aws.lakeformation.DataCellsFilter

AWS v7.20.0, Feb 19 26

AWS v7.20.0 published on Thursday, Feb 19, 2026 by Pulumi

Schema (JSON)

pulumi/pulumi-aws

AWS v7.20.0 published on Thursday, Feb 19, 2026 by Pulumi

Schema (JSON)

pulumi/pulumi-aws

Example Usage

Basic Usage

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const example = new aws.lakeformation.DataCellsFilter("example", {tableData: {
    databaseName: exampleAwsGlueCatalogDatabase.name,
    name: "example",
    tableCatalogId: current.accountId,
    tableName: exampleAwsGlueCatalogTable.name,
    columnNames: ["my_column"],
    rowFilter: {
        filterExpression: "my_column='example'",
    },
}});

import pulumi
import pulumi_aws as aws

example = aws.lakeformation.DataCellsFilter("example", table_data={
    "database_name": example_aws_glue_catalog_database["name"],
    "name": "example",
    "table_catalog_id": current["accountId"],
    "table_name": example_aws_glue_catalog_table["name"],
    "column_names": ["my_column"],
    "row_filter": {
        "filter_expression": "my_column='example'",
    },
})

package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v7/go/aws/lakeformation"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := lakeformation.NewDataCellsFilter(ctx, "example", &lakeformation.DataCellsFilterArgs{
			TableData: &lakeformation.DataCellsFilterTableDataArgs{
				DatabaseName:   pulumi.Any(exampleAwsGlueCatalogDatabase.Name),
				Name:           pulumi.String("example"),
				TableCatalogId: pulumi.Any(current.AccountId),
				TableName:      pulumi.Any(exampleAwsGlueCatalogTable.Name),
				ColumnNames: pulumi.StringArray{
					pulumi.String("my_column"),
				},
				RowFilter: &lakeformation.DataCellsFilterTableDataRowFilterArgs{
					FilterExpression: pulumi.String("my_column='example'"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var example = new Aws.LakeFormation.DataCellsFilter("example", new()
    {
        TableData = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataArgs
        {
            DatabaseName = exampleAwsGlueCatalogDatabase.Name,
            Name = "example",
            TableCatalogId = current.AccountId,
            TableName = exampleAwsGlueCatalogTable.Name,
            ColumnNames = new[]
            {
                "my_column",
            },
            RowFilter = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataRowFilterArgs
            {
                FilterExpression = "my_column='example'",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.lakeformation.DataCellsFilter;
import com.pulumi.aws.lakeformation.DataCellsFilterArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataRowFilterArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var example = new DataCellsFilter("example", DataCellsFilterArgs.builder()
            .tableData(DataCellsFilterTableDataArgs.builder()
                .databaseName(exampleAwsGlueCatalogDatabase.name())
                .name("example")
                .tableCatalogId(current.accountId())
                .tableName(exampleAwsGlueCatalogTable.name())
                .columnNames("my_column")
                .rowFilter(DataCellsFilterTableDataRowFilterArgs.builder()
                    .filterExpression("my_column='example'")
                    .build())
                .build())
            .build());

    }
}

resources:
  example:
    type: aws:lakeformation:DataCellsFilter
    properties:
      tableData:
        databaseName: ${exampleAwsGlueCatalogDatabase.name}
        name: example
        tableCatalogId: ${current.accountId}
        tableName: ${exampleAwsGlueCatalogTable.name}
        columnNames:
          - my_column
        rowFilter:
          filterExpression: my_column='example'

Filter with Excluded Columns Only (No Row Filter)

When excluding columns without a row filter, you must include all_rows_wildcard {}:

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const excludedColumns = new aws.lakeformation.DataCellsFilter("excluded_columns", {tableData: {
    databaseName: example.name,
    name: "exclude-pii",
    tableCatalogId: current.accountId,
    tableName: exampleAwsGlueCatalogTable.name,
    columnWildcard: {
        excludedColumnNames: [
            "ssn",
            "credit_card",
        ],
    },
    rowFilter: {
        allRowsWildcard: {},
    },
}});

import pulumi
import pulumi_aws as aws

excluded_columns = aws.lakeformation.DataCellsFilter("excluded_columns", table_data={
    "database_name": example["name"],
    "name": "exclude-pii",
    "table_catalog_id": current["accountId"],
    "table_name": example_aws_glue_catalog_table["name"],
    "column_wildcard": {
        "excluded_column_names": [
            "ssn",
            "credit_card",
        ],
    },
    "row_filter": {
        "all_rows_wildcard": {},
    },
})

package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v7/go/aws/lakeformation"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := lakeformation.NewDataCellsFilter(ctx, "excluded_columns", &lakeformation.DataCellsFilterArgs{
			TableData: &lakeformation.DataCellsFilterTableDataArgs{
				DatabaseName:   pulumi.Any(example.Name),
				Name:           pulumi.String("exclude-pii"),
				TableCatalogId: pulumi.Any(current.AccountId),
				TableName:      pulumi.Any(exampleAwsGlueCatalogTable.Name),
				ColumnWildcard: &lakeformation.DataCellsFilterTableDataColumnWildcardArgs{
					ExcludedColumnNames: pulumi.StringArray{
						pulumi.String("ssn"),
						pulumi.String("credit_card"),
					},
				},
				RowFilter: &lakeformation.DataCellsFilterTableDataRowFilterArgs{
					AllRowsWildcard: &lakeformation.DataCellsFilterTableDataRowFilterAllRowsWildcardArgs{},
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var excludedColumns = new Aws.LakeFormation.DataCellsFilter("excluded_columns", new()
    {
        TableData = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataArgs
        {
            DatabaseName = example.Name,
            Name = "exclude-pii",
            TableCatalogId = current.AccountId,
            TableName = exampleAwsGlueCatalogTable.Name,
            ColumnWildcard = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataColumnWildcardArgs
            {
                ExcludedColumnNames = new[]
                {
                    "ssn",
                    "credit_card",
                },
            },
            RowFilter = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataRowFilterArgs
            {
                AllRowsWildcard = null,
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.lakeformation.DataCellsFilter;
import com.pulumi.aws.lakeformation.DataCellsFilterArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataColumnWildcardArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataRowFilterArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataRowFilterAllRowsWildcardArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var excludedColumns = new DataCellsFilter("excludedColumns", DataCellsFilterArgs.builder()
            .tableData(DataCellsFilterTableDataArgs.builder()
                .databaseName(example.name())
                .name("exclude-pii")
                .tableCatalogId(current.accountId())
                .tableName(exampleAwsGlueCatalogTable.name())
                .columnWildcard(DataCellsFilterTableDataColumnWildcardArgs.builder()
                    .excludedColumnNames(                    
                        "ssn",
                        "credit_card")
                    .build())
                .rowFilter(DataCellsFilterTableDataRowFilterArgs.builder()
                    .allRowsWildcard(DataCellsFilterTableDataRowFilterAllRowsWildcardArgs.builder()
                        .build())
                    .build())
                .build())
            .build());

    }
}

resources:
  excludedColumns:
    type: aws:lakeformation:DataCellsFilter
    name: excluded_columns
    properties:
      tableData:
        databaseName: ${example.name}
        name: exclude-pii
        tableCatalogId: ${current.accountId}
        tableName: ${exampleAwsGlueCatalogTable.name}
        columnWildcard:
          excludedColumnNames:
            - ssn
            - credit_card
        rowFilter:
          allRowsWildcard: {}

Filter with Row Filter and Excluded Columns

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const rowAndColumn = new aws.lakeformation.DataCellsFilter("row_and_column", {tableData: {
    databaseName: example.name,
    name: "marketing-filtered",
    tableCatalogId: current.accountId,
    tableName: exampleAwsGlueCatalogTable.name,
    columnWildcard: {
        excludedColumnNames: [
            "salary",
            "bonus",
        ],
    },
    rowFilter: {
        filterExpression: "department = 'Marketing'",
    },
}});

import pulumi
import pulumi_aws as aws

row_and_column = aws.lakeformation.DataCellsFilter("row_and_column", table_data={
    "database_name": example["name"],
    "name": "marketing-filtered",
    "table_catalog_id": current["accountId"],
    "table_name": example_aws_glue_catalog_table["name"],
    "column_wildcard": {
        "excluded_column_names": [
            "salary",
            "bonus",
        ],
    },
    "row_filter": {
        "filter_expression": "department = 'Marketing'",
    },
})

package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v7/go/aws/lakeformation"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := lakeformation.NewDataCellsFilter(ctx, "row_and_column", &lakeformation.DataCellsFilterArgs{
			TableData: &lakeformation.DataCellsFilterTableDataArgs{
				DatabaseName:   pulumi.Any(example.Name),
				Name:           pulumi.String("marketing-filtered"),
				TableCatalogId: pulumi.Any(current.AccountId),
				TableName:      pulumi.Any(exampleAwsGlueCatalogTable.Name),
				ColumnWildcard: &lakeformation.DataCellsFilterTableDataColumnWildcardArgs{
					ExcludedColumnNames: pulumi.StringArray{
						pulumi.String("salary"),
						pulumi.String("bonus"),
					},
				},
				RowFilter: &lakeformation.DataCellsFilterTableDataRowFilterArgs{
					FilterExpression: pulumi.String("department = 'Marketing'"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var rowAndColumn = new Aws.LakeFormation.DataCellsFilter("row_and_column", new()
    {
        TableData = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataArgs
        {
            DatabaseName = example.Name,
            Name = "marketing-filtered",
            TableCatalogId = current.AccountId,
            TableName = exampleAwsGlueCatalogTable.Name,
            ColumnWildcard = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataColumnWildcardArgs
            {
                ExcludedColumnNames = new[]
                {
                    "salary",
                    "bonus",
                },
            },
            RowFilter = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataRowFilterArgs
            {
                FilterExpression = "department = 'Marketing'",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.lakeformation.DataCellsFilter;
import com.pulumi.aws.lakeformation.DataCellsFilterArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataColumnWildcardArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataRowFilterArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var rowAndColumn = new DataCellsFilter("rowAndColumn", DataCellsFilterArgs.builder()
            .tableData(DataCellsFilterTableDataArgs.builder()
                .databaseName(example.name())
                .name("marketing-filtered")
                .tableCatalogId(current.accountId())
                .tableName(exampleAwsGlueCatalogTable.name())
                .columnWildcard(DataCellsFilterTableDataColumnWildcardArgs.builder()
                    .excludedColumnNames(                    
                        "salary",
                        "bonus")
                    .build())
                .rowFilter(DataCellsFilterTableDataRowFilterArgs.builder()
                    .filterExpression("department = 'Marketing'")
                    .build())
                .build())
            .build());

    }
}

resources:
  rowAndColumn:
    type: aws:lakeformation:DataCellsFilter
    name: row_and_column
    properties:
      tableData:
        databaseName: ${example.name}
        name: marketing-filtered
        tableCatalogId: ${current.accountId}
        tableName: ${exampleAwsGlueCatalogTable.name}
        columnWildcard:
          excludedColumnNames:
            - salary
            - bonus
        rowFilter:
          filterExpression: department = 'Marketing'

Filter with Row Filter Only (All Columns Included)

To include all columns with a row filter, set excluded_column_names to an empty list:

import * as pulumi from "@pulumi/pulumi";
import * as aws from "@pulumi/aws";

const rowOnly = new aws.lakeformation.DataCellsFilter("row_only", {tableData: {
    databaseName: example.name,
    name: "regional-filter",
    tableCatalogId: current.accountId,
    tableName: exampleAwsGlueCatalogTable.name,
    columnWildcard: {
        excludedColumnNames: [],
    },
    rowFilter: {
        filterExpression: "region = 'US-WEST'",
    },
}});

import pulumi
import pulumi_aws as aws

row_only = aws.lakeformation.DataCellsFilter("row_only", table_data={
    "database_name": example["name"],
    "name": "regional-filter",
    "table_catalog_id": current["accountId"],
    "table_name": example_aws_glue_catalog_table["name"],
    "column_wildcard": {
        "excluded_column_names": [],
    },
    "row_filter": {
        "filter_expression": "region = 'US-WEST'",
    },
})

package main

import (
	"github.com/pulumi/pulumi-aws/sdk/v7/go/aws/lakeformation"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := lakeformation.NewDataCellsFilter(ctx, "row_only", &lakeformation.DataCellsFilterArgs{
			TableData: &lakeformation.DataCellsFilterTableDataArgs{
				DatabaseName:   pulumi.Any(example.Name),
				Name:           pulumi.String("regional-filter"),
				TableCatalogId: pulumi.Any(current.AccountId),
				TableName:      pulumi.Any(exampleAwsGlueCatalogTable.Name),
				ColumnWildcard: &lakeformation.DataCellsFilterTableDataColumnWildcardArgs{
					ExcludedColumnNames: pulumi.StringArray{},
				},
				RowFilter: &lakeformation.DataCellsFilterTableDataRowFilterArgs{
					FilterExpression: pulumi.String("region = 'US-WEST'"),
				},
			},
		})
		if err != nil {
			return err
		}
		return nil
	})
}

using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Aws = Pulumi.Aws;

return await Deployment.RunAsync(() => 
{
    var rowOnly = new Aws.LakeFormation.DataCellsFilter("row_only", new()
    {
        TableData = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataArgs
        {
            DatabaseName = example.Name,
            Name = "regional-filter",
            TableCatalogId = current.AccountId,
            TableName = exampleAwsGlueCatalogTable.Name,
            ColumnWildcard = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataColumnWildcardArgs
            {
                ExcludedColumnNames = new() { },
            },
            RowFilter = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataRowFilterArgs
            {
                FilterExpression = "region = 'US-WEST'",
            },
        },
    });

});

package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.aws.lakeformation.DataCellsFilter;
import com.pulumi.aws.lakeformation.DataCellsFilterArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataColumnWildcardArgs;
import com.pulumi.aws.lakeformation.inputs.DataCellsFilterTableDataRowFilterArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var rowOnly = new DataCellsFilter("rowOnly", DataCellsFilterArgs.builder()
            .tableData(DataCellsFilterTableDataArgs.builder()
                .databaseName(example.name())
                .name("regional-filter")
                .tableCatalogId(current.accountId())
                .tableName(exampleAwsGlueCatalogTable.name())
                .columnWildcard(DataCellsFilterTableDataColumnWildcardArgs.builder()
                    .excludedColumnNames()
                    .build())
                .rowFilter(DataCellsFilterTableDataRowFilterArgs.builder()
                    .filterExpression("region = 'US-WEST'")
                    .build())
                .build())
            .build());

    }
}

resources:
  rowOnly:
    type: aws:lakeformation:DataCellsFilter
    name: row_only
    properties:
      tableData:
        databaseName: ${example.name}
        name: regional-filter
        tableCatalogId: ${current.accountId}
        tableName: ${exampleAwsGlueCatalogTable.name}
        columnWildcard:
          excludedColumnNames: []
        rowFilter:
          filterExpression: region = 'US-WEST'

Create DataCellsFilter Resource

Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

Constructor syntax

new DataCellsFilter(name: string, args: DataCellsFilterArgs, opts?: CustomResourceOptions);

@overload
def DataCellsFilter(resource_name: str,
                    args: DataCellsFilterArgs,
                    opts: Optional[ResourceOptions] = None)

@overload
def DataCellsFilter(resource_name: str,
                    opts: Optional[ResourceOptions] = None,
                    table_data: Optional[DataCellsFilterTableDataArgs] = None,
                    region: Optional[str] = None,
                    timeouts: Optional[DataCellsFilterTimeoutsArgs] = None)

func NewDataCellsFilter(ctx *Context, name string, args DataCellsFilterArgs, opts ...ResourceOption) (*DataCellsFilter, error)

public DataCellsFilter(string name, DataCellsFilterArgs args, CustomResourceOptions? opts = null)

public DataCellsFilter(String name, DataCellsFilterArgs args)
public DataCellsFilter(String name, DataCellsFilterArgs args, CustomResourceOptions options)

type: aws:lakeformation:DataCellsFilter
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

Parameters

name string: The unique name of the resource.
args DataCellsFilterArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args DataCellsFilterArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args DataCellsFilterArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args DataCellsFilterArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args DataCellsFilterArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Constructor example

The following reference example uses placeholder values for all input properties.

var dataCellsFilterResource = new Aws.LakeFormation.DataCellsFilter("dataCellsFilterResource", new()
{
    TableData = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataArgs
    {
        DatabaseName = "string",
        Name = "string",
        RowFilter = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataRowFilterArgs
        {
            AllRowsWildcard = null,
            FilterExpression = "string",
        },
        TableCatalogId = "string",
        TableName = "string",
        ColumnNames = new[]
        {
            "string",
        },
        ColumnWildcard = new Aws.LakeFormation.Inputs.DataCellsFilterTableDataColumnWildcardArgs
        {
            ExcludedColumnNames = new[]
            {
                "string",
            },
        },
        VersionId = "string",
    },
    Region = "string",
    Timeouts = new Aws.LakeFormation.Inputs.DataCellsFilterTimeoutsArgs
    {
        Create = "string",
    },
});

example, err := lakeformation.NewDataCellsFilter(ctx, "dataCellsFilterResource", &lakeformation.DataCellsFilterArgs{
	TableData: &lakeformation.DataCellsFilterTableDataArgs{
		DatabaseName: pulumi.String("string"),
		Name:         pulumi.String("string"),
		RowFilter: &lakeformation.DataCellsFilterTableDataRowFilterArgs{
			AllRowsWildcard:  &lakeformation.DataCellsFilterTableDataRowFilterAllRowsWildcardArgs{},
			FilterExpression: pulumi.String("string"),
		},
		TableCatalogId: pulumi.String("string"),
		TableName:      pulumi.String("string"),
		ColumnNames: pulumi.StringArray{
			pulumi.String("string"),
		},
		ColumnWildcard: &lakeformation.DataCellsFilterTableDataColumnWildcardArgs{
			ExcludedColumnNames: pulumi.StringArray{
				pulumi.String("string"),
			},
		},
		VersionId: pulumi.String("string"),
	},
	Region: pulumi.String("string"),
	Timeouts: &lakeformation.DataCellsFilterTimeoutsArgs{
		Create: pulumi.String("string"),
	},
})

var dataCellsFilterResource = new DataCellsFilter("dataCellsFilterResource", DataCellsFilterArgs.builder()
    .tableData(DataCellsFilterTableDataArgs.builder()
        .databaseName("string")
        .name("string")
        .rowFilter(DataCellsFilterTableDataRowFilterArgs.builder()
            .allRowsWildcard(DataCellsFilterTableDataRowFilterAllRowsWildcardArgs.builder()
                .build())
            .filterExpression("string")
            .build())
        .tableCatalogId("string")
        .tableName("string")
        .columnNames("string")
        .columnWildcard(DataCellsFilterTableDataColumnWildcardArgs.builder()
            .excludedColumnNames("string")
            .build())
        .versionId("string")
        .build())
    .region("string")
    .timeouts(DataCellsFilterTimeoutsArgs.builder()
        .create("string")
        .build())
    .build());

data_cells_filter_resource = aws.lakeformation.DataCellsFilter("dataCellsFilterResource",
    table_data={
        "database_name": "string",
        "name": "string",
        "row_filter": {
            "all_rows_wildcard": {},
            "filter_expression": "string",
        },
        "table_catalog_id": "string",
        "table_name": "string",
        "column_names": ["string"],
        "column_wildcard": {
            "excluded_column_names": ["string"],
        },
        "version_id": "string",
    },
    region="string",
    timeouts={
        "create": "string",
    })

const dataCellsFilterResource = new aws.lakeformation.DataCellsFilter("dataCellsFilterResource", {
    tableData: {
        databaseName: "string",
        name: "string",
        rowFilter: {
            allRowsWildcard: {},
            filterExpression: "string",
        },
        tableCatalogId: "string",
        tableName: "string",
        columnNames: ["string"],
        columnWildcard: {
            excludedColumnNames: ["string"],
        },
        versionId: "string",
    },
    region: "string",
    timeouts: {
        create: "string",
    },
});

type: aws:lakeformation:DataCellsFilter
properties:
    region: string
    tableData:
        columnNames:
            - string
        columnWildcard:
            excludedColumnNames:
                - string
        databaseName: string
        name: string
        rowFilter:
            allRowsWildcard: {}
            filterExpression: string
        tableCatalogId: string
        tableName: string
        versionId: string
    timeouts:
        create: string

DataCellsFilter Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

The DataCellsFilter resource accepts the following input properties:

TableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
Region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
Timeouts DataCellsFilterTimeouts

TableData DataCellsFilterTableDataArgs: Information about the data cells filter. See Table Data below for details.
Region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
Timeouts DataCellsFilterTimeoutsArgs

tableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
region String: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
timeouts DataCellsFilterTimeouts

tableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
timeouts DataCellsFilterTimeouts

table_data DataCellsFilterTableDataArgs: Information about the data cells filter. See Table Data below for details.
region str: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
timeouts DataCellsFilterTimeoutsArgs

tableData Property Map: Information about the data cells filter. See Table Data below for details.
region String: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
timeouts Property Map

Outputs

All input properties are implicitly available as output properties. Additionally, the DataCellsFilter resource produces the following output properties:

Id string: The provider-assigned unique ID for this managed resource.

Id string: The provider-assigned unique ID for this managed resource.

id String: The provider-assigned unique ID for this managed resource.

id string: The provider-assigned unique ID for this managed resource.

id str: The provider-assigned unique ID for this managed resource.

id String: The provider-assigned unique ID for this managed resource.

Look up Existing DataCellsFilter Resource

Get an existing DataCellsFilter resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

public static get(name: string, id: Input<ID>, state?: DataCellsFilterState, opts?: CustomResourceOptions): DataCellsFilter

@staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        region: Optional[str] = None,
        table_data: Optional[DataCellsFilterTableDataArgs] = None,
        timeouts: Optional[DataCellsFilterTimeoutsArgs] = None) -> DataCellsFilter

func GetDataCellsFilter(ctx *Context, name string, id IDInput, state *DataCellsFilterState, opts ...ResourceOption) (*DataCellsFilter, error)

public static DataCellsFilter Get(string name, Input<string> id, DataCellsFilterState? state, CustomResourceOptions? opts = null)

public static DataCellsFilter get(String name, Output<String> id, DataCellsFilterState state, CustomResourceOptions options)

resources:  _:    type: aws:lakeformation:DataCellsFilter    get:      id: ${id}

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

resource_name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

name: The unique name of the resulting resource.
id: The unique provider ID of the resource to lookup.
state: Any extra arguments used during the lookup.
opts: A bag of options that control this resource's behavior.

The following state arguments are supported:

Region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
TableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
Timeouts DataCellsFilterTimeouts

Region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
TableData DataCellsFilterTableDataArgs: Information about the data cells filter. See Table Data below for details.
Timeouts DataCellsFilterTimeoutsArgs

region String: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
tableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
timeouts DataCellsFilterTimeouts

region string: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
tableData DataCellsFilterTableData: Information about the data cells filter. See Table Data below for details.
timeouts DataCellsFilterTimeouts

region str: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
table_data DataCellsFilterTableDataArgs: Information about the data cells filter. See Table Data below for details.
timeouts DataCellsFilterTimeoutsArgs

region String: Region where this resource will be managed. Defaults to the Region set in the provider configuration.
tableData Property Map: Information about the data cells filter. See Table Data below for details.
timeouts Property Map

Supporting Types

DataCellsFilterTableData, DataCellsFilterTableDataArgs

DatabaseName string: The name of the database.
Name string: The name of the data cells filter.
RowFilter DataCellsFilterTableDataRowFilter: A PartiQL predicate. See Row Filter below for details.
TableCatalogId string: The ID of the Data Catalog.
TableName string: The name of the table.
ColumnNames List<string>: A list of column names and/or nested column attributes.
ColumnWildcard DataCellsFilterTableDataColumnWildcard: A wildcard with exclusions. See Column Wildcard below for details.
VersionId string: ID of the data cells filter version.

DatabaseName string: The name of the database.
Name string: The name of the data cells filter.
RowFilter DataCellsFilterTableDataRowFilter: A PartiQL predicate. See Row Filter below for details.
TableCatalogId string: The ID of the Data Catalog.
TableName string: The name of the table.
ColumnNames []string: A list of column names and/or nested column attributes.
ColumnWildcard DataCellsFilterTableDataColumnWildcard: A wildcard with exclusions. See Column Wildcard below for details.
VersionId string: ID of the data cells filter version.

databaseName String: The name of the database.
name String: The name of the data cells filter.
rowFilter DataCellsFilterTableDataRowFilter: A PartiQL predicate. See Row Filter below for details.
tableCatalogId String: The ID of the Data Catalog.
tableName String: The name of the table.
columnNames List<String>: A list of column names and/or nested column attributes.
columnWildcard DataCellsFilterTableDataColumnWildcard: A wildcard with exclusions. See Column Wildcard below for details.
versionId String: ID of the data cells filter version.

databaseName string: The name of the database.
name string: The name of the data cells filter.
rowFilter DataCellsFilterTableDataRowFilter: A PartiQL predicate. See Row Filter below for details.
tableCatalogId string: The ID of the Data Catalog.
tableName string: The name of the table.
columnNames string[]: A list of column names and/or nested column attributes.
columnWildcard DataCellsFilterTableDataColumnWildcard: A wildcard with exclusions. See Column Wildcard below for details.
versionId string: ID of the data cells filter version.

database_name str: The name of the database.
name str: The name of the data cells filter.
row_filter DataCellsFilterTableDataRowFilter: A PartiQL predicate. See Row Filter below for details.
table_catalog_id str: The ID of the Data Catalog.
table_name str: The name of the table.
column_names Sequence[str]: A list of column names and/or nested column attributes.
column_wildcard DataCellsFilterTableDataColumnWildcard: A wildcard with exclusions. See Column Wildcard below for details.
version_id str: ID of the data cells filter version.

databaseName String: The name of the database.
name String: The name of the data cells filter.
rowFilter Property Map: A PartiQL predicate. See Row Filter below for details.
tableCatalogId String: The ID of the Data Catalog.
tableName String: The name of the table.
columnNames List<String>: A list of column names and/or nested column attributes.
columnWildcard Property Map: A wildcard with exclusions. See Column Wildcard below for details.
versionId String: ID of the data cells filter version.

DataCellsFilterTableDataColumnWildcard, DataCellsFilterTableDataColumnWildcardArgs

ExcludedColumnNames List<string>: (Optional) Excludes column names. Any column with this name will be excluded.

ExcludedColumnNames []string: (Optional) Excludes column names. Any column with this name will be excluded.

excludedColumnNames List<String>: (Optional) Excludes column names. Any column with this name will be excluded.

excludedColumnNames string[]: (Optional) Excludes column names. Any column with this name will be excluded.

excluded_column_names Sequence[str]: (Optional) Excludes column names. Any column with this name will be excluded.

excludedColumnNames List<String>: (Optional) Excludes column names. Any column with this name will be excluded.

DataCellsFilterTableDataRowFilter, DataCellsFilterTableDataRowFilterArgs

AllRowsWildcard DataCellsFilterTableDataRowFilterAllRowsWildcard: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
FilterExpression string: (Optional) A PartiQL predicate expression for row-level filtering.

AllRowsWildcard DataCellsFilterTableDataRowFilterAllRowsWildcard: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
FilterExpression string: (Optional) A PartiQL predicate expression for row-level filtering.

allRowsWildcard DataCellsFilterTableDataRowFilterAllRowsWildcard: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
filterExpression String: (Optional) A PartiQL predicate expression for row-level filtering.

allRowsWildcard DataCellsFilterTableDataRowFilterAllRowsWildcard: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
filterExpression string: (Optional) A PartiQL predicate expression for row-level filtering.

all_rows_wildcard DataCellsFilterTableDataRowFilterAllRowsWildcard: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
filter_expression str: (Optional) A PartiQL predicate expression for row-level filtering.

allRowsWildcard Property Map: (Optional) A wildcard that matches all rows. Required when applying column-level filtering without row-level filtering. Use an empty block: all_rows_wildcard {}.
filterExpression String: (Optional) A PartiQL predicate expression for row-level filtering.

DataCellsFilterTimeouts, DataCellsFilterTimeoutsArgs

Create string: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

Create string: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

create String: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

create string: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

create str: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

create String: A string that can be parsed as a duration consisting of numbers and unit suffixes, such as "30s" or "2h45m". Valid time units are "s" (seconds), "m" (minutes), "h" (hours).

Import

Using pulumi import, import Lake Formation Data Cells Filter using the database_name, name, table_catalog_id, and table_name separated by ,. For example:

$ pulumi import aws:lakeformation/dataCellsFilter:DataCellsFilter example database_name,name,table_catalog_id,table_name

To learn more about importing existing cloud resources, see Importing resources.

Package Details

Repository: AWS Classic pulumi/pulumi-aws
License: Apache-2.0
Notes: This Pulumi package is based on the aws Terraform Provider.

AWS v7.20.0 published on Thursday, Feb 19, 2026 by Pulumi

Schema (JSON)

pulumi/pulumi-aws

aws.lakeformation.DataCellsFilter

On this page

On this page

Example Usage

Basic Usage

Filter with Excluded Columns Only (No Row Filter)

Filter with Row Filter and Excluded Columns

Filter with Row Filter Only (All Columns Included)

Create DataCellsFilter Resource

Constructor syntax

Parameters

Constructor example

DataCellsFilter Resource Properties

Inputs

Outputs

Look up Existing DataCellsFilter Resource

Supporting Types

DataCellsFilterTableData, DataCellsFilterTableDataArgs

DataCellsFilterTableDataColumnWildcard, DataCellsFilterTableDataColumnWildcardArgs

DataCellsFilterTableDataRowFilter, DataCellsFilterTableDataRowFilterArgs

DataCellsFilterTimeouts, DataCellsFilterTimeoutsArgs

Import

Package Details

On this page

On this page