Databricks

This article focuses on Databricks-specific considerations for users of the datavault4dbt package, specifically regarding the calculation of the multi-active hashdiff when working with Databricks. In Databricks, there are some limitations with string aggregation functions, which necessitate a customized approach to ensure deterministic results.

Problem: Lack of LIST_AGG Function in Databricks

Databricks does not support the LIST_AGG function, which is commonly used in other platforms to aggregate string values when calculating the multi-active hashdiff. The multi-active hashdiff is a unique hash calculation needed when there are multiple active records for a specific business key at the same time, and you need to ensure deterministic results.

In Databricks, the following functions must be used to replicate the behavior of LIST_AGG:

ARRAY_AGG(): Collects values into an array.

SORT_ARRAY(): Sorts the array to ensure a consistent order.

ARRAY_JOIN(): Joins the array elements into a string.

Example:

ARRAY_JOIN(SORT_ARRAY(ARRAY_AGG(column_name)), ',')

While this combination of functions mimics the functionality of LIST_AGG, it introduces a significant problem: you cannot directly specify an order by clause inside the ARRAY_AGG() function. This prevents sorting by the multi-active key, which is necessary to ensure deterministic hashdiff calculations.

Why Order by Multi-Active Key Is Important

To achieve consistent and reproducible results in hashdiff calculations, it is crucial to aggregate string values in a specific, predictable order. Without the ability to order by the multi-active key, the calculation may produce different hash values across executions for the same input data, which would break the integrity of the data vault model.

Solution: Using a Derived Column with ROW_NUMBER

To address this issue, we recommend introducing a derived column using the ROW_NUMBER() function to create a deterministic ordering within partitions based on the multi-active key. This ensures that string values are aggregated in a consistent order, even when working within the limitations of Databricks.

Steps:

1. Create a Derived Column with ROW_NUMBER()

The first step is to generate a row number within each partition of records that share the same single_source_hk (hash key for the source data). This ensures that each record in a group of multi-active records gets a unique and deterministic row number based on the multi-active key.

ROW_NUMBER() OVER (PARTITION BY single_source_hk ORDER BY multi_active_key) AS rn

2. Add the Derived Column to the Hashdiff Calculation

In the multi-active hashdiff calculation, include the rn (row number) as the first column. This will ensure that the records are consistently ordered based on the multi-active key, even when using the ARRAY_AGG, SORT_ARRAY, and ARRAY_JOIN combination.