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ALTER TABLE

Update a table’s definition or schema.

Syntax

ALTER TABLE <table_name>
  {Table_Action}

-- Add Columns
ADD COLUMNS ( <column_name1> <data_type> [, ... ] )

-- Drop Column
DROP COLUMN <column_name>

-- Modify Column Data Type
{ ALTER | MODIFY | CHANGE } COLUMN <column_name> <column_name> <data_type>

-- Modify Column Name (Iceberg tables only)
{ ALTER | MODIFY | CHANGE } COLUMN <old_name> <new_name> <data_type>

-- Set a Column-Masking Policy
MODIFY COLUMN <column_name>
  SET MASKING POLICY <function_name> ( <column_name> [, ... ] )

-- Unset a Column-Masking Policy
MODIFY COLUMN <column_name>
  UNSET MASKING POLICY <function_name>

-- Add or Drop a Row-Access Policy
  { ADD | DROP } ROW ACCESS POLICY <function_name> ( <column_name> [, ... ] )

-- Refresh Metadata
REFRESH METADATA
  [ FOR PARTITIONS ( <partition_name> = '<value>') ]
  [ { AVOID | AUTO } PROMOTION ]
  [ { FORCE | LAZY } UPDATE ]
  [ { MAINTAIN | DELETE } WHEN MISSING ]

-- Forget Metadata
FORGET METADATA

-- Create Aggregate Reflections
CREATE AGGREGATE REFLECTION <reflection_name> USING DIMENSIONS ( <column_name1>, <column_name2>, ... ) MEASURES ( <column_name1> ( <aggregation_type>, <column_name2> <aggregation_type> , ... ) )
  [ PARTITION BY ( <column_name1>, <column_name2>, ... ) ]
  [ LOCALSORT BY ( <column_name1>, <column_name2>, ... ) ]
  [ ARROW CACHE ]

-- Create External Reflections
CREATE EXTERNAL REFLECTION <reflection_name> USING <table_name>

-- Create Raw Reflections
CREATE RAW REFLECTION <reflection_name> USING DISPLAY ( <column_name1>, <column_name2>, ...)
  [ PARTITION BY ( <column_name1>, <column_name2>, ... ) ]
  [ LOCALSORT BY ( <column_name1>, <column_name2>, ... ) ]
  [ ARROW CACHE ]

-- Route Reflections
ROUTE REFLECTIONS TO { DEFAULT ENGINE | ENGINE { <engine_name> | <engine_uuid> } }

-- Partition Fields (Iceberg tables only)
{ ADD | DROP } PARTITION FIELD { <column_name> | <partition_transform> }

Parameters

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

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. If a length is specified, it 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>>

Drops the specified column. This action cannot be undone.

Changes the data type for a specified column. The size is an attribute of the data type.

Note:

You can only rename columns of scratch and Iceberg tables.

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.

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.

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.

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.

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.

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

The name to give to the new reflection.

The columns to include as dimensions in the reflection.

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.

The columns on which to partition the data horizontally in the reflection.

The columns on which to sort the data that is in the reflection.

Specifies that you want Dremio to convert data from your reflection’s Parquet files to the Apache Arrow format when copying that data to executor nodes. Normally, Dremio copies data as-is from the Parquet files as-is to caches on executor nodes, which are nodes that carry out the query plans devised by the query optimizer. Enabling this option can improve query performance even more. However, data in the Apache Arrow format requires more space on the executor nodes than data in the default format. You can use this option with Amazon S3.

The columns to include in the reflection.

Specify an engine to route reflections to either by the name or UUID of the engine. If not specified, the default engine will be used.

Changes the data type for a column, and gives you the option of to renaming the column. If you do not want to rename the column, set <new_name> to <old_name>.
Only three types of changes to primitive types are allowed:

int to long
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>>

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.
These are the partition-transformation functions:

Transform	Description
identity( <col> )	Explicitly specified identity transform
year( <col> )	Partition by year. The column must use the TIMESTAMP data type.
month( <ts_col> )	Partition by month. The column must use the TIMESTAMP data type.
day( <ts_col> )	Partition by day. The column must use the TIMESTAMP data type.
hour( <ts_col> )	Partition by hour. The column must use 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.

Specifies the column to which the masking policy will apply and mask data for. The UDF serving as the masking policy must accept and return the same data type as the column it is masking.

Specifies the function to use with this security policy. If a function with this name does not exist, then the affected table/view will not be reachable until the policy is dropped or a UDF created.

Examples

Add a column

ALTER TABLE services
  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 "@user1"."customers"
  CREATE RAW REFLECTION customers_by_country USING DISPLAY (id,lastName,firstName,address,country)
    PARTITION BY (country)
    LOCALSORT BY (lastName)

Create an aggregate 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)

Routing Reflections

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

Adding a column for an Apache Iceberg Table

ALTER TABLE myTable ADD COLUMNS (address VARCHAR)

Changing the data type of a column to BIGINT for an Apache Iceberg Table

ALTER TABLE myTable ALTER COLUMN id id BIGINT

Set a column-masking policy that takes multiple columns

ALTER TABLE e.employees
    MODIFY COLUMN ssn_col
    SET MASKING POLICY protect_ssn (ssn_col, region)

Unset a column-masking policy

ALTER TABLE e.employees
    MODIFY COLUMN ssn_col
    UNSET MASKING POLICY protect_ssn

Add a row-access policy to a table

ALTER TABLE e.employees
  ADD ROW ACCESS POLICY state_policy ( state_col )

Remove a row-access policy from a table

ALTER TABLE employees
  DROP ROW ACCESS POLICY protect_ssn (ssn_col, region)

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