Create an offline physical table - Dataphin - Alibaba Cloud Documentation Center

Offline physical tables let you centrally configure and manage tables used in compute task development.

Limitations

Setting the data standard field in tables requires the data standard module.
Setting the data classification and data categorization fields in tables requires the asset security module.
The supported compute engines are MaxCompute, Hadoop, Lindorm, Databricks, GaussDB(DWS), TDH 6.x, TDH 9.3.x, and AnalyticDB for PostgreSQL.
In multi-engine mode, table management supports only projects bound to a compute source of type MaxCompute, Hadoop, AnalyticDB for PostgreSQL, GaussDB(DWS), Databricks, Lindorm (compute engine), TDH 6.x, or TDH 9.3.x.

Create offline physical table

Step 1: Configure basic information

In the top menu bar of the Dataphin homepage, select Develop > Data Development.
In the top menu bar, select a project. In Dev-Prod mode, you must also select an environment.
In the navigation pane on the left, select Data Processing > Table Management.
In the table management list, click the icon, and select Offline physical table.

In the Create Physical Table wizard, configure the following parameters. The required parameters vary depending on the compute engine.

MaxCompute

Parameter	Description
Table Name	Enter a name for the offline physical table. The name can contain only letters, digits, and underscores (_) and must be 128 characters or fewer.
Directory	Select the directory for the offline physical table. If no directory exists, you can create one by following these steps: Above the compute task list on the left side of the page, click the icon to open the New Folder dialog box. In the New Folder dialog box, enter a Name, set Type to Offline, and select a parent directory as needed. Click OK.
Data Domain (Optional)	Select the data domain for the table. If none are available, Create a data domain.
Description (Optional)	Enter a brief description of the table, up to 1,000 characters.

Hadoop

Parameter	Description
Table Name	Enter a name for the offline physical table. The name can contain only letters, digits, and underscores (_) and must be 128 characters or fewer.
Directory	Select the directory for the offline physical table. If no directory exists, you can create one by following these steps: Above the compute task list on the left side of the page, click the icon to open the New Folder dialog box. In the New Folder dialog box, enter a Name, set Type to Offline, and select a parent directory as needed. Click OK.
Data Domain (Optional)	Select the data domain for the table. If none are available, Create a data domain.
Description (Optional)	Enter a brief description of the table, up to 1,000 characters.
Storage Format	Select a storage format for the offline physical table. The following formats are supported. hudi and delta (Delta Lake): You can select these formats if and only if Spark SQL is enabled for the compute source of the project. If Spark SQL is not enabled for the compute source of the current project but the default storage format in the Develop > Table Management settings is set to hudi or delta (Delta Lake), then the storage format here defaults to Engine Default (you can specify another format in the CREATE TABLE statement). If you select hudi, the storage format clause in the DDL statement is `using hudi`. If you select delta (Delta Lake), the clause is `using delta`. Paimon Iceberg Parquet: The storage format clause in the DDL statement is `stored as parquet`. Avro: The storage format clause in the DDL statement is `stored as avro`. Rcfile: The storage format clause in the DDL statement is `stored as rcfile`. Orc: The storage format clause in the DDL statement is `stored as orc`. Textfile: The storage format clause in the DDL statement is `stored as textfile`. Sequencefile: The storage format clause in the DDL statement is `stored as sequencefile`.

Lindorm

Parameter	Description
Table Name	Enter a name for the offline physical table. The name can contain only letters, digits, and underscores (_) and must be 128 characters or fewer.
Directory	Select the directory for the offline physical table. If no directory exists, you can create one by following these steps: Above the compute task list on the left side of the page, click the icon to open the New Folder dialog box. In the New Folder dialog box, enter a Name, set Type to Offline, and select a parent directory as needed. Click OK.
Data Domain (Optional)	Select the data domain for the table. If none are available, Create a data domain.
Description (Optional)	Enter a brief description of the table, up to 1,000 characters.
Storage Format	Select the storage format. Defaults to the format in Develop > Table Management settings. Supported formats: Engine default (Can be overridden in the CREATE TABLE statement): The CREATE TABLE statement does not specify a storage format (using or stored as). Iceberg Parquet Avro Rcfile Orc Textfile Sequencefile

Databricks

Parameter	Description
Table Name	Enter a name for the offline physical table. The name can contain only letters, digits, and underscores (_) and must be 128 characters or fewer.
Directory	Select the directory for the offline physical table. If no directory exists, you can create one by following these steps: Above the compute task list on the left side of the page, click the icon to open the New Folder dialog box. In the New Folder dialog box, enter a Name, set Type to Offline, and select a parent directory as needed. Click OK.
Data Domain (Optional)	Select the data domain for the table. If none are available, Create a data domain.
Description (Optional)	Enter a brief description of the table, up to 1,000 characters.
Storage Format	Select the storage format. Defaults to the format in Develop > Table Management settings. Supported formats: Engine default (Can be specified otherwise in the CREATE TABLE statement): The CREATE TABLE statement lacks a storage format clause (using or stored as). Avro Binaryfile Csv Delta (Delta Lake) Json Orc Parquet Text

GaussDB (DWS) and AnalyticDB for PostgreSQL

Parameter	Description
Table Name	Enter a name for the offline physical table. The name can contain only letters, digits, and underscores (_) and must be 63 characters or fewer.
Directory	Select the directory for the offline physical table. If no directory exists, you can create one by following these steps: Above the compute task list on the left side of the page, click the icon to open the New Folder dialog box. In the New Folder dialog box, enter a Name, set Type to Offline, and select a parent directory as needed. Click OK.
Data Domain (Optional)	You can select a data domain only if the project is bound to a business segment.
Description (Optional)	Enter a brief description of the table, up to 1,000 characters.

Configure the parameters and then click Next.

Step 2: Configure the field list

Supported storage formats vary by compute engine (table management settings). Field list configurations depend on the storage format, as detailed below.

Note

For Databricks, field list configurations are the same whether the storage format is engine default (which you can specify in a table creation statement) or delta (Delta Lake).

Hudi, delta (Delta Lake), iceberg, or paimon

On the field list configuration page, configure the schema information for the current physical table, such as table fields, data types, and data classification.

Section	Description
① Field list operations	Search: You can search for fields by field name. Edit DDL: Edit the DDL statement for the current physical table. Add Data Field: Click Add Data Field and fill in the field name, data type, and description in the new row. Import from Statement: Import new fields by using a CREATE TABLE statement. Click Import from Statement. In the Import from Statement dialog box, enter the statement, click Parse SQL, select the required fields from the parsed results, and then click Add to import them. Import from Table: Click Import from Table, select the source table and the required fields in the Import from Table dialog box, and click Add.
② Field list	The field list displays field details such as No., field name, data type, description, data standard, data classification, and data sensitivity level. No.: The sequence number of the field. This number increments by 1 for each new field. Field name: The name of the table field. You can search by entering the full name of a root word, and the system automatically matches it with the root words configured in Governance > Data Standard > Root Word. Data type: Supports string, bigint, double, timestamp, decimal, Text, Numeric, Date/Time, and Other data types. Text: varchar, char. Numeric: int, smallint, tinyint, float. Date/Time: date. The MaxCompute compute engine supports datetime. Note The Hadoop compute engine does not support datetime. Other: boolean, binary. Description: The field description. Maximum length: 512 characters. Data standard: Select a data standard for the field. To create a standard, see Create and manage data standards. Data classification: Select a data classification for the field. To create a data classification, see Create a data classification. Data sensitivity level: After you select a data classification, the system automatically identifies the data sensitivity level. You can also delete fields in the Actions column. Note You cannot undo a field deletion.
③ Batch operations	You can select multiple table fields to perform the following batch operations. Delete: Click the icon to delete the selected data fields. Root word naming: Click the icon. The system tokenizes the field description and matches existing root words to recommend field names. In the Root Word Naming dialog box, you can replace the names of the selected fields with the updated values. Note If none of the recommended field names meet your needs, you can modify them in the Modified Field Name input box. Click Reset to revert the Modified Field Name to the system-matched root words. Data standard: Click the icon. The system recommends a data standard based on the field name. In the Data Standard dialog box, you can apply the recommended standard to the fields.

After adding the fields, click Next.

Other formats

On the field list configuration page, configure the schema information for the current physical table, such as table fields, data types, and data classification.

Section	Description
① Field list operations	Search: You can search for fields by field name. Edit DDL: Edit the DDL statement for the current physical table. Add Field: Click Add Field, select a field type (Data Field, partition field, or quick add date partition), and then fill in information such as field name, data type, and description in the new row. Add Data Field: Adds a data field row. partition field: Adds a partition field row. quick add date partition: Adds a date partition row. The default is `ds`. Import from Statement: Import new fields by using a CREATE TABLE statement. Click Import from Statement. In the Import from Statement dialog box, enter the statement, click Parse SQL, select the required fields from the parsed results, and then click Add to import them. Import from Table: Click Import from Table. In the Import from Table dialog box, select the source table and the fields to import, and then click Add.
② Field list	The field list displays field details such as No., field name, data type, description, data standard, data classification, and data sensitivity level. No.: The sequence number of the field. This number increments by 1 for each new field. Field name: The name of the table field. You can search by entering the full name of a root word, and the system automatically matches it with the root words configured in Governance > Data Standard > Root Word. Data type: Supports string, bigint, double, timestamp, decimal, Text, Numeric, Date/Time, and Other data types. Text: varchar, char. Numeric: int, smallint, tinyint, float. Date/Time: date. The MaxCompute compute engine supports datetime. Note The Hadoop compute engine does not support datetime. Other: boolean, binary. Description: The field description. Maximum length: 512 characters. Data standard: Select a data standard for the field. To create a standard, see Create and manage data standards. Data classification: Select a data classification for the field. To create a data classification, see Create a data classification. Data sensitivity level: After you select a data classification, the system automatically identifies the data sensitivity level. You can also delete fields in the Actions column. Note You cannot undo a field deletion.
③ Batch operations	You can select multiple table fields to perform the following batch operations. Delete: Click the icon to delete the selected data fields. Root word naming: Click the icon. The system tokenizes the field description and matches existing root words to recommend field names. In the Root Word Naming dialog box, you can replace the names of the selected fields with the updated values. Note If none of the recommended field names meet your needs, you can modify them in the Modified Field Name input box. Click Reset to revert the Modified Field Name to the system-matched root words. Data standard: Click the icon. The system recommends a data standard based on the field name. In the Data Standard dialog box, you can apply the recommended standard to the fields.

After adding the fields, click Next.

GaussDB (DWS)/AnalyticDB for PostgreSQL

Section	Description
① Field list operations	Search: You can search for fields by field name. Edit DDL: Edit the DDL statement for the current physical table. Add Data Field: Click Add Field and fill in the field name, Data Type (Length), and description in the new row. Import from Statement: Import new fields by using a CREATE TABLE statement. Click Import from Statement. In the Import from Statement dialog box, enter the statement, click Parse SQL, select the required fields from the parsed results, and then click Add to import them. Import from Table: Click Import from Table. In the Import from Table dialog box, select the source table and the fields that you want to import, and click Add.
② Field list	The field list displays field details such as No., field name, Data Type (Length), primary key, not null, description, data standard, data classification, and data sensitivity level. No.: The sequence number of the field. This number increments by 1 for each new field. Field name: The name of the table field. You can search by entering the full name of a root word, and the system automatically matches it with the root words configured in Governance > Data Standard > Root Word. Data Type (Length): You can select from the following types or manually enter a type name if the type you need is not listed. Common types: text, bigint (int8), double precision (float), timestamp without time zone, numeric (decimal) Text: character varying (varchar), character (char), json, xml, uuid Numeric: integer (int/int4), smallint (int2), real (float4), money Date/Time: date, time without time zone, time with time zone, timestamp with time zone, interval Other: boolean, bytea, bit, bit varying (varbit) Some data types require you to specify a length. The constraints are as follows: character varying (varchar): The length must be an integer from 1 to 65535. The default is 512. character (char): The length must be an integer from 1 to 255. The default is 255. numeric (decimal): The precision must be an integer from 1 to 38, and the scale must be an integer from 0 to 18. The defaults are 38 and 18, respectively. timestamp without time zone, timestamp with time zone: The precision must be an integer from 0 to 6. The default is 0. time without time zone, time with time zone: The precision must be an integer from 0 to 6. The default is 0. bit: The length must be an integer from 1 to 1024. The default is 8. bit varying (varbit): The length must be an integer from 1 to 1024. The default is 8. Primary key: This option is available only when the data type is text, character varying (varchar), bigint (int8), smallint (int2), or integer(int/int4). You can select multiple fields to create a composite primary key. Not null: Specifies whether the field can contain null values. Description: The field description. Maximum length: 512 characters. Data standard: Select a data standard for the field. To create a standard, see Create and manage data standards. Data classification: Select a data classification for the field. To create a data classification, see Create a data classification. Data sensitivity level: After you select a data classification, the system automatically identifies the data sensitivity level. You can also delete fields in the Actions column. Note You cannot undo a field deletion.
③ Batch operations	You can select multiple table fields to perform the following batch operations. Delete: Click the icon to delete the selected data fields. Root word naming: Click the icon. The system tokenizes the field description and matches existing root words to recommend field names. In the Root Word Naming dialog box, you can replace the names of the selected fields with the updated values. Note If none of the recommended field names meet your needs, you can modify them in the Modified Field Name input box. Click Reset to revert the Modified Field Name to the system-matched root words. Data standard: Click the icon. The system recommends a data standard based on the field name. In the Data Standard dialog box, you can apply the recommended standard to the fields.

Step 3: Storage

Storage configuration support for the MaxCompute compute engine and the Hadoop compute engine varies by storage format, as shown in the table below.

Hudi

Parameter	Description
Data update type (Optional)	For type, select cow (Copy on Write) or mor (Merge on Read).
Primary key and pre-combine field (Optional)	primaryKey: Select one or more primary keys. You can select any field from the field list. If you select multiple primary keys, they are sorted in the order of selection. preCombineField: Select a field to use as the pre-combine field. You can select any field from the field list.
Data distribution	Enable or disable Partition. This feature is disabled by default. If you enable partitions, you must also select one or more fields for Partitioned By from the field list. Note For Partitioned By, you cannot select all fields from the list.
Location (Optional)	Enter the storage path in the Location field. The path supports global variables and cannot exceed 512 characters. Note If the `CREATE TABLE` statement includes a `location` clause, the table is created as an external table. In this case, the `external` keyword can be omitted.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

For information about the DDL statements for editing Hudi tables in SQL, see SQL DDL and Schema Evolution.

Note

If Location is left empty, the CREATE TABLE statement does not include a location clause.
The Hadoop compute engine uses Spark SQL. The Lindorm compute engine and Databricks use the default SQL dialect of the compute source.

Delta (Delta Lake)

Parameter	Description
Data distribution	Liquid Clustering: Enable or disable Liquid Clustering. This feature is disabled by default. If you enable it, you must also select one or more fields for Cluster By from the field list. Partition: Enable or disable Partition. This feature is disabled by default. If you enable partitions, you must also select one or more fields for Partitioned By from the field list. Note You cannot enable Liquid Clustering and Partition at the same time. For Partitioned By, you cannot select all fields from the list.
Location (Optional)	Enter the storage path in the Location field. Global variables are supported. The path cannot exceed 512 characters. Note If the `CREATE TABLE` statement includes a `location` clause, the table is created as an external table. In this case, the `external` keyword can be omitted.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

For information about the DDL statements for editing Delta tables in SQL, see ALTER TABLE.

Note

If Location is left empty, the CREATE TABLE statement does not include a location clause.
The Hadoop compute engine uses Spark SQL. The Lindorm compute engine and Databricks use the default SQL dialect of the compute source.

Iceberg

Parameter

Description

Partition

This feature is disabled by default. If you enable it, you must configure Partitioned By.

Partitioned By: You can select multiple fields from the field list or enter fields manually. Separate multiple fields with a comma (,).

Location

Enter the storage path in the Location field. Global variables are supported. The path cannot exceed 512 characters.

Note

If the CREATE TABLE statement includes a location clause, the table is created as an external table. In this case, the external keyword can be omitted.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

Note

If Location is left empty, the CREATE TABLE statement does not include a location clause.
The Hadoop compute engine uses Spark SQL. The Lindorm compute engine uses the default SQL dialect of the compute source.

Paimon

Parameter	Description
Primary key	Select one or more primary keys. After you make a selection, you must also configure the Table Mode.
Table mode	For Table Mode (data update type), select MOR, COW, or MOW.
Partition	This feature is disabled by default. If you enable it, you must configure Partitioned By. Partitioned By: You can select one or more fields from the field list.
Location	Enter the storage path in the Location field. Global variables are supported. The path cannot exceed 512 characters. Note If the `CREATE TABLE` statement includes a `location` clause, the table is created as an external table. In this case, the `external` keyword can be omitted.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

Note

If Location is left empty, the CREATE TABLE statement does not include a location clause.
If the current compute engine is the Hadoop compute engine, Spark SQL is used.

Other storage formats

Parameter	Description
Storage type	Select Internal Table or External Table. If you select External Table, you must also configure Location.
Location	Enter the storage path in the Location field. Global variables are supported. The path cannot exceed 512 characters.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

Note

If the current compute engine is the Hadoop compute engine and the storage format is kudu, Impala SQL is used.

MaxCompute

MaxCompute internal table

Parameter	Description
Storage type	Select Internal Table.
Transactional table	Select Yes or No. If you select Yes, you can also configure Primary Key to create the table as a Delta table.
Primary key (Optional)	Select one or more primary keys. You can select any field from the field list. If you select multiple primary keys, they are sorted in the order of selection.
Lifecycle (Optional)	Specifies the table's retention period in days. You can enter a positive integer or select a preset value: 7, 14, 30, or 360.

MaxCompute external table

Parameter	Description
Storage type	Select External Table.
Storage format	Select a storage format. The default value is consistent with the default storage format for external tables in the Development Platform - Table Management settings. Valid values are parquet, avro, rcfile, orc, textfile, and sequencefile.
Location	Enter the storage path in the Location field. Global variables are supported. The path cannot exceed 512 characters.

After you configure the parameters, click Submit. In the Submit dialog box, review the SQL statement for creating the table and click OK and Submit.

GaussDB (DWS)/AnalyticDB for PostgreSQL

Table constraint: Click Add Constraint to add a new constraint row. You must configure Constraint Type, Constraint Settings, and Deferrable Strategy.

Parameter	Description
Constraint type	Select Primary Key, Unique Constraint, or Check Constraint.
Constraint settings	If Constraint Type is set to Primary Key: Select one or more fields with one of the following data types: `text`, `character varying (varchar)`, `bigint (int8)`, `smallint(int2)`, or `integer(int/int4)`. Note A table supports only one primary key constraint. If you already selected a primary key from the field list, the system automatically adds a corresponding table constraint, using the selected fields. If Constraint Type is set to Unique Constraint: Select one or more fields. All fields in the field list are available for selection. If Constraint Type is set to Check Constraint: Enter a string of up to 512 characters.
Deferrable strategy	Select not deferrable, initially immediate, or initially deferred. The default value is not deferrable. Note This parameter is not supported when the constraint type is check constraint.

Click the Delete icon to delete the corresponding constraint row.

Distribution method (Distributed By) (Optional):
- For the AnalyticDB for PostgreSQL compute engine, you can select RANDOMLY, BY(<columns>), or REPLICATED.
- For the GaussDB (DWS) compute engine, you can select REPLICATION, ROUNDROBIN, or BY HASH(<columns>). If you select BY HASH(<columns>), you must also select distribution fields. All fields from the field list are available for selection.
Partition: Click Add Partition to add a partition field. Configure parameters based on the Partition Type. Click the Delete icon to delete the partition field and all its partition data.
- If the partition type is LIST or RANGE:
  - Partition field: Select a partition field or enter an expression manually.
    
    The AnalyticDB for PostgreSQL compute engine (database version 6.x) supports only single-column partitioning. The AnalyticDB for PostgreSQL compute engine (database version 7.x) and the GaussDB (DWS) compute engine support expressions.
  - Partition name and partition value: Click the Add icon to add a data partition row. Click the Delete icon to delete the corresponding data partition row.
    Note
    
    When the compute engine is AnalyticDB for PostgreSQL (database version 6.x), the system automatically adds a default partition. The name for this default partition is optional. However, if you leave the name empty, you must add at least one other data partition.
    
    When the compute engine is GaussDB (DWS), you must add at least one data partition.
    
    When the compute engine is AnalyticDB for PostgreSQL (database version 7.x), you do not need to add any data partitions.
    - Partition name: Must contain only letters, digits, and underscores (_) and be no more than 63 characters long.
      
      Note
      A partition is a table in itself, and the default format for a full partitioned table name is {main_table_name}_{partition_level#}_prt_{partition_name}.
    - Partition value:
      - If the partition type is LIST: Enter a string of up to 512 characters. If the value is a text type (for example, text, varchar, or char), it must be enclosed in single quotation marks ('').
      - If the partition type is RANGE: You must configure START, END, and EVERY. Enter a string of up to 512 characters. If the value is a text type (for example, text, varchar, or char), it must be enclosed in single quotation marks ('').
        
        For START and END, you must also select INCLUSIVE or EXCLUSIVE. START defaults to INCLUSIVE, and END defaults to EXCLUSIVE.
      Note
      The partition value must be compatible with the data type of the partition field.
- If the partition type is HASH: You only need to configure partition fields. You do not need to configure data partitions. The partition field configuration is the same as for the LIST and RANGE types.
Note
- Tables with a REPLICATED distribution method do not support partitioning.
- Multi-level partitioning is not supported when the compute engine is GaussDB (DWS).
- You can select HASH as the partition type only when the compute engine is AnalyticDB for PostgreSQL (database version 7.x).

Import data

After you create an offline physical table, you can import data.

In the table management list, click the target offline physical table. You can search for the table by name.
On the table details page, click Import Data to open the Import Data dialog box.

In the Basic configurations step of the Import Data dialog box, upload your data file and configure the import parameters.

Parameter	Description
Upload file	Click Select file to upload the data file you want to import. Only .txt and .csv files up to 10 MB are supported.
Delimiter	The character that separates values in your data file. Supported delimiters include comma (,), tab (\t), vertical bar (\|), and forward slash (/). You can also specify a custom delimiter.
Character encoding	Select the character encoding of the uploaded data file. Supported encodings include UTF-8 (without BOM), UTF-8 (with BOM), GBK, Big5, GB2312, ASCII, and UTF-16.
Header row	Select this option if the first row of your data file contains column headers.
Target partition	For a partitioned table, you must enter the target partition name.

Click Next.
In the Import Data step, configure the field mapping.
- Mapping:
  - Same-row mapping: Maps source columns to destination fields by their order.
  - Same-name mapping: Maps source columns to destination fields by matching their names.
- Imported file data column: You can map a destination field to a source column, a null value (NULL), or a fixed value.
Click Start Import to begin the import process.

Edit an offline physical table

After you submit an offline physical table, you can edit its properties.

In the table management list, click the target offline physical table. You can search for the table by its name.

On the table details page, click Edit to open the Edit Physical Table page.

Editable parameters vary by storage format, as shown below.

Hudi

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit or delete the names and data types of any field except for hudi system fields. The hudi system fields include: _hoodie_commit_time _hoodie_commit_seqno _hoodie_record_key _hoodie_partition_path _hoodie_file_name Note When you modify field names or data types, or add or delete fields, an error might occur if the engine's configuration does not support the operation.
Storage configuration	You can edit only type, primary key, preCombineField, and Location. The Location can be edited only if the table is an external table.

After you finish editing, click Submit. This action uses the default SQL of the compute source. In the Submit dialog box, review the generated SQL statement and click Confirm and Submit.

Note

If the engine returns an error when you rename, delete, or modify the data type of a field in a hudi table, contact your engine service provider to check the engine settings.

Delta (Delta Lake)

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit and delete existing fields, and add new fields. The field requirements are the same as when you create an offline physical table.
Storage configuration	Data Distribution If Liquid Clustering is enabled, you can disable it or reselect the Cluster By fields. If both Liquid Clustering and Partition are disabled, you can enable Liquid Clustering and specify the Cluster By fields. If both Liquid Clustering and Partition are disabled, you cannot enable Partition. If Partition is enabled, you cannot modify Liquid Clustering, Partition, or Partitioned By. Storage Location: The location can be edited only for an external table.

After you finish editing, click Submit. This action uses the default SQL of the compute source. In the Submit dialog box, review the generated SQL statement and click Confirm and Submit.

Iceberg

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit field names and data types, and add or delete fields. Note When you modify field names or data types, or add or delete fields, an error might occur if the engine's configuration does not support the operation.
Storage configuration	You can edit Location only if the table is an external table.

After you finish editing, click Submit. If the current compute engine is the Hadoop compute engine, the system uses Spark SQL. If the current compute engine is Lindorm (compute engine), the system uses the default SQL of the compute source.

In the Submit dialog box, review the generated SQL statement and click Confirm and Submit.

Paimon

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit field names and data types, and add or delete fields. Note When you modify field names or data types, or add or delete fields, an error might occur if the engine's configuration does not support the operation.
Storage configuration	You can edit Location only if the table is an external table.

After you finish editing, click Submit. This action uses Spark SQL. In the Submit dialog box, review the generated SQL statement and click Confirm and Submit.

MaxCompute

MaxCompute internal table

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit and delete existing fields, and add new fields. The field requirements are the same as when you create an offline physical table. A DDL statement is generated when you modify a data type. You can clear the Not Null checkbox for a field. If the current table is an internal transactional table, you cannot clear the Not Null checkbox for primary key fields. You can only clear the Not Null checkbox (to make a field nullable), not select it.
Storage configuration	You can edit the lifecycle. The requirements are the same as when you create an offline physical table.

MaxCompute external table

Tab	Description
Basic information	You can edit only the Table Name and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit and delete existing fields, and add new fields. The field requirements are the same as when you create an offline physical table. A DDL statement is generated when you modify a data type. You can only clear the Not Null checkbox (to make a field nullable), not select it.
Storage configuration	You can edit the Storage Location (Location). The parameter requirements are the same as when you create an offline physical table.

After you finish editing, click Submit. In the Submit dialog box, review the generated SQL statement and click Confirm and Submit.

Note

If your changes include operations such as deleting a field or modifying a field type, you must first enable schema evolution in your MaxCompute project: setproject odps.schema.evolution.enable=true;.

GaussDB (DWS)/AnalyticDB for PostgreSQL

Tab	Description
Basic information	You can edit only the Table Name, Subject Area, and Description. The parameter requirements are the same as when you create an offline physical table.
Field list	You can edit and delete existing fields, and add new fields. The field requirements are the same as when you create an offline physical table. A DDL statement is generated when you modify a data type. You can modify the Not Null option for fields. You cannot change the primary key here. If you need to modify the primary key, edit the table-level constraints.
Storage configuration	You can edit table-level constraints and the distribution style. The requirements are the same as when you create an offline physical table. For partition information, go to Asset Inventory > Object Details > Fields.

Single-tenant multi-engine

When configuring the field list using import from table, you can import tables only from projects that share the same engine type.

Next steps

In Dev-Prod mode, publish the offline physical table through Manage publish tasks.
In Basic mode, manage submitted tables in the asset catalog.