Elasticsearch MV_APPEND: Handling Null Values Gracefully

When working with Elasticsearch, understanding how its Query Language (ES|QL) functions, especially those dealing with multi-value fields, is crucial for effective data manipulation. One such function that often comes up in data transformation is MV_APPEND. This function is designed to append a value to a multi-valued field. However, the current behavior when dealing with null values can lead to unexpected results, often causing the entire output to become null. This article delves into this specific nuance of MV_APPEND and explores a more intuitive and user-friendly approach to handling null values.

The Current Behavior of MV_APPEND with Nulls

The MV_APPEND function in ES|QL is intended to be a straightforward tool for adding elements to a multi-value field. For instance, if you have a field foo that contains [1, 2] and you want to append [3, 4] using MV_APPEND(foo, [3, 4]), the result is [1, 2, 3, 4], which is exactly what you’d expect. The issue arises when one of the arguments provided to MV_APPEND is null. Let's examine the provided example:

from test | eval foobar = mv_append(foo, bar) | keep foo, bar, foobar

      foo      |      bar      |    foobar     
---------------+---------------+---------------
[1, 2]         |null           |null           
null           |[3, 4]         |null           
[1, 2]         |[3, 4]         |[1, 2, 3, 4] 

As you can see, when bar is null, the foobar field becomes null, even if foo contains values. Similarly, if foo is null and bar has values, foobar also becomes null. The only case where MV_APPEND produces a non-null result is when both foo and bar are non-null. This behavior can be quite surprising for users who might intuitively think of null as representing an empty list or a missing value that shouldn't necessarily invalidate the entire operation. In many programming contexts, appending to a list where one element is null might result in the null being ignored or handled as an empty element, rather than propagating the null to the entire result. This current design in ES|QL can lead to data loss or require additional, often complex, filtering and transformation steps to work around, especially when dealing with data that naturally contains nulls.

Why This Behavior is Problematic

This current MV_APPEND behavior presents several challenges for Elasticsearch users. Firstly, it deviates from a common expectation where null often signifies absence rather than an error condition that nullifies an entire operation. Users might reasonably expect that if they are appending a value to a list, and that value happens to be null, the list should either remain unchanged or the null should be appended as a distinct null element (if that's the desired outcome, which is less common but still a possibility). However, the current implementation throws an error, in essence, by returning null for the entire foobar field. This can be particularly problematic in data ingestion and transformation pipelines where null values are common. For instance, if you are trying to aggregate multiple fields into a single multi-value field, and one of the source fields is occasionally null, your aggregated field will unexpectedly become null, potentially disrupting downstream analysis or reporting. This forces developers to implement workarounds, such as pre-filtering or transforming null values into empty lists or specific placeholder values before calling MV_APPEND. These workarounds add complexity to the queries and can make them less readable and maintainable. Furthermore, it can be inefficient, as you might be processing data multiple times to handle these nulls. The lack of explicit control over how null values are treated by MV_APPEND can also lead to subtle bugs if not carefully managed, as the