BigQuery Table Delete

In this article

Overview

You can use this Snap to delete BigQuery tables.

Snap Type

BigQuery Table Delete Snap is a Write-type Snap.

Prerequisites

A valid Google BigQuery Account with the required permissions.

Support for Ultra Pipelines 

Works in Ultra Pipelines

Limitations and Known Issues

None.

Snap Views

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input 

Document

 

  • Min: 0

  • Max: 1

  • Mapper

  • JSON Generator

The Project ID, Dataset ID, and Table ID.

Output

Document

 

  • Min: 1

  • Max: 1

  • Mapper

The status of the table deletion and the details of the deleted table: Project ID, Dataset ID, Table ID, and Table Type.

Error

Error handling is a generic way to handle errors without losing data or failing the Snap execution. You can handle the errors that the Snap might encounter while running the Pipeline by choosing one of the following options from the When errors occur list under the Views tab:

  • Stop Pipeline Execution: Stops the current pipeline execution if the Snap encounters an error.

  • Discard Error Data and Continue: Ignores the error, discards that record, and continues with the remaining records.

  • Route Error Data to Error View: Routes the error data to an error view without stopping the Snap execution.

Learn more about Error handling in Pipelines.

Snap Settings

  • Asterisk ( * ): Indicates a mandatory field.

  • Suggestion icon (): Indicates a list that is dynamically populated based on the configuration.

  • Expression icon ( ): Indicates the value is an expression (if enabled) or a static value (if disabled). Learn more about Using Expressions in SnapLogic.

  • Add icon ( ): Indicates that you can add fields in the fieldset.

  • Remove icon ( ): Indicates that you can remove fields from the fieldset.

Field Name

Field Type

Description

Field Name

Field Type

Description

Label*

 

Default ValueBigQuery Table Delete
ExampleDelete Contract Employees

String

Specify a unique name for the Snap.

 

Project ID*

 

Default Value: N/A
Example: contract-project-123

String/Expression/Suggestion

Specify the project ID in which the dataset to be deleted resides.

Dataset ID*

 

Default Value: N/A
Example: contract_emp_names

String/Expression/Suggestion

Specify the ID of the dataset that you want to delete.

Table ID*

 

Default Value: N/A
Example: Contract_Emp123

String/Expression/Suggestion

Specify the ID of the target table that you want to delete.

Snap Execution

Default ValueExecute only
Example: Validate & Execute

Dropdown list

Select one of the following three modes in which the Snap executes:

  • Validate & Execute: Performs limited execution of the Snap, and generates a data preview during Pipeline validation. Subsequently, performs full execution of the Snap (unlimited records) during Pipeline runtime.

  • Execute only: Performs full execution of the Snap during Pipeline execution without generating preview data.

  • Disabled: Disables the Snap and all Snaps that are downstream from it.

Example

Deleting Dummy Tables from the Dataset

This example Pipeline demonstrates how to delete a dummy table from a dataset.

First, configure the BigQuery Execute Snap with the CREATE table query as highlighted in the image that executes the query.

On validating, the Snap processes the query to create a table. You can view the following output in the Snap’s preview.

Next, configure the BigQuery Delete Snap to delete the Dummy_del table from the babynames dataset that belongs to case16370 Project ID.

On validation, the Snap deletes the table and displays the status of the deletion and the details of the deleted table.

Download this Pipeline

Downloads

  1. Download and import the Pipeline into SnapLogic.

  2. Configure Snap accounts, as applicable.

  3. Provide Pipeline parameters, as applicable.

 

  File Modified

File Example_GBQ Table Delete_Snap_Delete existing table.slp

Jul 22, 2022 by Kalpana Malladi

 


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