BigQuery Table List

In this article

Overview

You can use this Snap to list tables that are read from a BigQuery dataset.

Snap Type

BigQuery Table List Snap is a Read-type Snap that reads the tables from the BigQuery dataset and lists them in the output.

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

This Snap has at most one document input view.

The Project ID and the Document ID.

Output

Document

  • Min: 1

  • Max: 1

  • JSON Parser

  • File Writer

This Snap has exactly one document output view. The list of Table IDs along with their Project IDs, Dataset IDs, 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 List
ExampleBabynames Table List

String/Expression

Specify a unique name for the Snap. Modify this to be more specific, especially if you have more than one Snap of the same type in your Pipeline.

Project ID

Default Value: N/A
Example: Test-project-324543

String/Expression/Suggestion

Specify the project ID in which the dataset

Dataset ID

Default Value: N/A
Example: project-test-43433

String/Expression/Suggestion

Specify the dataset ID of the destination.

Detailed Information

Default value: Deselected

Checkbox

Select this checkbox to enable the Snap to access additional fields for displaying them in the output.

Snap Execution

Default ValueValidate & Execute
Example: Disabled

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

Reading a BigQuery Dataset and Listing the Tables

This example Pipeline demonstrates how to read tables from a BigQuery dataset and list the tables in the output.

Configure the Snap with the Project ID and the Dataset ID of the dataset from which the table names need to be listed.

On validation, the Snap lists the tables in the output.

Download this Pipeline. 

  File Modified

File Example_GBQ_Table_List.slp

Jul 22, 2022 by Gouri Bhagchandani

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_List.slp

Jul 22, 2022 by Gouri Bhagchandani

 


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