Skip to content

find_greater_value

find_greater_value(arr, x)

Description

Return the offset (zero-based index) of the first value in arr where value >= x (or null if no value is greater than x).

Usage

Call or Deploy find_greater_value ?
Call find_greater_value directly

The easiest way to use bigfunctions

  • find_greater_value function is deployed in 39 public datasets for all of the 39 BigQuery regions.
  • It can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
  • (You need to use the dataset in the same region as your datasets otherwise you may have a function not found error)

Public BigFunctions Datasets

Region Dataset
eu bigfunctions.eu
us bigfunctions.us
europe-west1 bigfunctions.europe_west1
asia-east1 bigfunctions.asia_east1
... ...
Deploy find_greater_value in your project

Why deploy?

  • You may prefer to deploy find_greater_value in your own project to build and manage your own catalog of functions.
  • This is particularly useful if you want to create private functions (for example calling your internal APIs).
  • Get started by reading the framework page

Deployment

find_greater_value function can be deployed with:

pip install bigfunctions
bigfun get find_greater_value
bigfun deploy find_greater_value

Examples

1. When a strictly greater value exists in array

select bigfunctions.eu.find_greater_value([0, 20, 50, 80, 100], 25)

select bigfunctions.us.find_greater_value([0, 20, 50, 80, 100], 25)

select bigfunctions.europe_west1.find_greater_value([0, 20, 50, 80, 100], 25)

+--------+
| offset |
+--------+
| 2      |
+--------+

2. When an identical value exists in array

select bigfunctions.eu.find_greater_value([0, 20, 50, 80, 100], 20)

select bigfunctions.us.find_greater_value([0, 20, 50, 80, 100], 20)

select bigfunctions.europe_west1.find_greater_value([0, 20, 50, 80, 100], 20)

+--------+
| offset |
+--------+
| 1      |
+--------+

3. When a greater value does NOT exist in array

select bigfunctions.eu.find_greater_value([0, 20, 50, 80, 100], 110)

select bigfunctions.us.find_greater_value([0, 20, 50, 80, 100], 110)

select bigfunctions.europe_west1.find_greater_value([0, 20, 50, 80, 100], 110)

+--------+
| offset |
+--------+
| null   |
+--------+

Use cases

Use Case: Finding the appropriate pricing tier

Imagine you have a table of pricing tiers for a product, with each tier defined by a usage threshold and a corresponding price. You could use find_greater_value to efficiently determine the correct pricing tier for a given customer's usage.

Example Scenario:

A software company offers different pricing tiers based on the number of API calls made per month:

Tier API Calls Price
Free 0-1,000 $0
Basic 1,001-5,000 $25
Premium 5,001-10,000 $50
Enterprise > 10,000 $100

BigQuery Implementation:

WITH PricingTiers AS (
    SELECT [1000, 5000, 10000] AS api_call_thresholds,
           [0, 25, 50, 100] AS prices
),
CustomerUsage AS (
    SELECT 'customer_A' AS customer_id, 7500 AS api_calls
)
SELECT
    CustomerUsage.customer_id,
    CustomerUsage.api_calls,
    PricingTiers.prices[SAFE_OFFSET(bigfunctions.YOUR_REGION.find_greater_value(PricingTiers.api_call_thresholds, CustomerUsage.api_calls))] AS price
FROM CustomerUsage
CROSS JOIN PricingTiers;

Explanation:

  1. PricingTiers CTE: This CTE stores the API call thresholds and corresponding prices as arrays.
  2. CustomerUsage CTE: This CTE represents the customer's API usage.
  3. Main Query:
  4. It joins CustomerUsage and PricingTiers.
  5. find_greater_value searches the api_call_thresholds array for the first value greater than or equal to the customer's api_calls. This returns the index (offset) of the appropriate tier.
  6. SAFE_OFFSET handles cases where the usage exceeds all defined tiers (e.g., > 10,000), returning the last price in the array.

Result:

customer_id api_calls price
customer_A 7500 50

This example demonstrates how find_greater_value can be used for efficient lookups in tiered data, eliminating the need for complex CASE statements or joins. This approach is particularly useful when dealing with a large number of tiers or when the tiers are subject to change, as updating the arrays is much simpler than modifying numerous CASE conditions. You could extend this to other use cases such as tax brackets, shipping costs based on weight, or commission rates based on sales volume. Remember to replace YOUR_REGION with your BigQuery region (e.g. us, eu, us-central1).

Need help or Found a bug?
Get help using find_greater_value

The community can help! Engage the conversation on Slack

We also provide professional suppport.

Report a bug about find_greater_value

If the function does not work as expected, please

  • report a bug so that it can be improved.
  • or open the discussion with the community on Slack.

We also provide professional suppport.

Show your ❤ by adding a ⭐ on