> ## Documentation Index
> Fetch the complete documentation index at: https://docs.maia.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Table Delete Rows

export const ComponentMetadata = ({warehouses, unsupportedWarehouses = [], componentType, connectionInputs, connectionOutputs}) => {
  const allWarehouses = [...warehouses.map(w => ({
    name: w,
    supported: true
  })), ...unsupportedWarehouses.map(w => ({
    name: w,
    supported: false
  }))];
  return <div style={{
    background: 'var(--colors-background-light, #f9fafb)',
    border: '1px solid var(--colors-border-default, #e5e7eb)',
    borderRadius: '12px',
    padding: '20px 28px',
    marginBottom: '28px',
    boxShadow: '0 1px 4px rgba(0,0,0,0.10)'
  }}>
      <table style={{
    width: '100%',
    borderCollapse: 'collapse'
  }}>
        <tbody>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle',
    width: '180px'
  }}>Project Availability</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>
              <div style={{
    display: 'flex',
    flexWrap: 'wrap',
    gap: '8px'
  }}>
                {allWarehouses.map((w, i) => <span key={i} style={{
    background: w.supported ? '#dcfce7' : '#fee2e2',
    color: w.supported ? '#15803d' : '#b91c1c',
    border: `1px solid ${w.supported ? '#bbf7d0' : '#fca5a5'}`,
    borderRadius: '9999px',
    padding: '3px 12px',
    fontSize: '0.85rem',
    fontWeight: '500',
    whiteSpace: 'nowrap'
  }}>
                    {w.name} {w.supported ? '✅' : '❌'}
                  </span>)}
              </div>
            </td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Component Type</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>{componentType}</td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    paddingBottom: '14px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Connection Inputs</td>
            <td style={{
    paddingBottom: '14px',
    verticalAlign: 'middle'
  }}>{connectionInputs}</td>
          </tr>
          <tr>
            <td style={{
    fontWeight: '600',
    paddingRight: '32px',
    whiteSpace: 'nowrap',
    verticalAlign: 'middle'
  }}>Connection Outputs</td>
            <td style={{
    verticalAlign: 'middle'
  }}>{connectionOutputs}</td>
          </tr>
        </tbody>
      </table>
    </div>;
};

<ComponentMetadata warehouses={["Amazon Redshift"]} unsupportedWarehouses={["Snowflake", "Databricks", "BigQuery"]} componentType="Transformation" connectionInputs="One" connectionOutputs="Unlimited" />

The **Table Delete Rows** transformation component lets you delete rows from a target table. The component matches the rows to key values in an input flow—that is to say, the information received from an input component, such as [Table Input](/docs/components/table-input)—and deletes any rows that meet all the "match" conditions.

Multiple key column mappings can be entered. These mappings form an `AND` condition, so all mappings must match for the row to be deleted.

Deleting rows requires the use of a [Vacuum](/docs/components/vacuum) component afterward to recover space. The Table Delete Rows component does not arrange that vacuum for you. If you are removing a large portion of the table, it may be better to rewrite the rows you want to keep to a new table, then drop the existing table and rename the new one. For more information on vacuuming tables, read [Vacuuming Tables](https://docs.aws.amazon.com/redshift/latest/dg/t_Reclaiming_storage_space202.html).

### Use case

This component can be used to perform targeted deletions of rows within your data. For example, you can use it to:

* Remove discontinued products from a sales catalog by matching product codes to discontinued products.
* Remove invalid transactions from financial data by matching invalid transaction IDs or values.
* Delete personal data to comply with data protection rules by matching a customer's personally identifiable information.

***

## Properties

<ResponseField name="Name" type="string" required>
  A human-readable name for the component.
</ResponseField>

{/* <!-- param-start:[schema] | warehouses: [redshift] --> */}

<ResponseField name="Schema" type="drop-down" required>
  Select the table schema. The special value `[Environment Default]` uses the schema defined in the environment. For more information on using multiple schemas, read [Schemas](https://docs.aws.amazon.com/redshift/latest/dg/r_Schemas_and_tables.html).
</ResponseField>

{/* <!-- param-start:[targetTable] | warehouses: [redshift] --> */}

<ResponseField name="Target Table" type="drop-down" required>
  The table to delete rows from.
</ResponseField>

{/* <!-- param-start:[keyColumnMapping] | warehouses: [redshift] --> */}

<ResponseField name="Key Column Mapping" type="column editor" required>
  * **Source Column:** The source column from the input flow.
  * **Target Column** The target column from the selected target table.
</ResponseField>