ALTER TABLE

Update a table’s definition or schema.

Syntax

ALTER TABLE <table_name>
[ AT { REF[ERENCE] | BRANCH } <reference_name> ]
{ ADD PRIMARY KEY ( <column_name> [ , ... ] )
  | DROP PRIMARY KEY
  | ADD COLUMNS ( <column_name> <data_type> [ , ... ] )
  | DROP COLUMN <column_name>
  | { ALTER | MODIFY | CHANGE } COLUMN <old_name> <new_name> <data_type>
  | LOCALSORT BY ( <column_name> [ , ... ] )
  | REFRESH METADATA [ IN <catalog_name> ]
    [ FOR PARTITIONS ( <partition_name> = '<value>') ]
    [ { AVOID | AUTO } PROMOTION ]
    [ { FORCE | LAZY } UPDATE ]
    [ { MAINTAIN | DELETE } WHEN MISSING ]
  | FORGET METADATA
  | SET TBLPROPERTIES ( '<property_name>' = '<property_value>' [ , ... ] )
  | UNSET TBLPROPERTIES ( '<property_name>' [ , ... ] )
  | CREATE AGGREGATE REFLECTION <reflection_name> USING  
    { DIMENSIONS ( <column_name> [ , ... ] )
    | MEASURES ( <column_name> ( <aggregation_type> ) [ , ... ] ) )
    | DIMENSIONS ( <column_name> [ , ... ] ) MEASURES ( <column_name> ( <aggregation_type> ) [ , ...  ] ) }
    [ PARTITION BY ( { <column_name> | <partition_transform> } [ , ... ] ) ]
    [ LOCALSORT BY ( <column_name> [ , ... ] ) ]
  | CREATE EXTERNAL REFLECTION <reflection_name> USING <table_name>
  | CREATE RAW REFLECTION <reflection_name> USING DISPLAY ( <column_name> [ , ... ] )
    [ PARTITION BY ( { <column_name> | <partition_transform> } [ , ... ] ) ]
    [ LOCALSORT BY ( <column_name> [ , ... ] ) ]
  | DROP REFLECTION <reflection_name>
  | REFRESH REFLECTIONS
  | ROUTE REFLECTIONS TO { DEFAULT ENGINE | ENGINE { <engine_name> | <engine_uuid> } }
  | { ADD | DROP } PARTITION FIELD { <column_name> | <partition_transform> }
}

Parameters

<table_name> String

The name of the table that you want to alter. The source can be in the scratch directory or in a datalake source.

AT { REF[ERENCE] | BRANCH } <reference_name> String Optional

Specifies the reference at which you want to alter the table. When this parameter is omitted, the current reference is used. REF identifies a specific reference; BRANCH identifies a specific branch.

ADD PRIMARY KEY ( <column_name> [ , ... ] ) String

Specifies to use one or more existing columns as the primary key of a table. Primary keys provide hints to the query planning during join planning. They can be added to Apache Iceberg tables only. Uniqueness of the values in a primary key is not enforced.

DROP PRIMARY KEY String

Removes a table's primary key. The columns that make up the primary key remain in the table.

ADD COLUMNS ( <column_name> <data_type> [ , ... ] ) String

Creates one or more columns that have the specified names, data types, and character limits. The size is an attribute of the data type.

These are the supported primitive types:

BOOLEAN
VARBINARY
DATE
FLOAT
DECIMAL
DOUBLE
INTERVAL
INT
BIGINT
TIME
TIMESTAMP
VARCHAR (the length is always 65536 bytes, and any specified value is ignored)

You can define complex types by using either of these two sets of syntax:

Set 1

struct_type: ROW( name primitive_or_complex_type, .. )
list_type: ARRAY(primitive_or_complex_type)

Examples:

ROW(innerfield INT, anotherinnerfield DOUBLE)
ARRAY(INT)
ROW(innerfield ARRAY(INT))
ARRAY(ROW(innerfield INT))

Set 2

struct_type: STRUCT <name : primitive_or_complex_type, ... >
list_type: { LIST | ARRAY } < primitive_or_complex_type >

Examples:

STRUCT<innerfield : INT, anotherinnerfield : DOUBLE>
LIST<INT>
ARRAY<INT>
STRUCT<innerfield : LIST<INT>>
LIST<STRUCT<innerfield : INT>>

DROP COLUMN <column_name> String

Drops the specified column. This action cannot be undone.

{ ALTER | MODIFY | CHANGE } COLUMN <old_column_name> <new_column_name> <data_type> String

Changes the data type for a column, and gives you the option to rename the column.

Only three types of changes to primitive types are allowed:

INT to BIGINT
FLOAT to DOUBLE
DECIMAL(p, s) to DECIMAL(p', s), if you are widening the precision

You can alter columns that use complex types by using either of these two sets of syntax:

Set 1

struct_type: ROW( name primitive_or_complex_type, .. )
list_type: ARRAY(primitive_or_complex_type)

Examples:

ROW(innerfield INT, anotherinnerfield DOUBLE)
ARRAY(INT)
ROW(innerfield ARRAY(INT))
ARRAY(ROW(innerfield INT))

Set 2

struct_type: STRUCT <name : primitive_or_complex_type, ...>
list_type: { LIST | ARRAY } < primitive_or_complex_type >

Examples:

STRUCT<innerfield : INT, anotherinnerfield : DOUBLE>
LIST<INT>
ARRAY<INT>
STRUCT<innerfield : LIST<INT>>
LIST<STRUCT<innerfield : INT>>

LOCALSORT BY ( <column_name> [ , ... ] ) String Optional

The columns on which to sort new data that is added to the table after the ALTER TABLE command is run. When used in the reflection parameters, sorts the data that is in the reflection.

REFRESH METADATA

Refreshes the metadata associated with the specified table. You can choose to either do a full or partial metadata refresh. A full refresh will update the metadata for the entire table. A partial refresh will enable you to only update specified partitions. Optional clauses are available for refreshing a table's metadata. If you choose to use two or more of these clauses, they must be entered in a specified priority order:

Promotion option: either AVOID PROMOTION or AUTO PROMOTION
Update option: either FORCE UPDATE or LAZY UPDATE
Missing option: either MAINTAIN WHEN MISSING or DELETE WHEN MISSING

note
If the table is not partitioned, you will receive an error when you attempt to refresh the metadata using the FOR PARTITIONS clause.

FOR PARTITIONS ( <partition_name> = '<value>' ) String Optional

Use this clause to do a partial refresh of the table's metadata. The <partition_name> identifies the name of the partition to be refreshed. The <value> identifies the specific partition that should be refreshed. Must be contained in single quotes.

{ AVOID | AUTO } PROMOTION Optional

Clauses that determine whether files and folders are promoted to datasets when you run a query. The AVOID PROMOTION prevents queries from promoting files/folders to datasets. The AUTO PROMOTION allows queries to promote files/folders to datasets. This is the default option when you do not include a promotion clause.

{ FORCE | LAZY } UPDATE Optional

Clauses that determine whether metadata is updated when you run a query. The FORCE UPDATE forces a full update of metadata. The LAZY UPDATE does not perform a full update of metadata. This is the default option when you do not include an update clause.

{ MAINTAIN | DELETE } WHEN MISSING Optional

Clauses that determine how missing metadata is handled when you run a query. The MAINTAIN WHEN MISSING Prevents missing metadata from being deleted during refresh. DELETE WHEN MISSING deletes missing metadata during refresh. This is the default option when you do not include a clause.

FORGET METADATA

Deletes the metadata information stored in Dremio for the specified table until the next metadata refresh. The dataset can still be queried using SQL.

SET TBLPROPERTIES ( '<property_name>' = '<property_value>' [ , ... ] )

Sets one or more table properties for controlling the behavior of the table. See Properties of Apache Iceberg Tables for a list of the supported properties.

UNSET TBLPROPERTIES ( '<property_name>' [ , ... ] )

Removes one or more table properties that control the behavior of the table. See Properties of Apache Iceberg Tables for a list of the supported properties.

CREATE AGGREGATE REFLECTION <reflection_name> String

Creates an aggregation reflection with the specified name.

DIMENSIONS ( <column_name> [ , ... ] ) String

The columns to include as dimensions in the reflection.

MEASURES ( <column_name> ( <aggregation_type> ) [ , ... ] ) String

The columns to include as measures in the reflection, and the type of aggregation to perform on them. The possible types are COUNT, MIN, MAX, SUM, and APPROXIMATE COUNT DISTINCT.

PARTITION BY ( { <column_name> | <partition_transform> } [ , ... ] ) String Optional

The columns or partition-transformation functions on which to partition the data horizontally in the reflection.

<column_name>: The unique name of the column. Multiple columns may be specified as long as the column names include their data type. Use commas to separate each column name and data-type pair. If a column is listed as a partition column, it cannot also be listed as a sort column for the same reflection. Each column specified must also be listed as a dimension column.

<partition_transform>: Applies only to Iceberg tables. Use one of these partition-transformation functions:

Type of Partition Transform	Description
identity(<column_name>)	Creates one partition per value. This is the default transform. The column can use any supported data type.
year(<column_name>)	Partitions by year. The column must use the DATE or TIMESTAMP data type.
month(<column_name>)	Partitions by month. The column must use the DATE or TIMESTAMP data type.
day(<column_name>)	Partitions on the equivalent of dateint. The column must use the DATE or TIMESTAMP data type.
hour(<column_name>)	Partitions on the equivalent of dateint and hour. The column must use the TIMESTAMP data type.
bucket(<integer>, <column_name>)	Partitions data into the number of partitions specified by an integer. For example, if the integer value N is specified, the data is partitioned into N, or (0 to (N-1)), partitions. The partition in which an individual row is stored is determined by hashing the column value and then calculating <hash_value> mod N. If the result is 0, the row is placed in partition 0; if the result is 1, the row is placed in partition 1; and so on. The column can use the DECIMAL, INT, BIGINT, VARCHAR, VARBINARY, DATE, or TIMESTAMP data type.
truncate(<integer>, <column_name>)	If the specified column uses the string data type, truncates strings to a maximum of the number of characters specified by an integer. For example, suppose the specified transform is truncate(1, stateUS). A value of CA is truncated to C, and the row is placed in partition C. A value of CO is also truncated to C, and the row is also placed in partition C. If the specified column uses the integer or long data type, truncates column values in the following way: For any truncate(L, col), truncates the column value to the biggest multiple of L that is smaller than the column value. For example, suppose the specified transform is truncate(10, intColumn). A value of 1 is truncated to 0 and the row is placed in the partition 0. A value of 247 is truncated to 240 and the row is placed in partition 240. If the transform is truncate(3, intColumn), a value of 13 is truncated to 12 and the row is placed in partition 12. A value of 255 is not truncated, because it is divisble by 3, and the row is placed in partition 255. The column can use the DECIMAL, INT, BIGINT, VARCHAR, or VARBINARY data type. Note: The truncate transform does not change column values. It uses column values to calculate the correct partitions in which to place rows.

CREATE EXTERNAL REFLECTION <reflection_name> String

Creates an external reflection with the specified name.

USING <table_name> String

The path of the derived table to use with the external reflection.

CREATE RAW REFLECTION <reflection_name> String

Creates a raw reflection with the specified name.

USING DISPLAY ( <column_name> [ , ... ] ) String

The columns to include in the reflection.

DROP REFLECTION String Optional

Drops the specified reflection defined on the table.

REFRESH REFLECTIONS String Optional

For information about the refresh action performed, see Triggering Refreshes by Using the Reflection API, the Catalog API, or an SQL Command.

ROUTE REFLECTIONS TO { DEFAULT ENGINE | ENGINE { <engine_name> | <engine_uuid> } } String

Specify the engine on which to run jobs that create and refresh reflections that are defined on the table. Use either the name or UUID of the engine. If neither a name nor a UUID is specified, the default engine is used. You can also directly specify the default engine.

{ ADD | DROP } PARTITION FIELD { <column_name> | <partition_transform> } String Optional

ADD partitions the table data on the values in a single column or by using one of the partition-transformation functions. DROP drops the partition definition.

<partition_transform>: Applies only to Iceberg tables. Use one of these partition-transformation functions:

Transform	Description
identity( <col> )	Explicitly specified identity transform.
year( <col> )	Partition by year. The column uses either the TIMESTAMP or DATE data type.
month( <ts_col> )	Partition by month. The column uses either the TIMESTAMP or DATE data type.
day( <ts_col> )	Partition by day. The column uses either the TIMESTAMP or DATE data type.
hour( <ts_col> )	Partition by hour. The column uses the TIMESTAMP data type.
bucket( <count>, <col> )	Partition by hashed value into <count> buckets.
truncate( <length>, <col> )	Partition by truncated value. Strings are truncated to the specified length. Integer and biginteger values are truncated to bins. Example: truncate(10, i) produces 0, 10, 20, and so on.

Examples

Add Primary Key

ALTER TABLE services
  ADD PRIMARY KEY (Country_ID);

Add a column

ALTER TABLE services
  ADD COLUMNS (county varchar);

Add a column to a table at the specified branch

ALTER TABLE services
 AT BRANCH main
 ADD COLUMNS (county varchar);

Modify a column

ALTER TABLE services
  MODIFY COLUMN tip_amount tip_amount DECIMAL;

Modify a column for a struct table

ALTER TABLE struct_type
  MODIFY COLUMN a  a struct<x: varchar, y: bigint>;

Rename a column

ALTER TABLE services
  MODIFY COLUMN tip_amount gratuity_amount DECIMAL;

Refresh all the metadata for a table

ALTER TABLE services
  REFRESH METADATA;

Refresh all the metadata for a table using optional clauses

ALTER TABLE services
  REFRESH METADATA
    AUTO PROMOTION
    LAZY UPDATE
    MAINTAIN WHEN MISSING;

Refresh the metadata for a single partition

ALTER TABLE Samples."samples.dremio.com"."zips.json"  
  REFRESH METADATA FOR PARTITIONS (state = 'TX');

Refresh the metadata for a single partition using optional clauses

ALTER TABLE Samples."samples.dremio.com"."zips.json"  
  REFRESH METADATA FOR PARTITIONS (state = 'TX')
    AUTO PROMOTION
    LAZY UPDATE
    MAINTAIN WHEN MISSING;

Forget the metadata for a table

ALTER TABLE Samples."samples.dremio.com"."zips.json"
  FORGET METADATA;

Create a raw reflection that sorts customers by last name and partitions them by country

ALTER TABLE Sales."customers"
  CREATE RAW REFLECTION customers_by_country USING DISPLAY (id,lastName,firstName,address,country)
    PARTITION BY (country)
    LOCALSORT BY (lastName);

Create an aggregation reflection that counts the cities per state and sorts by state

ALTER TABLE Samples."samples.dremio.com"."zips.json"
  CREATE AGGREGATE REFLECTION per_state USING
  DIMENSIONS (state) MEASURES (city (COUNT))
  LOCALSORT BY (state);

Create an aggregation reflection that counts p1 and p2 as measures in the reflection

ALTER TABLE BI."p1_table"
  CREATE AGGREGATE REFLECTION p1_table_agg USING
  DIMENSIONS (c1,c2) MEASURES (p1(COUNT, MIN), p2(SUM, MAX, APPROXIMATE COUNT DISTINCT))
    PARTITION BY (c1)
    LOCALSORT BY (c2)
    ARROW CACHE

Route reflections to Engine 1

ALTER TABLE "Table 1" ROUTE REFLECTIONS TO ENGINE "Engine 1";
ALTER VIEW "View 1" ROUTE REFLECTIONS TO ENGINE "Engine 1";
ALTER VIEW "View 3" ROUTE REFLECTIONS TO ENGINE "Engine 1";

Add a column for an Apache Iceberg table

ALTER TABLE myTable
  ADD COLUMNS (address VARCHAR);

Change the data type of a column to BIGINT for an Apache Iceberg table

ALTER TABLE myTable
  ALTER COLUMN id id BIGINT;

Parameters​

Examples​

Parameters

Examples