Recommendations

Recommendations

Overview

Slingshot analyzes warehouse usage patterns to generate optimization suggestions for managed and unmanaged warehouses. Managed warehouses with consistent schedules for the last 30 days and unmanaged warehouses with 90 days of historical data generate recommendations.

Right-sizing recommendations isn’t just about saving. It’s also about maximizing performance. Slingshot uses query execution times to gauge performance. You decide whether or not to apply the recommendations after analyzing cost versus performance based on your business needs.

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Applying some recommendations may increase costs to improve performance. Read on to learn more about applying recommendations.

Easily spot recommendations at the top of the Home page, in Your Warehouses, or see all your recommendations on the centralized Recommendations page.

Let’s dive into what triggers a recommendation, what’s in it and how making adjustments affects queries on your warehouses, then learn what to do with it.

Generating Recommendations

Slingshot analyzes warehouse trends to find areas of optimization for your warehouses based on idleness, query load, queueing, spillage, and utilization. Slingshot identifies 1 of 11 possible issues.

Potential Warehouse IssueDefinition
High auto-suspendWhen warehouses run for long periods of inactivity before suspending activity
High idlenessWhen a warehouse consumes credits without executing any queries for long periods of time
High query loadSeveral queries run at once, reduces performance and strains compute resources
High average (avg.) queueA large number of queries waiting to be processed, impacts overall warehouse performance
High spillQueries that require additional compute resources and rely on spilling data to remote storage for execution
Long queryQueries take a substantial amount of time to complete due complexity, size, or variety of factors
Low query loadAn underutilized warehouse that runs minimal queries
Low average (avg.) queueAn underutilized warehouse with only a few tasks waiting in queue
Low spillA warehouse with capacity to run more queries, it’s executing without spilling to remote storage
No auto-suspendDuring periods of inactivity the warehouse continues to run and consume credits
No warehouse loadAn inactive warehouse, underutilized
Short queryQueries execute quickly, underutilized

Hourly analysis on each warehouse looks for a single issue or a combination of issues to initiate a recommendation. There are 17 possible issue combinations. Combinations consist of a single issue or two or more issues together.

For example, a finding of High query load, Long query, High spill, High avg queue results in a recommendation to increase max cluster count.

Red tags on the Recommendation page identify the trigger and action. Dissect a Recommendation in Anatomy of a Recommendation.

Recommendation
Suggested actionTrigger (includes single issues and combinations)
Decrease warehouse sizeNull query Load
Low query load, Short query, Low spill
Low query load, Short query
Low query load, Low spill
Low query load, Low avg queue
Increase max cluster countHigh query load, High avg queue
High query load, Long query, High spill, High avg queue
High query load, Long query, High avg queue
Increase warehouse sizeLong query, High spill
Long query
High spill
Decrease warehouse size and Increase max cluster countHigh query load, Short query, Low spill, High avg queue
High query load, Short query, High avg queue
High query load, Low spill, High avg queue
Decrease auto-suspendHigh idleness
High auto-suspend
No auto-suspend
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Decreasing auto-suspend applies to shortening the period of inactivity necessary for a warehouse to enter suspension mode. No auto-suspend means there isn’t an auto-suspend time set and the warehouse could benefit from setting a timeout value.

Anatomy of a Recommendation

Review and adjust recommendations or apply them as is. The Recommendation consists of four parts.

  • Why you’re seeing this recommendation: A summary of the Slingshot-identified Issues, current cost and performance info (Average query execution time and Monthly cost), and the Projected results (cost and performance) should you apply the recommendation as suggested without making changes.

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Making changes to the recommendation, negates the Projected results for the current month.

  • What to optimize: The Recommendation settings and schedule compare the current settings and schedule with the recommended settings and schedule. Make adjustments to the suggested parameters or settings. Learn more about editing recommendations, see Manage Recommendations.
    • Compare schedules: Toggle between the current and recommended schedules to see which time blocks need your attention based on Slingshot’s hourly analysis of your warehouse’s performance.
    • The current schedule flags areas of opportunity in red with a flag icon. Selecting any red time block displays an issue list and explanation.
  • How optimization happens: Review the Projected impact on queries and Historical warehouse performance tabs to gain insights about the impacts of the issues and how taking Slingshot’s suggestions improves performance or costs. These tabs provide you with valuable analysis tools and answers the key question, what happens when I apply this recommendation.

Manage Recommendations

Slingshot allows tenant admins and warehouse owners to manage recommendations. Tenant admins see all the warehouses and recommendations for an organization. They assign unassigned warehouses to a business organization or business unit making them available to Warehouse owners.

Sort columns in ascending or descending order on the Recommendations table by clicking any header. An arrow appears (↑ or ↓). Press again to reset the table and remove the arrow.

Easily export Recommendations to a .csv file with a single click on the blue Export as CSV text to the right of the search bar.

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Warehouse owners are the only ones with the ability to tweak or apply recommendations.

Apply recommendation

  1. Use the Apply recommendation button.
  2. Enter a Business justification.
  3. Select Apply recommendation to submit the changes for approval.

Edit recommendation settings

  1. Select Edit in the Warehouse settings & schedule section.
  2. Review or adjust:
    • Warehouse environment
    • Warehouse template
    • Statement timeout value
    • QAS Scale factor
  3. Press Save.
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QAS Scale factor isn’t visible unless you’ve enabled QAS.

Edit the recommended schedule

  1. Select any Time block to view the Schedule Block Details.
  2. Make adjustments to:
    • Day
    • Start time
    • End time
    • Warehouse size
    • Cluster min
    • Cluster max
    • Auto-suspend
    • Scaling policy
  3. Save.

To add another schedule block,

  1. Select Add schedule block on the Recommended schedule tab.

View Recommendations

From Your Warehouses

  1. Go to Your Warehouses on the left navigation menu.
  2. Select the Managed or Unmanaged tab.
  3. Find a warehouse with the icon.
  4. Use the icon to open the Recommendation.
  5. Review your recommendation.

From Recommendations

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Click any list header to re-sort the listings in ascending or descending order.
  1. Select Recommendations on the left navigation menu.
  2. Click a warehouse name.
  3. The recommendation opens in a new browser tab.
  4. Review your recommendation.

Export Data to CSV

To export the recommendation to a CSV file,

  1. From the Recommendations page, press Export as CSV.
  2. The file downloads automatically.
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You may have to allow downloads. Your browser will alert you. Select Allow to begin the download.