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BigQuery Table Data List

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In this article

Overview

You can use this Snap to read and retrieve data from a Google BigQuery table.

Overview of settings with example values

Snap Type

The Google BigQuery Table Data List Snap is a Read-type Snap that reads table data from the BigQuery dataset and lists the data in the output.

Prerequisites

A valid Google BigQuery account with the required permissions.

Limitations and Known Issues

None.

Support for Ultra Pipelines

Works in Ultra Pipelines

Snap Views

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input 

Document

  • Min: 0

  • Max: 1

  • Mapper

  • JSON Generator

The Project ID and the Document ID.

Output

Document

  • Min: 1

  • Max: 1

  • JSON Parser

  • File Writer

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 when 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 ((blue star)): Indicates a list that is dynamically populated based on the configuration.

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

  • Add icon ( (blue star) ): Indicates that you can add fields in the field set.

  • Remove icon ( (blue star)): Indicates that you can remove fields from the field set.

  • Upload icon ((blue star) ): Indicates that you can upload files.

Field Name

Field Type

Field Dependency

Description

Label*

Default ValueBigQuery Table Data List
ExampleSales Leads Data List

String/Expression

None.

Enter a unique name for the Snap. You can modify this to be more specific, especially if you have more than one of the same Snap in your pipeline.

Project ID

Default Value: N/A
Example: test-project-12345

String/Expression/Suggestion

None.

Specify the project ID in which the dataset resides.

Dataset ID

Default Value: N/A
Example: dataset-12345

String/Expression/Suggestion

None.

Specify the dataset ID of the destination.

Table ID

Default Value: N/A
Example: table-12345

String/Expression/Suggestion

None.

Specify the table ID of the table you are creating.

Snap Execution

Default ValueValidate & Execute
Example: Disabled

Dropdown list

None.

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.

Examples

Reading a BigQuery Dataset and Listing the Table Data

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

BigQuery Table Data List Snap icon

Configure the Snap with the Project ID, Dataset ID, and Table ID of the dataset from which the table data is to be listed.

Settings for the Table Data List Snap

 

On validation, the Snap lists the table data in the output.

Output of the Table Data List Snap



Reading a BigQuery Dataset and Listing the Table Data After Filtering the Dataset

This example pipeline demonstrates how to read tables from a BigQuery dataset and list the data from a specific table in the output.

Pipeline showing BigQuery Table List, Filter, and BigQuery Table Data List.

First, configure the BigQuery Table List Snap with the Project ID and Dataset ID of the dataset from which the table data is to be listed.

Settings for the Table List Snap (warehouse example)

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

Output of the Table Data List Snap

 

Next, configure the Filter Snap with an expression that filters the data to limit it to just the Inventory table: $table_id=="Inventory"

Settings for the Filter Snap (filter by inventory table)

 

On validation, the Snap lists information about the filtered data in the output.

Output of the Filter Snap

 

Configure the Table Data List Snap with the Project ID, Dataset ID, and Table ID of the dataset from which the table data is to be listed.

Settings for the Table Data List Snap (warehouse example)

On validation, the Snap lists the table data in the output.

Output of the Table Data List Snap (warehouse inventory)

Download this pipeline.

Downloads

  1. Download and import the pipeline into SnapLogic.

  2. Configure Snap accounts, as applicable.

  3. Provide pipeline parameters, as applicable.

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Snap Pack History

 Click here to expand...
Google BigQuery Snap Pack

Snap Pack History

 Click to view/expand
Release Snap Pack VersionDateType  Updates
May 2024main26341 StableUpdated and certified against the current SnapLogic Platform release.
February 2024main25112 StableUpdated and certified against the current SnapLogic Platform release.
November 2023main23721 StableUpdated and certified against the current SnapLogic Platform release.

August 2023

main22460

 


Stable

Updated and certified against the current SnapLogic Platform release.

May 2023433patches22057  Latest

Introduced the Google BigQuery Upsert (Streaming) Snap, which enables you to perform bulk update/insert operations into a BigQuery table from existing tables or any input data stream.

May 2023433patches21955 LatestFixed an issue with the GBQ-Google Service Account that caused an input stream to remain open.
May 2023main21015 StableUpdated and certified to be compatible with the August SnapLogic Platform release.
February 2023432patches20962 LatestFixed an intermittent null pointer exception that occurred in the BigQuery Write Snap.
February 2023

432patches20298

 Latest
February 2023432patches19840 Latest

Fixed an issue with the Google BigQuery Bulk Load (Streaming) Snap that caused the Table not found message to display even when Create table if not present was selected.

February 2023main19844 Stable
November 2022431patches19301 LatestThe Google BigQuery Bulk Load (Streaming) Snap works as expected, with no active Timer threads remaining when the Pipeline execution fails. 
November 2022main18944 StableUpgraded with the latest SnapLogic Platform release.
August 2022main17386 Stable
4.29main15993 Stable

Upgraded with the latest SnapLogic Platform release.

4.28 Patch428patches15459 Latest
  • Fixed an issue with Google BigQuery Execute Snap, where the Snap displayed 404 Job not found error when calling a procedure.
  • Fixed an issue with the Google BigQuery Bulk Load (Cloud Storage) Snap where the Snap failed, because the access token expired when it had to wait longer to execute. With this fix, the Snap is reloaded to get refreshed access token.

4.28 Patch428patches14743 Latest
  • Fixed an issue with the Google BigQuery Execute Snap, where the Snap displayed an error when the input data contained a table having the record type column and its value was null.
  • Fixed an issue with the Google BigQuery Write Snap, when the input data contained complex data type columns (such as nested fields) and Create table if not present checkbox was selected.

4.28main14627 StableUpgraded with the latest SnapLogic Platform release.
4.27 Patch427patches13752 Latest

Upgraded Google BigQuery driver to 1.119.0 version to support time partition intervals by MONTH and YEAR.

4.27 Patch427patches13615 LatestFixed the table truncate 404 error with the Google BigQuery Load (Streaming) Snap by supporting the retry functionality. The Snap now waits in case of an error and retries before loading the data.
4.27 Patch427patches12691 Latest

Fixed an issue with the Google BigQuery Bulk Load (Cloud Storage) Snap, where the Snap failed with an exception for big query tables. The CreateDisposition is now set conditionally on the basis of the setting in the Create table if not present checkbox.

4.27

main12833

Stable

Enhanced the Google BigQuery Bulk Load (Cloud Storage) Snap with the following batching and retry properties to process input records:

  • Batching: Processes the input records in batches.

  • Batch Size: The number of records batched per request.

  • Batch Timeout (milliseconds): Time in milliseconds to elapse following which the batch, if not empty, will be processed even though it might be lesser than the given batch size.

4.26main11181 StableUpgraded with the latest SnapLogic Platform release.
4.25main9554
 
StableUpgraded with the latest SnapLogic Platform release.
4.24main8556
StableUpgraded with the latest SnapLogic Platform release.
4.23main7430
 
Stable
4.22main6403
 
StableUpgraded with the latest SnapLogic Platform release.
4.21snapsmrc542

 

StableUpgraded with the latest SnapLogic Platform release.
4.20 Patch google/bigquery8773 Latest

Fixed the NPE issue with stored procedures and DROP TABLE queries in the Google BigQuery Execute Snap.

4.20snapsmrc535
 
StableUpgraded with the latest SnapLogic Platform release.
4.19snaprsmrc528
 
StableUpgraded with the latest SnapLogic Platform release.
4.18snapsmrc523
 
StableUpgraded with the latest SnapLogic Platform release.
4.17ALL7402
 
Latest

Pushed automatic rebuild of the latest version of each Snap Pack to SnapLogic UAT and Elastic servers.

4.17snapsmrc515
 
Stable

Added the Snap Execution field to all Standard-mode Snaps. In some Snaps, this field replaces the existing Execute during preview check box.

4.16snapsmrc508
 
StableUpgraded with the latest SnapLogic Platform release.
4.15snapsmrc500
 
StableUpgraded with the latest SnapLogic Platform release.
4.14snapsmrc490
 
StableUpgraded with the latest SnapLogic Platform release.
4.13

snapsmrc486

 
StableUpgraded with the latest SnapLogic Platform release.
4.12

snapsmrc480

 
Stable

Added a new property Schema auto detect in the Google BigQuery Bulk Load (Cloud Storage) Snap to support CSV and JSON files where one or more columns in the source file may not contain any values. 

4.11snapsmrc465
 
Stable
  • Added new Snap: Google BigQuery Bulk Load (Cloud Storage)
  • Added new Snap: Google BigQuery Bulk Load (Streaming).
  • Updated Google Big Query Write Snap with a new Create table if not present property.
4.10 Patch google/bigquery4046 Latest

Addressed an issue when authenticating with Dynamic OAuth accounts.

4.10

snapsmrc414

 
StableUpgraded with the latest SnapLogic Platform release.
4.9snapsmrc405
 
StableUpgraded with the latest SnapLogic Platform release.
4.8 Patchbigquery2952 Latest

Supports refreshing OAuth access tokens during long-running pipeline executions. Fixed an issue with writing small batch sizes and when querying empty dataset tables.

4.8.0 Patchbigquery2813 Latest

Reload OAuth account from Platform when the access token expires during pipeline execution.

4.8

snapsmrc398

 
StableUpgraded with the latest SnapLogic Platform release.
4.7

snapsmrc382

 
StableUpgraded with the latest SnapLogic Platform release.
4.6snapsmrc362
 
StableUpgraded with the latest SnapLogic Platform release.
4.5.1

snapsmrc344

 
StableUpgraded with the latest SnapLogic Platform release.
4.4.1NA StableUpgraded with the latest SnapLogic Platform release.
4.4NA StableUpgraded with the latest SnapLogic Platform release.
4.3.2NA Stable
  • Resolved the following issues with the Google BigQuery Execute Snap:
    • throwing binary data in stacktrace and two error messages.
    • improve error handling for suggestions
    • improve error handling on bad queries
    • suggestion bubble missing for Destination table ID
  • Resolved an issue with Auto refresh token not working in Google BigQuery account.

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