bigfunctions > find_greater_value
find_greater_value¶
Call or Deploy find_greater_value
?
✅ You can call this find_greater_value
bigfunction directly from your Google Cloud Project (no install required).
- This
find_greater_value
function is deployed inbigfunctions
GCP project in 39 datasets for all of the 39 BigQuery regions. You need to use the dataset in the same region as your datasets (otherwise you may have a function not found error). - Function is public, so it can be called by anyone. Just copy / paste examples below in your BigQuery console. It just works!
- You may prefer to deploy the BigFunction in your own project if you want 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). Discover the framework
Public BigFunctions Datasets:
Region | Dataset |
---|---|
eu |
bigfunctions.eu |
us |
bigfunctions.us |
europe-west1 |
bigfunctions.europe_west1 |
asia-east1 |
bigfunctions.asia_east1 |
... | ... |
Description¶
Signature
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
).
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 |
+--------+
Need help using find_greater_value
?
The community can help! Engage the conversation on Slack
For professional suppport, don't hesitate to chat with us.
Found a bug using 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.
For professional suppport, don't hesitate to chat with us.
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:
PricingTiers
CTE: This CTE stores the API call thresholds and corresponding prices as arrays.CustomerUsage
CTE: This CTE represents the customer's API usage.- Main Query:
- It joins
CustomerUsage
andPricingTiers
. find_greater_value
searches theapi_call_thresholds
array for the first value greater than or equal to the customer'sapi_calls
. This returns the index (offset) of the appropriate tier.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
).
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