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) }
<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>,...)
[<index_option>] ...
| SORT KEY (<index_column_name>,... [DESC])
| FULLTEXT [<index_name>] (<index_column_name>,...)
<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
<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

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 rowstore 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.

  • 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.

  • The only charset_name supported by SingleStore is utf8.

  • 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.

  • <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.

  • 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. If the column is of the type TIMESTAMP, TIMESTAMP(6), DATETIME , or DATETIME(6), then you can update <default_value> to one of the following values: CURRENT_TIMESTAMP(), CURRENT_TIMESTAMP(6), NOW(), or NOW(6). For more information, see Data Types.

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.

AUTO_INCREMENT Behavior

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.

Examples

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

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.

Examples

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.

Examples

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 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).

Example 1

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 |
+----+---------------------+

Example 2

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      |
+-------------+

COMPRESSION = SPARSE and SPARSE behavior

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.

Examples

Example 1: Creating a Rowstore Table Having 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;

Example 2: Creating a Rowstore Table Having 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
);

Example 3: 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       |
+----------------------+-----------+

Example 4: An Excellent Sparse Compression 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.

FULLTEXT behavior

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 during CREATE TABLE and only on the text types CHAR, VARCHAR, TEXT, and LONGTEXTData Types

Warning

A FULLTEXT index cannot be dropped or altered after the table is created, and if the table is dropped, the index is deleted automatically.

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.

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

Examples

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.

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

USING HASH behavior

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

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

  • When you create a unique 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.

  • 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 only single-column hash indexes.

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

Example

The following example creates a columnstore table with three hash indexes that each have a one-column key.

CREATE TABLE articles_2 (
id 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 (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; does not use the hash index on 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.

Using HASH behavior for multiple columns

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

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) USING HASH, KEY(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.

Last modified: March 8, 2024

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