feat: implemented filter aggregation

[mdashti]

Ticket(s) Closed

• Closes Add Elasticsearch Filter Aggregation Support quickwit-oss/tantivy#2706

What

Implements filter aggregation support in Tantivy, enabling multiple filtered aggregations in a single query.

Why

Currently, there's no way to compute aggregations on different filtered subsets of documents in a single query. Users must run separate queries for each filter, which is slow and inefficient. For example, computing "average price overall + average price for t-shirts + count of electronics" requires three separate queries.

Elasticsearch's filter aggregation solves this by creating a single bucket containing documents matching a query, with support for nested sub-aggregations. This is a common analytics pattern that Tantivy now supports!

How

Added a new FilterAggregation bucket aggregation type that:

1. Accepts both query strings (parsed via QueryParser) and direct Query objects for custom query types
2. Uses DocumentQueryEvaluator to evaluate filter queries per-document during aggregation collection, avoiding separate query executions
3. Extended aggregation collectors to receive SegmentReader references, enabling filter aggregations to create query weights and scorers per segment

Some Implementation Details:

• FilterAggregation supports two modes:
  • FilterQuery::QueryString: Parsed using Tantivy's standard QueryParser
  • FilterQuery::Direct: Accepts Box<dyn Query> for custom query extensions
• FilterSegmentCollector evaluates the filter query on each document collected by the main query
• Documents matching the filter are counted and passed to sub-aggregation collectors
• Results include doc_count and flattened sub-aggregation results

Tests

Test suite with 20 tests covering:

• Basic Filtering: Single filters, no matches, multiple independent filters
• Query Types: Term queries, range queries, boolean queries, bool field queries
• Nested Filters: 2-level nesting, deep nesting (4+ levels), multiple branches at each level
• Sub-Aggregations: Terms aggregations, multiple metric aggregations
• Edge Cases: Empty indexes, malformed queries, base query interaction
• Custom Queries: Direct Query objects, serialization behavior, equality checks
• Correctness: Validation against equivalent separate query execution

All tests use the assert_agg_results! macro for clean, consistent result validation with floating-point tolerance.

[philippemnoel]

Would it make sense for us to get feedback from upstream Tantivy team for this?

[stuhood]

Partial review: overall, looks really solid.

Thanks @mdashti!

[mdashti]

Would it make sense for us to get feedback from upstream Tantivy team for this?

@philippemnoel Here's the upstream PR: quickwit-oss#2711

[mdashti]

@stuhood Thanks for the feedback.

[stuhood]

Looks good to me, thanks!

Please wait to land until the consumer PR is almost ready.

[stuhood]

Thanks!