feat(data-explore): Add support in EAP to filter Array by elements

[manessaraj]

Current implementation of arrays in TraceItemTable endpoint transforms arrays as array of strings, and then only allows LIKE/NOT_LIKE filter on them.

With this change, arrays will preserve their original type, and client can filter EAP items by element of an array attribute.
To preserve the type, array is converted to JSON string, (clickhouse-driver doesn't support Array(JSON) type, as discussed in this PR), and post processing of results recovers the original array by decoding JSON string.

To filter, predicate maps arrays to corresponding type and use array exists with element filter.

Example Clickhouse query is:

SELECT (
    cast(lower(leftPad(hex(item_id), if(
        greater(length(hex(item_id)), 16), 32, 16), '0')), 'String'
    ) AS `sentry.item_id_TYPE_STRING`
), (toJSONString(attributes_array.`tags`::Array(
    JSON)) AS tags_TYPE_ARRAY
)
FROM eap_items_1_local
WHERE in(
    project_id, [1, 2, 3]
)
AND equals(organization_id, 1)
AND less(
    timestamp, toDateTime('2026-04-24 14:00:00')
)
AND greaterOrEquals(timestamp, toDateTime('2026-04-24 08:00:00'))
AND arrayExists(x -> equals(lower(x), lower('error')), (arrayMap(x -> coalesce(
    x.`String`::Nullable(String), toString(x.`Int`::Nullable(Int64)), toString(x.`Double`::Nullable(Float64)), x.`Bool`::Nullable(String)), attributes_array.`tags`::Array(
        JSON)) AS tags_TYPE_ARRAY__array_members
    )
)
AND lessOrEquals(sampling_factor, 1)
AND greater(sampling_factor, 0)
AND equals(item_type, 1)
LIMIT 10001 OFFSET 0

[linear-code]

EXP-912 Add EAP support for searching a value within an Array

[cursor]

Array aggregation uses wrong existence check after field type change

Medium Severity

_resolve_field_and_existence correctly computes f.notEmpty(field) for TYPE_ARRAY, but aggregation_to_expression discards this field_exists and calls _array_aggregation_to_expression without it. Inside _array_aggregation_to_expression, get_field_existence_expression(field) is re-computed on the JsonPath object, which falls through to f.isNotNull(field) since JsonPath isn't a FunctionCall. Per the codebase comment, missing JSON array keys return empty arrays (not NULL), so isNotNull incorrectly treats missing attributes as present. This changes the aggregation result from NULL to 0 when no rows have the attribute.

Additional Locations (2)

• snuba/web/rpc/v1/resolvers/common/aggregation.py#L885-L889
• snuba/web/rpc/v1/resolvers/common/aggregation.py#L862-L863

 

^{Reviewed by Cursor Bugbot for commit ee6a796. Configure here.}

[onewland]

seems generally fine, I think, pending tests passing. Have we documented clearly somewhere what the right behavior is for null because I'm confused and not really following. Maybe literally a NULL.md somewhere in snuba/protos?

[onewland]

Is there a repeat of this logic tree elsewhere that could be reused or put in a common place?

[manessaraj]

seems generally fine, I think, pending tests passing. Have we documented clearly somewhere what the right behavior is for null because I'm confused and not really following. Maybe literally a NULL.md somewhere in snuba/protos?

Good Idea. let me finalize this, I need to ask product about this.

[manessaraj]

seems generally fine, I think, pending tests passing. Have we documented clearly somewhere what the right behavior is for null because I'm confused and not really following. Maybe literally a NULL.md somewhere in snuba/protos?

Good Idea. let me finalize this, I need to ask product about this.

1. None/Null Values: Arrays with None/Null are silently dropped in EAP Items processor.
2. If array is empty, you have empty values in the JSON.
3. If array has null values, null values are skipped.

[cursor]

Cursor Bugbot has reviewed your changes and found 2 potential issues.

There are 3 total unresolved issues (including 1 from previous review).

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