarting an aggregator, such as during upgrades or host machine maintenance, will introduce a large gap between any AUTO_INCREMENT values inserted before the restart and any values inserted after. In the case of reference tables, this same behavior might also occur when a child aggregator is promoted to master aggregator. Depending on how often you restart your aggregators, you could see many jumps in values from a specific aggregator.

These jumps are because each aggregator defines and manages its own range of values to start incrementing from to prevent collisions in a table. With each restart, a new batch of values is used. For sharded tables, the range of AUTO_INCREMENT values increases to the next 1,000,000 after each restart (e.g. 2,430,403 before restart -> 3,000,000 after). For reference tables, the batch size jumps to the next 1,000. And as with previous versions of SingleStore, these values are also encoded with the aggregator ID, as described in the next section.

AUTO_INCREMENT in Sharded Tables

On a sharded (distributed) table, AUTO_INCREMENT can only be used on a BIGINT column (as they usually use the entire 64 bits). Each aggregator computes and tracks its own AUTO_INCREMENT values and uses those values when new rows are added to a table. AUTO_INCREMENT values in sharded tables are assigned using the high 14 bits to encode the aggregator ID and the bottom 50 bits for a per-aggregator unique value. The values on each aggregator are usually, but not always, sequential; therefore, inserts on an individual aggregator generate values which are unique and usually sequential. And because each aggregator manages its own AUTO_INCREMENT values, the automatically-generated values from inserts across multiple aggregators are only unique, never sequential.

Here is an example to illustrate how AUTO_INCREMENT values are generated across aggregators in a cluster as new rows are inserted into table ct_tb:

SELECT * FROM ct_tb ORDER BY b;
+-------------------+------+------------+
| a                 | b    | c          |
+-------------------+------+------------+
|                 1 |    1 | from MA    |
|                 2 |    2 | from MA    |
|                 3 |    3 | from MA    |
|                 4 |    4 | from MA    |
|                 5 |    5 | from MA    |
| 13510798882111489 |    6 | from CA 96 |
| 13510798882111490 |    7 | from CA 96 |
| 13510798882111491 |    8 | from CA 96 |
| 13510798882111492 |    9 | from CA 96 |
| 13510798882111493 |   10 | from CA 96 |
| 14636698788954113 |   11 | from CA 20 |
| 14636698788954114 |   12 | from CA 20 |
| 14636698788954115 |   13 | from CA 20 |
| 14636698788954116 |   14 | from CA 20 |
| 14636698788954117 |   15 | from CA 20 |
|                 6 |   16 | from MA    |
| 15762598695796737 |   17 | from CA 17 |
| 13510798882111494 |   18 | from CA 96 |
|                 7 |   19 | from MA    |
| 14636698788954118 |   20 | from CA 20 |
+-------------------+------+------------+

As shown in the example above, automatically-generated AUTO_INCREMENT values can differ depending on which aggregator you run the inserts on. Of course, if you ran some inserts on one aggregator and some inserts on another aggregator, you would get different automatically generated values. Also note that automatically-generated values and explicitly-set values can collide in sharded tables.

AUTO_INCREMENT in Reference Tables

The AUTO_INCREMENT value for a reference table is tracked by the master aggregator. It is guaranteed that the next AUTO_INCREMENT value will always be greater than any value previously seen in this column. These generated values are usually sequential, but not always. Contrarily to the behavior for sharded tables, explicitly setting a value in an INSERT or UPDATE statement will not create a collision with future automatically generated values.

The next example shows some queries using AUTO_INCREMENT fields on reference tables.

CREATE REFERENCE TABLE ct_ref_1(id INT AUTO_INCREMENT PRIMARY KEY);
INSERT INTO ct_ref_1 VALUES();
INSERT INTO ct_ref_1 VALUES(5);
INSERT INTO ct_ref_1 VALUES();
SELECT id FROM ct_ref_1 ORDER BY id;
+----+
| id |
+----+
|  1 |
|  5 |
|  6 |
+----+
UPDATE ct_ref_1 SET id = 9 WHERE id = 5;
INSERT INTO ct_ref_1();
SELECT id FROM ct_ref_1 ORDER BY id;
+----+
| id |
+----+
|  1 |
|  6 |
|  9 |
| 10 |
+----+
DELETE FROM ct_ref_1;
INSERT INTO ct_ref_1 VALUES();
SELECT id FROM ct_ref_1 ORDER BY id;
+----+
| id |
+----+
| 11 |
+----+

Setting AUTO_INCREMENT Starting Values

It is possible to override the starting AUTO_INCREMENT value for reference tables by setting the AUTO_INCREMENT option on a CREATE TABLE statement.

The following example shows how to set the AUTO_INCREMENT start value during table creation:

CREATE REFERENCE TABLE ct_ref_2 (id int AUTO_INCREMENT PRIMARY KEY) AUTO_INCREMENT = 7;
INSERT INTO ct_ref_2 VALUES (), ();
SELECT * FROM ct_ref_2;
+----+
| id |
+----+
|  7 |
|  8 |
+----+

This syntax has no effect on sharded tables. It will not return an error, for compatibility with external tools, but it will explicitly present a warning and no operation will be done.

AUTO_INCREMENT During Replication

When replicating data between clusters, the secondary cluster has all the replicated AUTO_INCREMENT values from the primary cluster. When you failover to a secondary cluster, SingleStore synchronizes the secondary cluster by looking for the maximum value in the range of AUTO_INCREMENT values on every aggregator.

CREATE TABLE IF NOT EXISTS my_MemSQL_table (id INT PRIMARY KEY AUTO_INCREMENT, v VARCHAR(10) NOT NULL);

CREATE TABLE AS SELECT

CREATE TABLE AS SELECT (also referred to as CREATE TABLE ... SELECT) can create one table from results of a SELECT query.

Here is the basic syntax. You can create the new table and set shard keys, sort keys, and or other indexes:

CREATE [ROWSTORE] [REFERENCE | TEMPORARY | GLOBAL TEMPORARY] TABLE [IF NOT EXISTS] <table_name_2>
(column_name(s), [SHARD KEY(column_name)] | [SORT KEY(column_name)] | [KEY(column_name)]
AS SELECT [*] | [column_name(s)] FROM table_name_1;

Here is an example of a CREATE TABLE AS SELECT command with a shard key, sort key and an index:

CREATE TABLE ctas_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b), KEY(a)) AS SELECT * FROM orig_table;

The table will include a column for each column of the SELECT query. You can define indexes, additional columns, and other parts of the table definition in the create_definition. Persisted computed columns can also be specified this way. Some examples:

CREATE TABLE table_1 (PRIMARY KEY (a, b)) AS SELECT * FROM table_2;
CREATE TABLE table_1 (SORT KEY (a, b)) AS SELECT * FROM table_2;
CREATE TABLE table_1 (a int, b int) AS SELECT c, d FROM table_2;
CREATE TABLE table_1 (b AS a+1 PERSISTED int) AS SELECT a FROM table_2;

In the case that the original table (table_2 in the above examples) has an AUTO_INCREMENT column, it will be created as a non-auto-increment column in the new table (table_1).

CREATE TABLE AS SELECT to Extract Data from One Column in an Existing Table

Extract time column from an event table to build a times table.

CREATE TABLE events (type VARCHAR(256), time TIMESTAMP);
INSERT INTO events VALUES('WRITE', NOW());
CREATE TABLE times (id INT AUTO_INCREMENT KEY, time TIMESTAMP) AS SELECT time FROM events;
SELECT * FROM times;
+----+---------------------+
| id | time                |
+----+---------------------+
|  1 | 2023-06-21 15:57:35 |
+----+---------------------+

CREATE TABLE AS SELECT to Extract Distinct Values from an Existing Table

SELECT * FROM courses ORDER BY course_code, section_number;
+-------------+----------------+-----------------+
| course_code | section_number | number_students |
+-------------+----------------+-----------------+
| CS-101      |              1 |              20 |
| CS-101      |              2 |              16 |
| CS-101      |              3 |              22 |
| CS-101      |              4 |              25 |
| CS-101      |              5 |              22 |
| CS-150      |              1 |              10 |
| CS-150      |              2 |              16 |
| CS-150      |              3 |              11 |
| CS-150      |              4 |              17 |
| CS-150      |              5 |               9 |
| CS-201      |              1 |              14 |
| CS-201      |              2 |              17 |
| CS-301      |              1 |               7 |
| CS-301      |              2 |              10 |
+-------------+----------------+-----------------+
CREATE TABLE IF NOT EXISTS distinct_courses (PRIMARY KEY(course_code))
AS SELECT DISTINCT(course_code) FROM courses;
SELECT * FROM distinct_courses ORDER by course_code;
+-------------+
| course_code |
+-------------+
| CS-101      |
| CS-150      |
| CS-201      |
| CS-301      |
+-------------+

CREATE TABLE USING HASH

The USING HASH clause creates a hash index in a table.

If a rowstore or columnstore table is being created, the following applies:

  • You can create single-column or multi-column hash indexes.

  • When you create a unique single-column hash index, the shard key can contain only one column and that column must be the same column that you have created the index on. When you create a unique multi-column hash index, the shard key must be a subset of the columns that you have created the index on.

  • You can create multiple single-column hash indexes on a reference table.

If a columnstore table is being created, the following applies:

  • You can create at most one unique hash index. You can create multiple multi-column hash indexes.

  • You cannot create a unique hash index on a FLOAT, REAL, or DOUBLE column.

CREATE TABLE with Multiple Hash Indexes

The following example creates a columnstore table with three hash indexes. One of these indexes has a multi-column key.

CREATE TABLE articles_3 (
id INT UNSIGNED,
month int UNSIGNED,
year int UNSIGNED,
title VARCHAR(200),
body TEXT,
SHARD KEY(title),
SORT KEY (id),
KEY (id) USING HASH,
UNIQUE KEY (title) USING HASH,
KEY (month,year) USING HASH);

The query SELECT * FROM articles WHERE title = 'Interesting title here'; uses title’s hash index since the query uses an equality predicate. The query runs faster than if the hash index had not been used.

The query SELECT * FROM articles WHERE year > 2010 AND month > 5; does not use the hash index on month and year since the query does not use an equality predicate.

See the ColumnstoreFilter in the Query Plan Operations topic for an example EXPLAIN plan for a columnstore query that uses a hash index.

See Highly Selective Joins for an example of a columnstore query with a join that uses a hash index.

CREATE TABLE with One Hash Index Containing Multiple Columns

KEY(<column 1 name>,<column 2 name>, ... <column n name>) is equivalent to KEY(<column 1 name>,<column 2 name>,... <column n name>) USING HASH. For example,

CREATE TABLE ct_hash_1(a INT, b INT, c INT, KEY(a,b));

is equivalent to:

CREATE TABLE ct_hash_1(a INT, b INT, SORT KEY(), KEY(a,b) USING HASH);

A query against t with an equality filter on a, an equality filter on b, or equality filters on both a and b could benefit from KEY(a,b) USING HASH. A query that uses both equality filters would be the most efficient.

Depending on the cardinality, the performance of the query may be worse than the performance of the same query, where t is a rowstore table and KEY(a,b) is defined on that table.

CREATE TABLE with FULLTEXT Columns

SingleStore supports full-text search across text columns in a columnstore table using the FULLTEXT index type. A full-text index can only be added in a CREATE TABLE or ALTER TABLE ADD FULLTEXT statement and only on the text types CHAR, VARCHAR, TEXT, and LONGTEXTData Types

If you query a column cthat is part of a multi-column FULLTEXT index, where the query uses a FULLTEXT MATCH on c, the index on c will be applied.

This differs from a multi-column non-FULLTEXT index, where behavior is as follows: if you query column c that is part of index i, where the query uses an equality filter on c, the index on c will only be applied if c is the leftmost column in i.

Any column that is part of a FULLTEXT index can be queried, even if it is not the leftmost. Searches across FULLTEXT columns are done using the SELECT ... MATCH AGAINST syntax. For more information, see MATCH.

CREATE TABLE with FULLTEXT Index on Two Columns

This example creates a FULLTEXT index for both the title column and the body column. Either column could be queried separately using MATCH <column_name>, and the index on the column would be applied. The USING VERSION 1 syntax is optional.

CREATE TABLE articles_1 (
id INT UNSIGNED,
year int UNSIGNED,
title VARCHAR(200),
body TEXT,
SORT KEY (id),
FULLTEXT USING VERSION 1 (title,body));

CREATE TABLE with Version 2 FULLTEXT Index

This example creates a FULLTEXT index for both the title column and the body column. Either column can be queried separately using MATCH (TABLE <table_name>) AGAINST (<expression>), and the index on the column will be applied.

Refer to Working with Full-Text Search for more information about version 2 full-text search.

CREATE TABLE articles (
id INT UNSIGNED,
year int UNSIGNED,
title VARCHAR(200),
body TEXT,
SORT KEY (id),
FULLTEXT USING VERSION 2 art_ft_index (title, body));
INSERT INTO articles (id, year, title, body) VALUES
(1, 2021, 'Introduction to SQL', 'SQL is a standard language for accessing and manipulating databases.'),
(2, 2022, 'Advanced SQL Techniques', 'Explore advanced techniques and functions in SQL for better data manipulation.'),
(3, 2020, 'Database Optimization', 'Learn about various optimization techniques to improve database performance.'),
(4, 2023, 'SQL in Web Development', 'Discover how SQL is used in web development to interact with databases.'),
(5, 2019, 'Data Security in SQL', 'An overview of best practices for securing data in SQL databases.'),
(6, 2021, 'SQL and Data Analysis', 'Using SQL for effective data analysis and reporting.'),
(7, 2022, 'Introduction to Database Design', 'Fundamentals of designing a robust and scalable database.'),
(8, 2020, 'SQL Performance Tuning', 'Tips and techniques for tuning SQL queries for better performance.'),
(9, 2023, 'Using SQL with Python', 'Integrating SQL with Python for data science and automation tasks.'),
(10, 2019, 'NoSQL vs SQL', 'A comparison of NoSQL and SQL databases and their use cases.');
OPTIMIZE TABLE articles FLUSH;
SELECT * FROM articles WHERE MATCH (TABLE articles) AGAINST ('body:database');
+----+------+---------------------------------+-----------------------------------------------------------------------------+
| id | year | title                           | body                                                                        |
+----+------+---------------------------------+-----------------------------------------------------------------------------+
| 7  | 2022 | Introduction to Database Design |	Fundamentals of designing a robust and scalable database.                   |
| 3  | 2020 | Database Optimization	      | Learn about various optimization techniques to improve database performance.|
+----+------+---------------------------------+-----------------------------------------------------------------------------+

Refer to the MATCH page for more legacy and version 2 full-text examples.

Errors

These are the possible errors you may encounter when using FULLTEXT.

Error

Error String

Invalid Type specified for column

Invalid type specified for FULLTEXT

Specifying FULLTEXT keyword more than once in a CREATE TABLE statement

FULLTEXT may only be specified once in a CREATE TABLE statement

Specifying the same column multiple times

Column may only be specified once in a FULLTEXT definition

Specifying a column that is not defined on the table

Column not defined

Specifying FULLTEXT on a row store table

Only column store tables may have a FULLTEXT index

CREATE TABLE WITH DEEP COPY

The WITH DEEP COPY feature creates a new table that will have the same table definition as the original table. CREATE TABLE WITH DEEP COPY  makes a full copy of the data and indexes in the original table. Computed columns will be recomputed during the WITH DEEP COPY process. Any operation (INSERT, UPDATE, DELETE, ALTER TABLE, or DROP TABLE) on the original table will not affect the copied table and vice versa.

The WITH DEEP COPY feature eliminates the need to run a CREATE TABLE LIKE followed by an INSERT SELECT statement. In one statement, a table can be created that contains all of the columns, data, and other metadata (such as indexes) of the table from which it is copied.

There are some cases where WITH DEEP COPY is not supported. Error messages will be generated if these cases are attempted.

Creating a rowstore deep copy of an existing table:

CREATE TABLE orig_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b));
CREATE ROWSTORE TABLE ctdc_table LIKE orig_table WITH DEEP COPY;
ERROR 1706 ER_MEMSQL_FEATURE_LOCKDOWN: Feature 'CREATE Explicit ROWSTORE TABLE LIKE' is not supported by SingleStore.

Creating a reference deep copy of an existing table:

CREATE TABLE orig_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b));
CREATE REFERENCE TABLE ctdc_table LIKE orig_table WITH DEEP COPY;
ERROR 1706 ER_MEMSQL_FEATURE_LOCKDOWN: Feature 'CREATE REFERENCE TABLE LIKE' is not supported by SingleStore.

CREATE TABLE WITH DEEP COPY Same Database

CREATE TABLE orig_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b));
INSERT INTO orig_table (a,b) VALUES (9,3), (5,2), (10,4), (12,7);
SELECT * FROM orig_table;
+----+----+
| a  | b  |
+----+----+
| 10 | 4  |
| 12 | 7  |
| 5  | 2  |
| 9  | 3  |
+----+----+   
CREATE TABLE ctdc_table LIKE orig_table WITH DEEP COPY;
SELECT * FROM ctdc_table;
+----+----+
| a  | b  |
+----+----+
| 10 | 4  |
| 12 | 7  |
| 5  | 2  |
| 9  | 3  |
+----+----+

CREATE TABLE WITH DEEP COPY Across Databases

CREATE TABLE test1.orig_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b));
INSERT INTO test1.orig_table (a,b) VALUES (9,3), (5,2), (10,4), (12,7);
SELECT * FROM test1.orig_table;
+----+----+
| a  | b  |
+----+----+
| 10 | 4  |
| 12 | 7  |
| 5  | 2  |
| 9  | 3  |
+----+----+
CREATE TABLE test2.ctdc_table LIKE test1.orig_table WITH DEEP COPY;
SELECT * FROM test2.ctdc_table;
+----+----+
| a  | b  |
+----+----+
| 10 | 4  |
| 12 | 7  |
| 5  | 2  |
| 9  | 3  |
+----+----+

CREATE TABLE WITH SHALLOW COPY

The WITH SHALLOW COPY feature creates a new table that will have the same structure as the original table. CREATE TABLE WITH SHALLOW COPY is a metadata-only operation and will not duplicate the actual data. Any operation (INSERT, UPDATE, DELETE, ALTER TABLE, or DROP TABLE) on the original table will not affect the shallow copy table and vice versa.

The WITH SHALLOW COPY feature is useful when you want to test new data models or perform operations on existing tables without risking live data. After testing or modifying the copied table, it can be easily deleted or promoted to the main table.

Creating a shallow table copy is orders of magnitude faster and uses less disk space than creating a table (CREATE TABLE new_table LIKE original_table) and then inserting all the rows from the original table into the new table (INSERT INTO new_table...SELECT * FROM original_table). For example, it's possible to shallow copy a large table in a second whereas a full copy would take minutes.

When a shallow copy of a table is created, SingleStore copies some of the in-memory metadata of the table from which the copy is created ("source table"), i.e the columnar blobs and index blobs. However the in-memory rowstore portion of the source table is not copied. Therefore, the memory utilization of the copy at the time of creation is bounded by the memory utilization of the source table. Post that, any changes made to the copy take up additional memory similar to any other columnstore table.

To promote a shallow copy table to a main table, drop the original table and then rename the shallow copy table to the original table name. This approach is faster for resuming query operations on the table. For optimal performance, ensure that autostats is enabled and that the background merger is turned on by executing ALTER TABLE col_table BACKGROUND_MERGER=ON; before using the table.

When creating a shallow copy of an existing table:

  • The plancache of the source table is not reused.

  • Only the on-disk portion of the table is copied. In-memory rowstore segment rows of the table are not copied. If you want the in-memory rowstore rows, do OPTIMIZE TABLE tbl_name FLUSH on the source table before the shallow copy.

  • Autostats on the new table are disabled. As a result, queries on the new table may run with a worse execution plan. See Disabling and Enabling Automatic Statistics for how to enable autostats for the new table.

  • The background merger is disabled for the new table. This can be changed by running an ALTER TABLE statement on the new table to enable it after the table is created:

    CREATE TABLE ctsc_table LIKE orig_table WITH SHALLOW COPY;
    ALTER TABLE ctsc_table BACKGROUND_MERGER=ON;
  • An exclusive lock is taken on the original table which blocks operations on the table while a shallow copy is created.

  • To verify the memory usage of a shallow copy table, use the TABLE_STATISTICS and INTERNAL_TABLE_STATISTICS views, just as with any other table.

  • After a shallow copy is created, it is treated like any other columnstore table. This means that information about shallow copies is not specifically tracked, and currently it is not possible to retrieve a list of all shallow copy tables from information_schema.

CREATE TABLE WITH SHALLOW COPY Performance Example

This example creates a table ctsc_r with 4,194,304 rows, then does a shallow copy of it, and a full copy of it using a INSERT INTO...SELECT statement. The shallow copy is over 200 times faster on a small test system.

First, create a table of dummy random id values .

CREATE TABLE ctsc_r(id BINARY(16));
INSERT ctsc_r VALUES (sys_guid());
DELIMITER //
DO DECLARE
c BIGINT;
BEGIN
SELECT COUNT(*) INTO c FROM ctsc_r;
WHILE (c < 4*1024*1024) LOOP
INSERT INTO ctsc_r SELECT sys_guid() FROM ctsc_r;
SELECT COUNT(*) INTO c FROM ctsc_r;
END LOOP;
END //
DELIMITER ;
SELECT COUNT(*) FROM ctsc_r;
+----------+
| COUNT(*) |
+----------+
| 4194304  |
+----------+

Make a shallow copy of all rows of ctsc_r to ctsc_r2:

OPTIMIZE TABLE ctsc_r FLUSH;
CREATE TABLE ctsc_r2 LIKE ctsc_r WITH SHALLOW COPY;
/* shallow copy time = 0.02 sec */
SELECT COUNT(*) FROM ctsc_r2;
+----------+
| COUNT(*) |
+----------+
| 4194304  |
+----------+

All rows were copied to ctsc_r2 and took 0.02 seconds to execute.

Next, make a full copy of all rows of ctsc_r to ctsc_r3:

CREATE TABLE ctsc_r3 LIKE ctsc_r;
INSERT INTO ctsc_r3 SELECT id FROM ctsc_r;
/* full copy time = 4.86 sec */
SELECT COUNT(*) FROM ctsc_r3;
+----------+
| COUNT(*) |
+----------+
| 4194304  |
+----------+

All rows were copied to ctsc_r3 ; however, it took almost 5 seconds to execute.

Restrictions

The WITH SHALLOW COPY option is not supported for the following operations: copying across databases, copying rowstore tables, or copying temporary tables. Error messages will be generated if these cases are attempted.

Across databases:

CREATE TABLE test1.orig_table (a BIGINT, b BIGINT, SHARD KEY(a), SORT KEY(b));
CREATE TABLE test2.ctsc_table LIKE test1.orig_table WITH SHALLLOW COPY;
ERROR 1706 (HY000): Feature 'shallow copy of a table across databases' is not supported by SingleStore.

Rowstore tables:

CREATE ROWSTORE TABLE orig_table (a BIGINT, b BIGINT, SHARD KEY(a));
CREATE TABLE ctsc_table LIKE orig_table WITH SHALLOW COPY;
ERROR 1706 (HY000): Feature 'shallow copy of non-columnstore tables' is not supported by SingleStore.

Temporary or rowstore global temporary tables:

CREATE ROWSTORE GLOBAL TEMPORARY TABLE orig_table (a BIGINT, b BIGINT, SHARD KEY(a));
CREATE TABLE ctsc_table LIKE orig_table WITH SHALLOW COPY;
ERROR 1706 (HY000): Feature 'shallow copy of temporary and global temporary tables' is not supported by SingleStore.

CREATE TABLE with COMPRESSION = SPARSE

SingleStore supports sparse data compression for rowstore tables. Nullable structured columns can use sparse data compression. The data types of these columns include numbers, dates, datetimes, timestamps, times, and varchars.

Columns that use sparse data compression only store non-NULL data values. Example 4 discusses an excellent sparse data compression use case, which also includes the query to retrieve actual memory usage of rowstore tables that use sparse data compression.

Sparse compression has the following limitations:

  • The SPARSE clause cannot be used for key columns. However, if a rowstore table uses sparse data compression using the COMPRESSION = SPARSE clause, then the key columns are stored in-row.

  • The SPARSE clause cannot be used for columns where the non-NULL size of the column is greater than 15 bytes.

Refer to the Data Types topic for details.

CREATE TABLE with COMPRESSION = SPARSE All Sparse Columns

The following example demonstrates the COMPRESSION = SPARSE clause. This clause indicates that all columns in the table will use sparse data compression.

CREATE ROWSTORE TABLE transaction_1(
id BIGINT NOT NULL,
explanation VARCHAR(70),
shares DECIMAL(18, 2),
share_price DECIMAL(18, 2),
total_amount as shares * share_price PERSISTED DECIMAL(18,2),
transaction_date DATE,
dividend_exdate DATE,
misc_expenses DECIMAL(18, 2),
country_abbreviation CHAR(6),
correction_date DATE,
settlement_date DATE
) COMPRESSION = SPARSE;

CREATE TABLE with COMPRESSION = SPARSE Selected Sparse Columns

The following example demonstrates the SPARSE clause. This clause is applied to the columns that will use sparse data compression.

CREATE ROWSTORE TABLE transaction_2(
id BIGINT NOT NULL,
explanation VARCHAR(70) SPARSE,
shares DECIMAL(18, 2) SPARSE,
share_price DECIMAL(18, 2),
total_amount as shares * share_price PERSISTED DECIMAL(18,2),
transaction_date DATE,
dividend_exdate DATE SPARSE,
misc_expenses DECIMAL(18, 2) SPARSE,
country_abbreviation CHAR(6),
correction_date DATE SPARSE,
settlement_date DATE SPARSE
);

Listing Whether Columns use Sparse Compression

The following query lists the columns in the transaction table that was created in Example 2. The query indicates, for each column, whether the column uses sparse compression.

SELECT column_name, is_sparse FROM information_schema.columns
WHERE table_name = 'transaction_2';
+----------------------+-----------+
| column_name          | is_sparse |
+----------------------+-----------+
| id                   | NO        |
| explanation          | YES       |
| shares               | YES       |
| share_price          | NO        |
| total_amount         | NO        |
| transaction_date     | NO        |
| dividend_exdate      | YES       |
| misc_expenses        | YES       |
| country_abbreviation | NO        |
| correction_date      | YES       |
| settlement_date      | YES       |
+----------------------+-----------+

CREATE TABLE with COMPRESSION = SPARSE Use Case

Sparse rowstore compression works best on a wide table with more than half NULL values. The distribution of the NULL values in the table does not contribute to the amount of memory used.

For example, consider this wide table t having three-hundred columns:

CREATE ROWSTORE TABLE ct_sparse (
c1 double,
c2 double,
c300 double) COMPRESSION = SPARSE;

In SingleStore 7.3, table t was loaded with 1.05 million rows, two-thirds of which are NULL. To retrieve the actual memory usage (in GB) of table t, run the following command:

SELECT table_name, SUM(memory_use) memory_usage FROM information_schema.table_statistics
WHERE table_name = 'ct_sparse' GROUP BY table_name;
+-------------+--------------+
| table_name  | memory_usage |
+-------------+--------------+
| ct_sparse   |         1.23 |
+-------------+--------------+

The following table lists the memory usage of table t, with and without sparse compression:

Compression Setting

Memory Use

Savings (Percent)

NONE

2.62 GB

NA

SPARSE

1.23 GB

53%

For this wide table with two-thirds NULL values, you can store more than twice the data in the same amount of RAM.

Last modified: December 18, 2024

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