issue： #46033
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## Pull Request Summary: Entity-Level TTL Field Support
### Core Invariant and Design
This PR introduces **per-entity TTL (time-to-live) expiration** via a
dedicated TIMESTAMPTZ field as a fine-grained alternative to
collection-level TTL. The key invariant is **mutual exclusivity**:
collection-level TTL and entity-level TTL field cannot coexist on the
same collection. Validation is enforced at the proxy layer during
collection creation/alteration (`validateTTL()` prevents both being set
simultaneously).
### What Is Removed and Why
- **Global `EntityExpirationTTL` parameter** removed from config
(`configs/milvus.yaml`, `pkg/util/paramtable/component_param.go`). This
was the only mechanism for collection-level expiration. The removal is
safe because:
- The collection-level TTL path (`isEntityExpired(ts)` check) remains
intact in the codebase for backward compatibility
- TTL field check (`isEntityExpiredByTTLField()`) is a secondary path
invoked only when a TTL field is configured
- Existing deployments using collection TTL can continue without
modification
The global parameter was removed specifically because entity-level TTL
makes per-entity control redundant with a collection-wide setting, and
the PR chooses one mechanism per collection rather than layering both.
### No Data Loss or Behavior Regression
**TTL filtering logic is additive and safe:**
1. **Collection-level TTL unaffected**: The `isEntityExpired(ts)` check
still applies when no TTL field is configured; callers of
`EntityFilter.Filtered()` pass `-1` as the TTL expiration timestamp when
no field exists, causing `isEntityExpiredByTTLField()` to return false
immediately
2. **Null/invalid TTL values treated safely**: Rows with null TTL or TTL
≤ 0 are marked as "never expire" (using sentinel value `int64(^uint64(0)
>> 1)`) and are preserved across compactions; percentile calculations
only include positive TTL values
3. **Query-time filtering automatic**: TTL filtering is transparently
added to expression compilation via `AddTTLFieldFilterExpressions()`,
which appends `(ttl_field IS NULL OR ttl_field > current_time)` to the
filter pipeline. Entities with null TTL always pass the filter
4. **Compaction triggering granular**: Percentile-based expiration (20%,
40%, 60%, 80%, 100%) allows configurable compaction thresholds via
`SingleCompactionRatioThreshold`, preventing premature data deletion
### Capability Added: Per-Entity Expiration with Data Distribution
Awareness
Users can now specify a TIMESTAMPTZ collection property `ttl_field`
naming a schema field. During data writes, TTL values are collected per
segment and percentile quantiles (5-value array) are computed and stored
in segment metadata. At query time, the TTL field is automatically
filtered. At compaction time, segment-level percentiles drive
expiration-based compaction decisions, enabling intelligent compaction
of segments where a configurable fraction of data has expired (e.g.,
compact when 40% of rows are expired, controlled by threshold ratio).
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---------
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
issue: #39157
Overview:
Support search by PK by resolving IDs to vectors on Proxy side. Upgrade
go-api to adapt to new proto definitions.
Design:
- Upgrade milvus-proto/go-api to latest master.
- Implement handleIfSearchByPK in Proxy: resolve IDs to vectors via
internal Query, then rewrite SearchRequest.
- Adapt to 'SearchInput' oneof field in SearchRequest across client and
handlers.
- Fix binary vector stride calculation bug in placeholder utils.
Compatibility:
- Old Pymilvus can still work w/o this feature
What is included:
- Dense and Sparse
- Multi vector fields
- Rejection on BM25
What is **not** include:
- Hybrid Search
- EmbeddingList
- Restful API
Signed-off-by: Li Liu <li.liu@zilliz.com>
#44212
Also, record metrics only when storageUsageTracking is enabled.
Use MB for scanned_remote counter and scanned_total counter metrics to
avoid overflow.
---------
Signed-off-by: chasingegg <chao.gao@zilliz.com>
issue: #29735
Implement partial field update functionality for upsert operations,
supporting scalar, vector, and dynamic JSON fields without requiring all
collection fields.
Changes:
- Add queryPreExecute to retrieve existing records before upsert
- Implement UpdateFieldData function for merging data
- Add IDsChecker utility for efficient primary key lookups
- Fix JSON data creation in tests using proper map marshaling
- Add test cases for partial updates of different field types
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
The convertion of byte slice to string may copy the underline data which
may cause extra memory and cpu time for httpserver
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
The partition num shall be determined by core logic if user did not
specifiy the partition num in request.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
if nq>2, restful will flatten all the res. If one nq res has duplicate
pks, the length of this slice will be less then topk. This pr
will attach topks in the output.
Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
#38077
remove the check for two reason
1. server will do the same to make sure use the correct database;
2. each req has an additional overhead of calling the proxy to check
database.
Signed-off-by: lixinguo <xinguo.li@zilliz.com>
Co-authored-by: lixinguo <xinguo.li@zilliz.com>
Custom `jsonRender` that encodes JSON data directly into the response
stream, it uses less memory since it does not buffer the entire JSON
structure before sending it, unlike `c.JSON` in `HTTPReturn`, which
serializes the JSON fully in memory before writing it to the response.
Benchmark testing shows that, using the custom render incurs no
performance loss and reduces memory consumption by nearly 50%.
issue: https://github.com/milvus-io/milvus/issues/37671
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
