Create and Manage Sledhouse Tables

This article provides you with a step-by-step guide on how to get started with Bobsled Sledhouse to create Sledhouse Tables.

FEATURE IN PUBLIC PREVIEW:
• While in Public Preview, expect some limitations. Your feedback is crucial as we build the product.
• We look forward to your feedback and to helping you integrate Sledhouse into your data architecture. Feel free to reach out if you have any questions about setup, configuration, or advanced use cases.

Prerequisites

• Bobsled Account: You must have access to Bobsled’s main application and the Sledhouse tab/feature enabled in your environment.

• To successfully create a Sledhouse Table, you must have at least one Data source preconfigured in Bobsled.

NOTE:
What you can see and do will differ based on your role and permissions.

Setup Instructions

Step 1: Choose Source

1. In the Bobsled Application, locate and select the Sledhouse Tables Tab, then select the “Create Sledhouse Table” button

2. In the wizard, select the data source you have configured before (e.g., BigQuery)

3. Choose a table from the list and click “continue.”

Step 2: Configure Sledhouse Table

1. Choose a name for your Sledhouse Table (a human-friendly name) and an Alias (A short, SQL-safe identifier when referencing this table in data products later)

2. Optionally review your schema and confirm the column structures following Bobsled data types

3. Set a replication pattern for your Sledhouse Table:

   • Append: Every new record in the source is appended

   • Update & Append: Provide a unique identifier and a “last updated” timestamp to merge changes

   • Overwrite: Replace the table each time with a full snapshot.

TIP:
The available replication patterns work in the same was as in Cloud Data Warehouse Sources to Cloud Data Warehouse Destination in Bobsled transfers.

4. Optionally set Partitioning for the Sledhouse Table.

   • Choose one or more columns to partition for performance optimization. If you anticipate frequent queries filtered by a specific column (e.g., state, zip_code, or event_date), use it as a partition key to speed up downstream queries.

TIP:
• Large datasets will significantly benefit from partitioning.
• When using time-based data types, Bobsled offers transformation options to tune the right field cardinality by choosing the right timeframe to partition by (hour, day, month, year).

NOTE:  
• Clustering/zOrder support—in addition to partitioning—is coming soon to give further performance tuning options.

5. Set the scheduling options.

   • Currently, Sledhouse runs a default hourly sync

   • Bobsled offers two ways of setting syncing preferences:

     • Simple scheduler (a set of fixed intervals up to 1 month cadence) and,

     • Cron scheduler (an advanced scheduling tool to suit your operational needs).

NOTE:
• Sledhouse defaults to hourly syncs and does not support intervals shorter than one hour. If you require more frequent syncs, please contact your account team.

• Bobsled Cron scheduler uses UNIX cron syntax ↗

Step 3: Review Sledhouse Table

1. Once happy with your Sledhouse Table configuration, click “Continue“

2. Review and optionally publish your Sledhouse Table as a Data Product

   • This immediately makes the table available for sharing as-is

3. Click “Save.” You have successfully set up a Sledhouse Table!

Managing Sledhouse Tables

On the Sledhouse Table page, you can review the state of the pipeline, and also:

• Schema: Displays all columns replicated from the source, eventually enabling type casting or other transformations

• Logs: Shows ongoing and past replication jobs, with status and potential errors

• Settings: Allows you to review the configuration (e.g., replication pattern, partitioning) and make changes.

Delete a Sledhouse Table

1. Locate the Sledhouse Table you wish to delete, and click on the name to enter its detail page.

2. Click on the ‘settings’ tab and scroll down.

3. Click on the ‘Delete Sledhouse Table’ button at the bottom.

NOTE:
• Bobsled prevents the deletion of any Sledhouse Table that has published Data Products associated with it.

• To proceed with deletion, all related Data Products must first be removed.

• For your convenience, Bobsled lists and links all dependent Data Products to help you manage this process efficiently.