feat(deletes): support item attribute conditions in API and consumer #7537
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…-attribute-conditions-in-consumer
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onewland
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Nov 17, 2025
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| def _execute_query( | ||
| query: Query, | ||
| storage: WritableTableStorage, | ||
| table: str, | ||
| cluster_name: Optional[str], | ||
| attribution_info: AttributionInfo, | ||
| query_settings: HTTPQuerySettings, | ||
| ) -> Result: |
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This method (and dependencies) should probably move out of snuba/web/delete_query.py since we no longer want to support the synchronous delete from an endpoint (everything should flow through Kafka and the LW deletion consumer). But it can be follow-up work.
onewland
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onewland
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| # Number of attribute buckets used in eap_items storage | ||
| # TODO: find a way to wire this in from a canonical source | ||
| NUM_ATTRIBUTE_BUCKETS = 40 |
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Bug: EAPItemsFormatter uses a hardcoded NUM_ATTRIBUTE_BUCKETS, causing incorrect bucket indexing if configuration changes, leading to silent delete failures.
Severity: CRITICAL | Confidence: 1.00
🔍 Detailed Analysis
The EAPItemsFormatter uses a hardcoded NUM_ATTRIBUTE_BUCKETS = 40 for calculating attribute bucket indices. If the num_attribute_buckets configuration changes (e.g., to 64), but the hardcoded value is not updated, delete queries will incorrectly calculate bucket indices. For example, an attribute hashing to 45 would target attributes_string_5 instead of attributes_string_45, leading to silent failures where data is not deleted as intended, causing data inconsistency.
💡 Suggested Fix
Parameterize EAPItemsFormatter to receive num_attribute_buckets as a constructor argument, injecting the value from the canonical storage configuration, similar to other transformers.
🤖 Prompt for AI Agent
Review the code at the location below. A potential bug has been identified by an AI
agent.
Verify if this is a real issue. If it is, propose a fix; if not, explain why it's not
valid.
Location: snuba/lw_deletions/formatters.py#L59-L61
Potential issue: The `EAPItemsFormatter` uses a hardcoded `NUM_ATTRIBUTE_BUCKETS = 40`
for calculating attribute bucket indices. If the `num_attribute_buckets` configuration
changes (e.g., to 64), but the hardcoded value is not updated, delete queries will
incorrectly calculate bucket indices. For example, an attribute hashing to 45 would
target `attributes_string_5` instead of `attributes_string_45`, leading to silent
failures where data is not deleted as intended, causing data inconsistency.
Did we get this right? 👍 / 👎 to inform future reviews.
Reference_id: 2749980
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MeredithAnya
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MeredithAnya
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Overall this seems good to me, but Im wondering what happens if a request has an attr value that doesn't match the type, like {"group_id": ["hello"]} ?
Also, do we need to be updating https://github.com/getsentry/sentry-kafka-schemas/blob/main/schemas/snuba-lw-deletions-eap-items.v1.json ?
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| # For each attribute, determine its type and bucket (if applicable) | ||
| for attr_name, attr_values in attribute_conditions.items(): | ||
| if not attr_values: |
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this seems like a case that shouldn't happen? should we be logging something if it does? or is this a valid case and im just missing something
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This PR enables (gated behind a runtime-config) deletions of EAP items by attributes.
Changes:
attributes_string_x['key_name']DeleteQueryMessagehas two new fields:attribute_conditionsandattribute_conditions_item_typepermit_delete_by_attribute, defaulting to offEnd-to-end tested locally, verification walk-through: https://www.notion.so/sentry/e2e-attribute-testing-2ab8b10e4b5d80cea5cfdc255cff5305