This topic describes how to use the CREATE TABLE statement to create a table in AnalyticDB for MySQL.

CREATE TABLE [IF NOT EXISTS] table_name
  ({column_name column_type [column_attributes] [ column_constraints ] [COMMENT 'string']
  | table_constraints}
   [, ... ]  )
   table_attribute
   [partition_options]
   [AS] query_expression
   COMMENT 'string'

column_attributes:
   [DEFAULT default_expr]
   [AUTO_INCREMENT]

column_constraints:
   [{NOT NULL|NULL} ]
   [PRIMARY KEY]

table_constraints:
   [{INDEX|KEY} [index_name] (column_name,...)]
   [PRIMARY KEY [index_name] (column_name,...)]
   [CLUSTERED KEY [index_name] (column_name,...)]

table_attribute:
   DISTRIBUTED BY HASH(column_name,...) | DISTRIBUTED BY BROADCAST

partition_options:
  PARTITION BY 
        {VALUE(column_name) | VALUE(date_format(column_name, ?)}
  LIFECYCLE N

Parameters

Parameter Description
table_name The name of the table.

The table name must be 1 to 127 characters in length and can contain letters, digits, and underscores (_). The table name must start with a letter or underscore (_).

Specify the table name in the db_name.table_name format to distinguish tables that have the same name across different databases.

column_name The name of the column.

The column name must be 1 to 127 characters in length and can contain letters, digits, and underscores (_). The table name must start with a letter or underscore (_).

column_type The data type of the column to be added.

For more information about the data types supported by AnalyticDB for MySQL, see Data types.

column_attributes
  • DEFAULT default_expr: the default value of the column. The value of DEFAULT is an expression without variables, such as current_timestamp.

    If this parameter is not specified, the default value is NULL.

  • AUTO_INCREMENT: Optional. Specifies whether the column is an auto-increment column.

    The data type of an auto-increment column must be BIGINT because AnalyticDB for MySQL provides unique values for an auto-increment column. However, these values are not incremented in sequence.

column_constraints
  • NOT NULL|NULL: specifies whether the column accepts the NULL value. A value of NOT NULL indicates that the column does not accept the NULL value. A value of NULL indicates that the column accepts the NULL value. Default value: NULL.
  • PRIMARY KEY: the primary key of the column.

    You can define one or more primary keys in the PRIMARY KEY(column_name [, ... ]) format.

table_constraints INDEX|KEY: the inverted index.

AnalyticDB for MySQL automatically creates indexes for tables. You do not need to manually create an index.

PRIMARY KEY The index for the primary keys.
  • Only tables with primary keys support the DELETE and UPDATE operations.
  • The primary keys must include the partition key. We recommend that you place the partition key before the primary key combination.
CLUSTERED KEY The clustered index that defines the aggregate columns used for sorting data in the table. The logical order of the key values in the clustered index determines the physical order of the corresponding rows in the table. You can create only one clustered index for each table.

For example, clustered key col5_col6_cls_index(col5,col6) specifies the col5 col6 clustered index. col5 col6 and col6 col5 are different clustered indexes.

A clustered index can sort the entire table. For example, seller_id is the clustered index for an e-commerce transaction table. Each seller can use the seller_id clustered index in the WHERE condition to access only their own data. This method eliminates random access to data and improves the efficiency of data queries. Content Delivery Network (CDN) users can use the user_id aggregate column to sort global data. In practice, CDN users can quickly access their own logs in a more efficient manner.

Aggregate columns have the following limits:

  • You can create only one clustered index for each table.
  • Clustered indexes sort the entire table and cause lower data write performance and high CPU utilization. Therefore, we recommend that you do not use clustered indexes.
  • Clustered indexes are independent from Index Condition Pushdown (ICP).
DISTRIBUTED BY HASH(column_name,...) The distribution key of the fact table. The data of the table is distributed based on the hash value of the columns specified by column_name.

AnalyticDB for MySQL allows you to select multiple fields as the partition key.

DISTRIBUTED BY BROADCAST The dimension table. The dimension table is stored on each node of a cluster. For performance reasons, we recommend that you do not store large amounts of data in the dimension table.
partition_options The options for fact table partitions.

AnalyticDB for MySQL manages the lifecycle of tables based on the LIFECYCLE N parameter. That is, AnalyticDB for MySQL only stores N number of partitions. All other partitions are deleted.

For example, PARTITION BY VALUE(column_name) indicates that the table is partitioned based on the column specified by column_name. PARTITION BY VALUE(DATE_FORMAT(column_name, '%Y%m%d')) indicates that the table is partitioned based on the column specified by column_name after the column is formatted to a date format such as 20190101. LIFECYCLE 365 indicates that a maximum of 365 partitions can be retained on each node. That is, only data of the last 365 days is stored. When you write data on the 366th day, the data from the first day is deleted.

Precautions

  • AnalyticDB for MySQL clusters use the UTF-8 encoding format during table creation. This encoding format is equivalent to the utf8mb4 format in MySQL. AnalyticDB for MySQL does not support other encoding formats.
  • The maximum number of tables that can be created in a cluster varies with the following AnalyticDB for MySQL editions:
    • Cluster Edition: min (256 × Number of node groups, 10000)
    • Basic Edition:
      • T8: 500
      • T16 and T32: 1,500
      • T52: 2,500

Examples

  • Create a test table.
    create table test (
           id bigint auto_increment,
           name varchar,
           value int,
           ts timestamp
    )
    DISTRIBUTED BY HASH(id)                  

    The test table is a fact table. The id column is an auto-increment column. The distribution key is id. The data of the table is distributed based on the hash value of the id column.

  • Create a customer table.
    CREATE TABLE customer (
    customer_id bigint NOT NULL COMMENT 'Customer ID',
    customer_name varchar NOT NULL COMMENT 'Customer name',
    phone_num bigint NOT NULL COMMENT 'Phone number',
    city_name varchar NOT NULL COMMENT 'City',
    sex int NOT NULL COMMENT 'Gender',
    id_number varchar NOT NULL COMMENT 'ID card number',
    home_address varchar NOT NULL COMMENT 'Home address',
    office_address varchar NOT NULL COMMENT 'Office address',
    age int NOT NULL COMMENT 'Age',
    login_time timestamp NOT NULL COMMENT 'Logon time',
    PRIMARY KEY (login_time,customer_id,phone_num)
     )
    DISTRIBUTED BY HASH(customer_id)
    PARTITION BY VALUE(DATE_FORMAT(login_time, '%Y%m%d')) LIFECYCLE 30
    COMMENT 'Customer information table';                   

    The customer table is a fact table. In the table, the distribution key is customer_id. The partition key is login_time. login_time, customer_id, and phone_num form the primary key combination.

MySQL syntax compatibility

The standard CREATE TABLE syntax of AnalyticDB for MySQL must contain the DISTRIBUTED BY ... clause. The CREATE TABLE syntax of MySQL does not contain the DISTRIBUTED BY ... clause. By default, AnalyticDB for MySQL is compatible with the CREATE TABLE syntax of MySQL. You can use one of the following methods to manage the compatibility issues caused by the DISTRIBUTED BY ... clause:

  • By default, if a MySQL table contains a primary key, AnalyticDB for MySQL uses the primary key as DISTRIBUTED BY COLUMN.
    mysql> create table t (c1 bigint, c2 int, c3 varchar, primary key(c1,c2));
    Query OK, 0 rows affected (2.37 sec)
    mysql> show create table t;
    +-------+-------------------------------------------------------------------------------------------------------------------------------+
    | Table | Create Table                                                                                                                  |
    +-------+-------------------------------------------------------------------------------------------------------------------------------+
    | t     | Create Table `t` (
     `c1` bigint,
     `c2` int,
     `c3` varchar,
     primary key (c1,c2)
    ) DISTRIBUTED BY HASH(`c1`,`c2`) INDEX_ALL='Y' |
    +-------+-------------------------------------------------------------------------------------------------------------------------------+
    1 row in set (0.04 sec)
  • If a MySQL table does not contain a primary key, AnalyticDB for MySQL automatically adds the __adb_auto_id__ field to the table and uses this field as the primary key and DISTRIBUTED BY COLUMN.
    mysql> create table t (c1 bigint, c2 int, c3 varchar);
    Query OK, 0 rows affected (0.50 sec)
    mysql> show create table t;
    +-------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
    | Table | Create Table                                                                                                                                                                              |
    +-------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
    | t     | Create Table `t` (
     `c1` bigint,
     `c2` int,
     `c3` varchar,
     `__adb_auto_id__` bigint AUTO_INCREMENT,
     primary key (__adb_auto_id__)
    ) DISTRIBUTED BY HASH(`__adb_auto_id__`) INDEX_ALL='Y' |
    +-------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
    1 row in set (0.04 sec)

Specify storage policies of cold and hot data when you create a table

Note Only AnalyticDB for MySQL elastic clusters support the tiered storage of hot and cold data feature.

AnalyticDB for MySQL allows you to specify storage policies of cold and hot data when you create a table.

CREATE TABLE [IF NOT EXISTS] table_name
  ({column_name column_type [column_attributes] [ column_constraints ] [COMMENT 'string']
  | table_constraints}
   [, ... ]  )
   table_attribute
   [partition_options]
   [storage_policy]
   [AS] query_expression
   COMMENT 'string'
   
storage_policy:
   STORAGE_POLICY= 'HOT'|'COLD'|'MIXED' [hot_partition_count=N]
Example 1: Specify the storage policy of cold data when you create a table.
Create Table test_table (
 L_ORDERKEY bigint NOT NULL,
 L_LINENUMBER int NOT NULL,
 L_SHIPDATE date NOT NULL,
 dummy varchar,
 primary key (l_orderkey,l_linenumber,l_shipdate)
) DISTRIBUTE BY HASH(l_orderkey) 
PARTITION BY VALUE(date_format(l_shipdate, '%Y%m')) LIFECYCLE 200 INDEX_ALL='Y' 
STORAGE_POLICY='COLD';
Example 2: Specify the storage policy of hot data when you create a table.
Create Table test_table (
 L_ORDERKEY bigint NOT NULL,
 L_LINENUMBER int NOT NULL,
 L_SHIPDATE date NOT NULL,
 dummy varchar,
 primary key (l_orderkey,l_linenumber,l_shipdate)
) DISTRIBUTE BY HASH(l_orderkey) 
PARTITION BY VALUE(date_format(l_shipdate, '%Y%m')) LIFECYCLE 200 INDEX_ALL='Y' 
STORAGE_POLICY='HOT';
Example 3: Specify a mixed storage policy and set the number of hot partitions to 16 when you create a table.
Create Table test_table (
 L_ORDERKEY bigint NOT NULL,
 L_LINENUMBER int NOT NULL,
 L_SHIPDATE date NOT NULL,
 dummy varchar,
 primary key (l_orderkey,l_linenumber,l_shipdate)
) DISTRIBUTE BY HASH(l_orderkey) 
PARTITION BY VALUE(date_format(l_shipdate, '%Y%m')) LIFECYCLE 200 INDEX_ALL='Y' 
STORAGE_POLICY='MIXED' HOT_PARTITION_COUNT=16;

Create a table that has a vector index

AnalyticDB for MySQL allows you to create an ann index synchronously when you create a table.

Syntax
ann index [index_name] (col_name,...)] [algorithm=HNSW_PQ ] [dis_function=SquaredL2]
Example
CREATE TABLE fact_tb (  
xid bigint not null,  
cid bigint not null,  
uid varchar not null,  
vid varchar not null,  
wid varchar not null,  
short_feature array < smallint >(32),  
float_feature array < float >(32),  
ann index short_feature_index(short_feature), 
ann index float_feature_index(float_feature),  
PRIMARY KEY (xid, cid, vid)
) DISTRIBUTE BY HASH(xid) PARTITION BY VALUE(cid) LIFECYCLE 4
Parameters
  • short_feature/float_feature: the name of the vector column. You can customize this parameter value.
  • array<float>(32): the data type of the vector column and the dimension of the vector. You can customize this parameter value. You must specify the dimension of the vector. Valid values: float, byte, and short. Define the type of the feature_data column as 512. Example:
    feature_data` array<float>(512)
  • ann: the system keyword
  • index: the system keyword
  • short_feature_index/float_feature_index: the name of the index. You can customize this parameter value. Create a vector index on the feature_data column:
    ann index ecnn_index(`FEATURE_DATA`) algorithm=HNSW_PQ dis_function=SquaredL2

    You can ignore the algorithm and dis_function parameters. The default value of the algorithm parameter is HNSW_PQ. The default value of the dis_function parameter is SquaredL2.

  • algorithm: the algorithm used by the formula to calculate the vector distance. The following table lists the algorithm of the calculation formula of vector distance supported by AnalyticDB for MySQL.
    Algorithm Scenario Supported data type
    HNSW_PQ This algorithmis suitable for scenarios of medium-scale data volume, in which the data volume of a single table ranges from millions to tens of millions and is sensitive to the vector dimension. short[], byte[], and float[]
  • dis_function: the calculation formula of vector distance. Default value: SquaredL2. The following table lists the calculation formula of vector distance supported by AnalyticDB for MySQL.
    Calculation formula of distance Calculation formula Supported data type
    SquaredEuclidean (SquaredL2) (x1-y1)^2+(x2-y2)^2+… byte[], short[], or float[]
Use the vector index to retrieve queries
  1. Query the last five records of the vector '[1,1,1,1]':
    select id, l2_distance(short_feature, '[1,1,1,1]') from fact_tb order by 2 limit 5;
  2. Query the last five records of the vector '[1,1,1,1]' by using the vector index, and sort the records by distance:
    select id, l2_distance(short_feature, '[1,1,1,1]') from fact_tb where xid = 1 and cid = 0 order by 2 limit 5;
  3. Query the last five records of the vector '[1,1,1,1]' by using the vector index, sort the records by distance, and set the maximum range of distance:
    select id, l2_distance(float_feature, '[1.2,1.5,2,3.0]') from fact_tb where l2_distance(float_feature, '[1.2,1.5,2,3.0]') < 50.0 and xid = 2 order by 2 limit 5;