Getting Started with HTAP Standard Edition

1. Log in to the management console.
2. Click in the upper left corner and select a region and project.
3. Click in the upper left corner of the page and choose Databases > TaurusDB.
4. On the Instances page, locate a TaurusDB instance and click its name to access the Basic Information page.
5. In the navigation pane, choose HTAP Analysis. On the displayed page, click Create HTAP Instance.
6. Set parameters for the standard HTAP instance.
   • Basic configuration
     Figure 1 Basic configuration
     

     Table 2 Basic configuration

     Parameter	Description
     Billing Mode	Select Pay-per-use or Yearly/Monthly.

   • Resource selection
     Figure 2 Resource selection
     

     Table 3 Resource selection

     Parameter	Description
     Instance Edition	Only Standard is available. This edition is developed based on open-source StarRocks.
     HTAP Instance Type	Select Single or Cluster. Single: There is only one FE node and one BE node. It is used only for function experience and testing and does not ensure SLA. Cluster: There are at least three FE or BE nodes and at most 10 FE or BE nodes.
     Storage Type	Select Extreme SSD or Ultra-high I/O. Extreme SSD: uses 25GE network and RDMA technologies to provide you with up to 1,000 MB/s throughput per disk and sub-millisecond latency. Ultra-high I/O: uses disk striping to balance I/O loads among multiple disks to improve read/write bandwidth. The maximum throughput is 1.7 GB/s.
     AZ Type	Only Single-AZ is available.
     AZ	Select an AZ as needed.
     Time Zone	Select a time zone for your instance based on the region hosting your instance. The time zone is selected during instance creation and cannot be changed after the instance is created.
     Security Group	The default value is the security group of the TaurusDB instance. You are advised to keep the security group consistent with that of the TaurusDB instance.

   • Instance options
     Figure 3 Instance options
     

     Table 4 Instance options

     Parameter	Description
     Instance Specifications	Only general-enhanced is available.
     Backend Node Specifications	Select the BE node specifications. The BE nodes are for data storage and SQL computing.
     Backend Node Storage (GB)	Select the storage for BE nodes. The default storage is 50 GB and can be expanded to up to 32,000 GB.
     Backend Nodes	A single-node instance has only one BE node. A cluster instance has 3 to 10 BE nodes. You can apply for a maximum of 10 nodes at once.
     Frontend Node Specifications	Select the FE node specifications. The FE nodes manage metadata, manage client connections, and plan and schedule queries.
     Frontend Node Storage (GB)	Select the storage for FE nodes. The default storage is 50 GB and can be expanded to up to 1,000 GB.
     Frontend Nodes	A single-node instance has only one FE node. A cluster instance has 3 to 10 FE nodes. You can apply for a maximum of 10 nodes at once.

   • Instance configuration
     Figure 4 Instance configuration
     

     Table 5 Instance configuration

     Parameter	Description
     DB Instance Name	The instance name must start with a letter and consist of 4 to 64 characters. Only letters (case-sensitive), digits, hyphens (-), and underscores (_) are allowed.
     Administrator Password	The password must consist of 8 to 32 characters and contain at least three types of the following characters: uppercase letters, lowercase letters, digits, and special characters (~!@#%^*-_=+?,()&$|.). Enter a strong password and periodically change it to improve security and defend against threats such as brute force cracking attempts.
     Confirm Password	Enter the administrator password again.

   • Required duration and quantity
     Figure 5 Required duration and quantity
     

     Table 6 Required duration and quantity

     Parameter	Description
     Required Duration	This parameter is only available for yearly/monthly instances. The system will automatically calculate the fee based on the selected required duration. The longer the required duration is, the larger discount you will enjoy.
     Auto-renew	This parameter is only available for yearly/monthly instances and is not selected by default. If you select this parameter, the auto-renew cycle is determined by the selected required duration.
     Quantity	You can only buy one instance at a time.

7. Click Next in the lower right corner.
   • For pay-per-use instances, go to 8.
   • For yearly/monthly instances, go to 9.
8. Confirm the information and click Submit.

   To modify the instance information, click Previous.

9. Confirm the order.
   • To modify the instance information, click Previous.
   • If you do not need to modify your settings, click Pay Now. On the order page, complete the payment.
10. On the HTAP instance list page, view and manage the HTAP instance.

1. On the Instances page, locate a TaurusDB instance and click its name to access the Basic Information page.
2. In the navigation pane, choose HTAP Analysis.
3. Click the name of an HTAP instance to access the Basic Information page.
4. In the navigation pane, choose Data Synchronization. On the displayed page, click Create Synchronization Task.
5. Configure required parameters.
   Figure 6 Creating a synchronization task
   

   Table 7 Parameter description

   Parameter	Description
   Synchronize Read Replica Data	Controls whether to synchronize full data from a read replica. During a full synchronization, ensure that the read replica is available, or the synchronization will fail and you will need to perform the synchronization again. Yes: Full data is synchronized from the selected read replica, preventing query load on the primary node during a full synchronization. If there is only one read replica, this node is selected by default. No: No synchronization is performed.
   Instance-level Synchronization	Controls whether to synchronize multiple databases. Yes: A synchronization task can synchronize multiple or all databases. No: A synchronization task can synchronize only one database.
   Database Synchronization Scope	This parameter is only available when Instance-level Synchronization is set to Yes. All databases: All databases are synchronized by default. You do not need to specify any database name. Some databases: You need to specify two or more database names.
   Synchronization Task Name	The name can contain 3 to 128 characters. Only letters, digits, underscores (_) are allowed.
   Destination Database	The name can contain 3 to 128 characters. Only letters, digits, underscores (_) are allowed. This parameter is not displayed when Database Synchronization Scope is set to All databases. When Assign Requests to Row and Column Store Nodes is enabled, the source database name must be the same as the destination database name.
   Database to be Synchronized	Select a database that the data will be synchronized to from the drop-down list. You can modify the database parameters of the HTAP instance as required. The drop-down list is hidden when Database Synchronization Scope is set to All databases.
   Synchronization Scope	Select All Tables or Some Tables.
   Wildcard Supported by Table Name	This parameter is only displayed when Instance-level Synchronization is set to Yes and Synchronization Scope is set to Some tables. In an instance-level synchronization scenario, you can determine whether table names in the blacklist or whitelist support wildcards * and ?. The wildcard * matches zero or more characters, and the wildcard ? matches exactly one character.
   Synchronization Scope: Whitelist	If Synchronization Scope is set to Some Tables, you need to configure tables for the blacklist or whitelist. You can set either a blacklist or a whitelist. If you select the whitelist, only the tables in the whitelist are synchronized. If you select the blacklist, the tables in the blacklist are not synchronized. The tables to be synchronized must contain primary keys or a non-empty unique key, or they cannot be synchronized to the HTAP instance. Extra disk space may be used during backend data combination and query. You are advised to reserve 50% of the disk space for the system. When setting the table blacklist or whitelist, you can enter multiple tables in the search box at once. The tables can be separated by commas (,), spaces, or line breaks (\n). After entering multiple tables, you need to click . These tables will be selected by default and displayed in the Selected Table area.
   Configure Table Operations	Enable or disable it as required. Enabled: Select a synchronized table on the left and perform operations on its columns. The operations include order by, key columns, distributed by, partition by, data_model, buckets, replication_num, and enable_persistent_index. Multiple operations are separated by semicolons (;). For details about the syntax, see Table 8. Disabled: No operations are required.

   Table 8 Operation syntax

   Operation Type	Syntax
   order by	order by (column1, column2) or order by column1,column2
   key columns	key columns (column1, column2) or key columns column1,column2
   distributed by	distributed by (column1, column2) buckets 3 NOTE: buckets is optional. If it is not set, the default value is used.
   partition by	There are expression partitions and list partitions. For details, see the partition syntax example.
   data_model	Specifies the table type. The value can be primary key, duplicate key, or unique key. Syntax: data_model=primary key, data_model=duplicate key, or data_model=unique key
   replication_num	replication_num=3 NOTE: The value cannot exceed the number of BE nodes, or the verification fails.
   enable_persistent_index	Specifies whether to make the index persistent. Syntax: enable_persistent_index=true or enable_persistent_index=false
   Combined scenario	data_model=duplicate key;key columns column1, column2;

   Partition syntax example:

   You only need to set a partition expression (time function expression or column expression) when creating a table. During data import, an HTAP instance automatically creates partitions based on the data and the rule defined in the partition expression.

   Partitioning based on a time function expression: If data is often queried and managed based on a continuous date range, you only need to specify a partition column of the date type (DATE or DATETIME) and a partition granularity (year, month, day, or hour) in the time function expression. An HTAP instance automatically creates partitions and sets the start time and end time of the partitions based on the imported data and partition expression.

   Syntax:

   PARTITION BY expression
   ...
   [ PROPERTIES( 'partition_live_number' = 'xxx' ) ]
   
   expression ::=
       { date_trunc ( <time_unit> , <partition_column> ) |
         time_slice ( <partition_column> , INTERVAL <N> <time_unit> [ , boundary ] ) }

   Table 9 Parameter description

   Parameter	Mandatory	Description
   expression	Yes	Currently, only the date_trunc and time_slice functions are supported. If you use time_slice, you do not need to configure the boundary parameter because this parameter can only be set to floor by default. It cannot be set to ceil.
   time_unit	Yes	Partition granularity. Currently, the value can only be hour, day, month, or year. It cannot be week. If the partition granularity is hour, the partition columns can only be of the DATETIME type. They cannot be of the DATE type.
   partition_column	Yes	Partition column. Only the date type (DATE or DATETIME) is supported. If date_trunc is used, the partition column can be of the DATE or DATETIME type. If time_slice is used, the partition column can only be of the DATETIME type. The value of the partition column can be NULL. If the partition column is of the DATE type, the value range is from 0000-01-01 to 9999-12-31. If the partition column is of the DATETIME type, the value range is from 0000-01-01 01:01:01 to 9999-12-31 23:59:59. Currently, only one partition column can be specified.

   Example: If you often query data by day, you can use the partition expression date_trunc (), set the partition column to event_day, and set the partition granularity to day during table creation. In this way, data is automatically partitioned based on dates when being imported. Data of the same day is stored in the same partition. Partition pruning can significantly improve queries.

   CREATE TABLE site_access1 (
       event_day DATETIME NOT NULL,
       site_id INT DEFAULT '10',
       city_code VARCHAR(100),
       user_name VARCHAR(32) DEFAULT '',
       pv BIGINT DEFAULT '0'
   )
   DUPLICATE KEY(event_day, site_id, city_code, user_name)
   PARTITION BY date_trunc('day', event_day)
   DISTRIBUTED BY HASH(event_day, site_id);

   Partitioning based on the column expression: If you often query and manage data based on enumerated values, you only need to specify the column representing the type as the partition column. An HTAP instance automatically divides and creates partitions based on the partition column value of the imported data.

   Syntax:

   PARTITION BY expression
   ...
   [ PROPERTIES( 'partition_live_number' = 'xxx' ) ]
   
   expression ::=
       ( <partition_columns> )
   
   partition_columns ::=
       <column>, [ <column> [,...] ]

   Table 10 Parameter description

   Parameter	Mandatory	Description
   partition_columns	Yes	Partition columns. The value can be a Character (BINARY is not supported), Date, Integer, or Boolean value. The value cannot be NULL. After the import, a partition automatically created can contain only one value of each partition column. If multiple values of each partition column need to be contained, use list partitioning.

   Example: If you often query the equipment room billing details by date range and city, you can use a partition expression to specify the date and city as the partition columns when creating a table. In this way, data of the same date and city is grouped into the same partition, and partition pruning can be used to significantly accelerate queries.

   CREATE TABLE t_recharge_detail1 (
       id bigint,
       user_id bigint,
       recharge_money decimal(32,2), 
       city varchar(20) not null,
       dt varchar(20) not null
   )
   DUPLICATE KEY(id)
   PARTITION BY (dt,city)
   DISTRIBUTED BY HASH(`id`);

   List partitioning

   Data is partitioned based on a list of enumerated values that you explicitly define. You need to explicitly list the enumerated values contained in each list partition, and the values do not need to be consecutive.

   List partitioning is suitable for storing columns where there are a small number of enumerated values and querying and managing data based on the enumerated values. For example, a column indicates a geographical location, status, or category. Each value of a column represents an independent category. Data is partitioned based on the enumerated values of columns to improve query performance and data management. List partitioning is especially suitable for scenarios where a partition needs to contain multiple values of each partition column. For example, the city column in a table indicates the city that an individual is from, and you often query and manage data by state and city. You can use the city column as the partition column for list partitioning when creating a table, and specify that data of multiple cities in the same state is stored in the same partition PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego"), this feature accelerates queries and data management.

   

   Partitions must be created during table creation. Partitions cannot be automatically created during data import. If the table does not contain the partitions corresponding to the data, an error is reported.

   Syntax:

   PARTITION BY LIST (partition_columns)(
       PARTITION <partition_name> VALUES IN (value_list)
       [, ...]
   )
   
   partition_columns::= 
       <column> [,<column> [, ...] ]
   
   value_list ::=
       value_item [, value_item [, ...] ]
   
   value_item ::=
       { <value> | ( <value> [, <value>, [, ...] ] ) }    

   Table 11 Parameter description

   Parameter	Mandatory	Description
   partition_columns	Yes	Partition columns. The value can be a Character (except BINARY), Date (DATE and DATETIME), Integer, or Boolean value. The value cannot be NULL.
   partition_name	Yes	Partition name. You are advised to set proper partition names to distinguish data categories in different partitions.
   value_list	Yes	List of enumerated values of partition columns in a partition.

   Example 1: If you often query the equipment room billing details by state or city, you can specify the city column as the partition column and specify that the cities in each partition belong to the same state. In this way, you can quickly query data of a specific state or city and manage data by state or city.

   CREATE TABLE t_recharge_detail2 (
       id bigint,
       user_id bigint,
       recharge_money decimal(32,2), 
       city varchar(20) not null,
       dt varchar(20) not null
   )
   DUPLICATE KEY(id)
   PARTITION BY LIST (city) (
      PARTITION pCalifornia VALUES IN ("Los Angeles","San Francisco","San Diego"), -- These cities belong to the same state.
      PARTITION pTexas VALUES IN ("Houston","Dallas","Austin")
   )
   DISTRIBUTED BY HASH(`id`);

   Example 2: If you often query the equipment room billing details by date range and state or city, you can specify the date and city as the partition columns when creating a table. In this way, data of a specific date and a specific state or city is grouped into the same partition, to accelerate queries and data management.

   CREATE TABLE t_recharge_detail4 (
       id bigint,
       user_id bigint,
       recharge_money decimal(32,2), 
       city varchar(20) not null,
       dt varchar(20) not null
   ) ENGINE=OLAP
   DUPLICATE KEY(id)
   PARTITION BY LIST (dt,city) (
      PARTITION p202204_California VALUES IN (
          ("2022-04-01", "Los Angeles"),
          ("2022-04-01", "San Francisco"),
          ("2022-04-02", "Los Angeles"),
          ("2022-04-02", "San Francisco")
       ),
      PARTITION p202204_Texas VALUES IN (
          ("2022-04-01", "Houston"),
          ("2022-04-01", "Dallas"),
          ("2022-04-02", "Houston"),
          ("2022-04-02", "Dallas")
      )
   )
   DISTRIBUTED BY HASH(`id`);

6. After the settings are complete, click Create Synchronization Task.
7. Click Back to Synchronization List to return to the data synchronization page. A synchronization task to be synchronized is generated. The task status is Synchronization Stage: Waiting for synchronization.
   Figure 7 Viewing the task status
   

8. To start the task, click Synchronize in the Operation column.

   If the task status changes to Synchronization Stage: Incremental synchronization in progress, the data synchronization is complete.

   

   • During the full synchronization, if some tables fail to be synchronized, an alarm will be generated and those tables will be skipped. The remaining tables will continue to be synchronized. After the full synchronization is complete, the incremental synchronization starts. You can repair tables that failed to be synchronized during the incremental synchronization.
   • When you start a synchronization task, it begins with a full synchronization, during which tables are locked using the FLUSH TABLES WITH READ LOCK command. To minimize the impact on workloads, start synchronization tasks during off-peak hours.
   • During service tests, if you want to suspend a synchronization task, click Stop. The suspension duration cannot exceed the binlog retention period set for the source primary TaurusDB instance. If the suspension duration exceeds the binlog retention period, the synchronization task cannot continue. You need to delete the task and create a new one. Do not suspend synchronization tasks in the production environment to prevent data inconsistency between OLTP and OLAP.

For details about how to connect to a standard HTAP instance and perform OLAP queries, see Connecting to a Standard HTAP Instance Through DAS.