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Databricks - Run Job

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Overview

You can use this Snap to execute a job, check its status in Databricks, and, based on the job's status, complete or fail the pipeline. The Snap triggers the task to execute and then periodically checks its status. The Snap stops after the job is executed. However, if the pipeline is canceled before the task is finished, the Snap requests to stop the task.

databricks-run-job-overview.png

Example

Run Job on a Cluster

The following example pipeline demonstrates how to run a job specified in the notebook on a cluster.Snap Type

The Databricks - Run Job Snap is a Write-type Snap.

Prerequisites

  • Valid client ID.

  • A valid account with the required permissions.

Support for Ultra Pipelines

Limitations and Known Issues

None.

Snap Views

Type

Format

Number of Views

Examples of Upstream and Downstream Snaps

Description

Input 

Document

 

  • Min: 0

  • Max: 1

  • Mapper

  • Copy

Requires a valid task name, notebook path, and cluster-info.

Output

Document

 

  • Min: 1

  • Max: 1

  • Mapper

  • Filter

Executes the selected notebook.

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

Description

Label*

 

Default ValueDatabricks - Run Job
ExampleRun Job

String

Specify the 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.

 

Task name*

 

Default Value: N/A
Example: Test username and password

String/Expression

Specify the name of the task to perform the job.

Notebook path*

 

Default Value: N/A
Example: /Users/johndoe@snaplogic.com/notebook

String/Expression/Suggestion

Specify the path of the saved notebook that will run in this job. Notebook is a web-based interface that allows you to create, edit, and execute data science and data engineering workflows. Learn more about Databricks notebooks.

Cluster*

 

Default Value: N/A
Example: Code Ammonite - Shared Compute Cluster - V2

String/Expression/Suggest

Specify the cluster to run the job within its environment.

Parameter(s)

Use this field set to specify the parameters to run the job.

Key*

Default Value: N/A
ExampleAge

String/Expression

Specify the parameter key.

Value*

Default Value: N/A
Example35

String/Expression

Specify the parameter value.

Interval check (seconds)*

 

Default Value10
Example15

Integer/Expression

Specify the number of seconds to wait before checking the status of the task.

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

Run Job on a Cluster

The following example pipeline demonstrates how to run a job specified in the notebook on a cluster.

databricks-run-job-example-overview.png

Download this pipeline.

Step 1: Configure the Databricks - Run Job Snap with the following settings:

a. Task name: Specify the task the Databricks - Run Job Snap must perform in this field.

b. Notebook path: Specify the path to the Databricks notebook that contains the code to be executed. This path indicates the location within the Databricks environment where the notebook is stored.

c. Cluster: Specify the cluster on which the job must be executed. The cluster configuration (including computational resources) is predefined and identified by this name and ID.

d. Interval check (seconds): Specify the frequency (in seconds) at which the Snap will check the status of the running job. In this case, it will check every 10 seconds.

Databricks - Run Job Configuration

Databricks - Run Job Output

databricks-run-job-config.png

databricks-run-job-output.png

Step 2: Configure the Mapper Snap to store the result status of the Databricks - Run Job Snap. On validation, the Mapper Snap displays the job success message.

mapper-config.pngmapper-output.png

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Snap Pack History

Release

Snap Pack Version

Date

Type

Updates

August 2024

main27765

Stable

Upgraded the org.json.json library from v20090211 to v20240303, which is fully backward compatible.

May 2024

437patches27246

Latest

Added Databricks - Run Job. This Snap executes a job, checks its status in Databricks, and, based on the job's status, completes or fails the pipeline.

May 2024

437patches26400

Latest

Fixed an invalid session handle issue with the Databricks Snap Pack that intermittently triggered an error message when the Snaps failed to connect with Databricks to execute the SQL statement.

May 2024

main26341

Stable

Updated the Delete Condition (Truncates a Table if empty) field in the Databricks - Delete Snap to Delete condition (deletes all records from a table if left blank) to indicate that all entries will be deleted from the table when this field is blank, but no truncate operation is performed.

February 2024

main25112

Stable

Updated and certified against the current SnapLogic Platform release.

November 2023

main23721

Stable

Updated and certified against the current SnapLogic Platform release.

August 2023

main22460

Stable

Updated and certified against the current SnapLogic Platform release.

May 2023

433patches21630

Latest

Enhanced the performance of the Databricks - Insert Snap to improve the amount of time it takes for validation.

May 2023

main21015

Stable

Upgraded with the latest SnapLogic Platform release.

February 2023

main19844

Stable

Upgraded with the latest SnapLogic Platform release.

November 2022

main18944

Stable

The Databricks - Insert Snap now creates the target table only from the table metadata of the second input view when the following conditions are met:

  • The Create table if not present checkbox is selected.

  • The target table does not exist.

  • The table metadata is provided in the second input view.

September 2022

430patches18305

Latest

The following fields are added to each Databricks Snap as part of this enhancement:

  • Number of Retries: The number of attempts the Snap should make to perform the selected operation when the Snap account connection fails or times out.

  • Retry Interval (seconds): The time interval in seconds between two consecutive retry attempts.

September 2022

430patches17796

Latest

The Manage Queued Queries property in the Databricks Snap Pack enables you to decide whether a given Snap should continue or cancel executing the queued Databricks SQL queries.

August 2022

main17386

Stable

Upgraded with the latest SnapLogic Platform release.

4.29.2.0

42920rc17045

Latest

A new Snap Pack for Databricks Lakehouse Platform (Databricks or DLP) introduces the following Snaps:

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