Syntax Properties Return values Remarks Examples See also

AWS::LakeFormation::DataCellsFilter

A structure that represents a data cell filter with column-level, row-level, and/or cell-level security. Data cell filters belong to a specific table in a Data Catalog. During a stack operation, Amazon CloudFormation calls the Amazon Lake Formation CreateDataCellsFilter API operation to create a DataCellsFilter resource, and calls the DeleteDataCellsFilter API operation to delete it.

Syntax

To declare this entity in your Amazon CloudFormation template, use the following syntax:

JSON


{
  "Type" : "AWS::LakeFormation::DataCellsFilter",
  "Properties" : {
      "ColumnNames" : [ String, ... ],
      "ColumnWildcard" : ColumnWildcard,
      "DatabaseName" : String,
      "Name" : String,
      "RowFilter" : RowFilter,
      "TableCatalogId" : String,
      "TableName" : String
    }
}

YAML


Type: AWS::LakeFormation::DataCellsFilter
Properties: 
  ColumnNames: 
    - String
  ColumnWildcard: 
    ColumnWildcard
  DatabaseName: String
  Name: String
  RowFilter: 
    RowFilter
  TableCatalogId: String
  TableName: String

Properties

ColumnNames

An array of UTF-8 strings. A list of column names.

Required: No

Type: List of String

Update requires: Replacement

ColumnWildcard

A wildcard with exclusions. You must specify either a ColumnNames list or the ColumnWildCard.

Required: No

Type: ColumnWildcard

Update requires: Replacement

DatabaseName

UTF-8 string, not less than 1 or more than 255 bytes long, matching the single-line string pattern.

A database in the Data Catalog.

Required: Yes

Type: String

Update requires: Replacement

Name

UTF-8 string, not less than 1 or more than 255 bytes long, matching the single-line string pattern.

The name given by the user to the data filter cell.

Required: Yes

Type: String

Update requires: Replacement

RowFilter

A PartiQL predicate.

Required: No

Type: RowFilter

Update requires: Replacement

TableCatalogId

Catalog id string, not less than 1 or more than 255 bytes long, matching the single-line string pattern.

The ID of the catalog to which the table belongs.

Required: Yes

Type: String

Update requires: Replacement

TableName

UTF-8 string, not less than 1 or more than 255 bytes long, matching the single-line string pattern.

A table in the database.

Required: Yes

Type: String

Update requires: Replacement

Return values

Ref

When you pass the logical ID of this resource to the intrinsic Reffunction, Refreturns the resource properties such as TableCatalogId, DatabaseName, TableName, and FilterName. For example: 123456789012|ExampleDbName|ExampleTableName|ExampleFilterName

Remarks

The level of filtering that you get depends on how you populate the data filter.

When you specify the "all columns" wildcard and provide a row filter expression, you are establishing row-level security (row filtering) only.
When you include or exclude specific columns and specify all rows using the all-rows wildcard, you are establishing column-level security (column filtering) only.
When you include or exclude specific columns and also provide a row filter expression, you are establishing cell-level security (cell filtering).

Specify the following to create a valid data cells filter:

ColumnWildcard or ColumnNames
RowFilter.AllRowsWildcard or RowFilter.FilterExpression

Examples

Creating a DataCellsFilter using row and column wildcards

The following example demonstrates how to create a DataCellsFilter resource using row and column wildcards:

JSON


{
  "SampleDataCellsFilter": {
    "Type": "AWS::LakeFormation::DataCellsFilter",
    "Properties": {
      "TableCatalogId": "12345678910",
      "DatabaseName": "sample_db",
      "TableName": "sample_tbl",
      "Name": "sample_data_cells_filter",
      "RowFilter": {
          "AllRowsWildcard": {}
       },
          "ColumnWildcard": {}
     }
   }
}

YAML


SampleDataCellsFilter:
    Type: AWS::LakeFormation::DataCellsFilter
    Properties:
        TableCatalogId: "12345678910"
        DatabaseName: "sample_db" 
        TableName: "sample_tbl" 
        Name: "sample_data_cells_filter" 
        RowFilter: 
            AllRowsWildcard: {}
        ColumnWildcard: {}

Creating a DataCellsFilter using a row wild card and specified columns

The following example demonstrates how to create a DataCellsFilter resource using a row wild card and specified columns:

JSON


{
    "SampleDataCellsFilter": {
        "Type": "AWS::LakeFormation::DataCellsFilter",
        "Properties": {
            "TableCatalogId": "12345678910",
            "DatabaseName": "sample_db",
            "TableName": "sample_tbl",
            "Name": "sample_data_cells_filter",
            "RowFilter": {
                "AllRowsWildcard": {}
            },
            "ColumnNames": ["sample_column_1", "sample_column_2"]
        }
    }
}

YAML


SampleDataCellsFilter:
    Type: AWS::LakeFormation::DataCellsFilter
    Properties:
        TableCatalogId: "12345678910"
        DatabaseName: "sample_db" 
        TableName: "sample_tbl" 
        Name: "sample_data_cells_filter" 
        RowFilter: 
            AllRowsWildcard: {}
        ColumnNames: ["sample_column_1", "sample_column_2"]

Creating a DataCellsFilter using a row filter expression and a column wildcard

The following example demonstrates how to create a DataCellsFilter using a row filter expression and a column wildcard:

JSON


{
    "SampleDataCellsFilter": {
        "Type": "AWS::LakeFormation::DataCellsFilter",
        "Properties": {
            "TableCatalogId": "12345678910",
            "DatabaseName": "sample_db",
            "TableName": "sample_tbl",
            "Name": "sample_data_cells_filter",
            "RowFilter": {
                "FilterExpression": "sample_column_1 > 0"
            },
            "ColumnWildcard": {}
        }
    }
}

YAML


SampleDataCellsFilter:
    Type: AWS::LakeFormation::DataCellsFilter
    Properties:
        TableCatalogId: "12345678910"
        DatabaseName: "sample_db" 
        TableName: "sample_tbl" 
        Name: "sample_data_cells_filter" 
        RowFilter: 
            FilterExpression: "sample_column_1 > 0"
        ColumnWildcard: {}

Creating a DataCellsFilter using a row filter and specified columns

The following example demonstrates how to create a DataCellsFilter resource using a row filter and specified columns:

JSON


{
    "SampleDataCellsFilter": {
        "Type": "AWS::LakeFormation::DataCellsFilter",
        "Properties": {
            "TableCatalogId": "12345678910",
            "DatabaseName": "sample_db",
            "TableName": "sample_tbl",
            "Name": "sample_data_cells_filter",
            "RowFilter": {
                "FilterExpression": "sample_column_1 > 0"
            },
            "ColumnNames": ["sample_column_1", "sample_column_2"]
        }
    }
}

YAML


SampleDataCellsFilter:
    Type: AWS::LakeFormation::DataCellsFilter
    Properties:
        TableCatalogId: "12345678910"
        DatabaseName: "sample_db" 
        TableName: "sample_tbl" 
        Name: "sample_data_cells_filter" 
        RowFilter: 
            FilterExpression: "sample_column_1 > 0"
        ColumnNames: ["sample_column_1", "sample_column_2"]