related: #36380
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- Core invariant: aggregation is centralized and schema-aware — all
aggregate functions are created via the exec Aggregate registry
(milvus::exec::Aggregate) and validated by ValidateAggFieldType, use a
single in-memory accumulator layout (Accumulator/RowContainer) and
grouping primitives (GroupingSet, HashTable, VectorHasher), ensuring
consistent typing, null semantics and offsets across planner → exec →
reducer conversion paths (toAggregateInfo, Aggregate::create,
GroupingSet, AggResult converters).
- Removed / simplified logic: removed ad‑hoc count/group-by and reducer
code (CountNode/PhyCountNode, GroupByNode/PhyGroupByNode, cntReducer and
its tests) and consolidated into a unified AggregationNode →
PhyAggregationNode + GroupingSet + HashTable execution path and
centralized reducers (MilvusAggReducer, InternalAggReducer,
SegcoreAggReducer). AVG now implemented compositionally (SUM + COUNT)
rather than a bespoke operator, eliminating duplicate implementations.
- Why this does NOT cause data loss or regressions: existing data-access
and serialization paths are preserved and explicitly validated —
bulk_subscript / bulk_script_field_data and FieldData creation are used
for output materialization; converters (InternalResult2AggResult ↔
AggResult2internalResult, SegcoreResults2AggResult ↔
AggResult2segcoreResult) enforce shape/type/row-count validation; proxy
and plan-level checks (MatchAggregationExpression,
translateOutputFields, ValidateAggFieldType, translateGroupByFieldIds)
reject unsupported inputs (ARRAY/JSON, unsupported datatypes) early.
Empty-result generation and explicit error returns guard against silent
corruption.
- New capability and scope: end-to-end GROUP BY and aggregation support
added across the stack — proto (plan.proto, RetrieveRequest fields
group_by_field_ids/aggregates), planner nodes (AggregationNode,
ProjectNode, SearchGroupByNode), exec operators (PhyAggregationNode,
PhyProjectNode) and aggregation core (Aggregate implementations:
Sum/Count/Min/Max, SimpleNumericAggregate, RowContainer, GroupingSet,
HashTable) plus proxy/querynode reducers and tests — enabling grouped
and global aggregation (sum, count, min, max, avg via sum+count) with
schema-aware validation and reduction.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: MrPresent-Han <chun.han@gmail.com>
Co-authored-by: MrPresent-Han <chun.han@gmail.com>
issue: #46635
## Summary
- Fix spelling error in constant name: `CredentialSeperator` ->
`CredentialSeparator`
- Updated all usages across the codebase to use the correct spelling
## Changes
- `pkg/util/constant.go`: Renamed the constant
- `pkg/util/contextutil/context_util.go`: Updated usage
- `pkg/util/contextutil/context_util_test.go`: Updated usage
- `internal/proxy/authentication_interceptor.go`: Updated usage
- `internal/proxy/util.go`: Updated usage
- `internal/proxy/util_test.go`: Updated usage
- `internal/proxy/trace_log_interceptor_test.go`: Updated usage
- `internal/proxy/accesslog/info/util.go`: Updated usage
- `internal/distributed/proxy/service.go`: Updated usage
- `internal/distributed/proxy/httpserver/utils.go`: Updated usage
## Test Plan
- [x] All references updated consistently
- [x] No functional changes - only constant name spelling correction
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- Core invariant: the separator character for credentials remains ":"
everywhere — only the exported identifier was renamed from
CredentialSeperator → CredentialSeparator; the constant value and
split/join semantics are unchanged.
- Change (bug fix): corrected the misspelled exported constant in
pkg/util/constant.go and updated all references across the codebase
(parsing, token construction, header handling and tests) to use the new
identifier; this is an identifier rename that removes an inconsistent
symbol and prevents compile-time/reference errors.
- Logic simplified/redundant work removed: no runtime logic was removed;
the simplification is purely maintenance-focused — eliminating a
misspelled exported name that could cause developers to introduce
duplicate or incorrect constants.
- No data loss or behavior regression: runtime code paths are unchanged
— e.g., GetAuthInfoFromContext, ParseUsernamePassword,
AuthenticationInterceptor, proxy service token construction and
access-log extraction still use ":" to split/join credentials; updated
and added unit tests (parsing and metadata extraction) exercise these
paths and validate identical semantics.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: majiayu000 <1835304752@qq.com>
Signed-off-by: lif <1835304752@qq.com>
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
issue： #46033
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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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).
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
If collection TTL property is malformed (e.g., non-numeric value),
compaction tasks would fail silently and get stuck. This change:
- Add centralized GetCollectionTTL/GetCollectionTTLFromMap functions in
pkg/common to handle TTL parsing with proper error handling
- Validate TTL property in createCollectionTask and alterCollectionTask
PreExecute to reject invalid values early
- Refactor datacoord compaction policies to use the new common functions
- Remove duplicated getCollectionTTL from datacoord/util.go
issue: #46716
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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- Core invariant: collection.ttl.seconds must be a parseable int64 and
validated at collection creation/alter time so malformed TTLs never
reach compaction/execution codepaths.
- Bug fix (resolves#46716): malformed/non-numeric TTLs could silently
cause compaction tasks to fail/stall; fixed by adding centralized
parsing helpers pkg/common.GetCollectionTTL and GetCollectionTTLFromMap
and validating TTL in createCollectionTask.PreExecute and
alterCollectionTask.PreExecute (calls with default -1 and return
parameter-invalid errors on parse failure).
- Simplification / removed redundancy: eliminated duplicated
getCollectionTTL in internal/datacoord/util.go and replaced ad-hoc TTL
parsing across datacoord (compaction policies, import_util, compaction
triggers) and proxy util with the common helpers, centralizing error
handling and defaulting logic.
- No data loss or behavior regression: valid TTL parsing semantics
unchanged (helpers use identical int64 parsing and default fallback from
paramtable/CommonCfg); validation occurs in PreExecute so existing valid
collections proceed unchanged while malformed values are rejected
early—compaction codepaths now receive only validated TTL values (or
explicit defaults), preventing silent skips without altering valid
execution flows.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/44123
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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- Core invariant: legacy in-cluster CDC/replication plumbing
(ReplicateMsg types, ReplicateID-based guards and flags) is obsolete —
the system relies on standard msgstream positions, subPos/end-ts
semantics and timetick ordering as the single source of truth for
message ordering and skipping, so replication-specific
channels/types/guards can be removed safely.
- Removed/simplified logic (what and why): removed replication feature
flags and params (ReplicateMsgChannel, TTMsgEnabled,
CollectionReplicateEnable), ReplicateMsg type and its tests, ReplicateID
constants/helpers and MergeProperties hooks, ReplicateConfig and its
propagation (streamPipeline, StreamConfig, dispatcher, target),
replicate-aware dispatcher/pipeline branches, and replicate-mode
pre-checks/timestamp-allocation in proxy tasks — these implemented a
redundant alternate “replicate-mode” pathway that duplicated
position/end-ts and timetick logic.
- Why this does NOT cause data loss or regression (concrete code paths):
no persistence or core write paths were removed — proxy PreExecute flows
(internal/proxy/task_*.go) still perform the same schema/ID/size
validations and then follow the normal non-replicate execution path;
dispatcher and pipeline continue to use position/subPos and
pullback/end-ts in Seek/grouping (pkg/mq/msgdispatcher/dispatcher.go,
internal/util/pipeline/stream_pipeline.go), so skipping and ordering
behavior remains unchanged; timetick emission in rootcoord
(sendMinDdlTsAsTt) is now ungated (no silent suppression), preserving or
increasing timetick delivery rather than removing it.
- PR type and net effect: Enhancement/Refactor — removes deprecated
replication API surface (types, helpers, config, tests) and replication
branches, simplifies public APIs and constructor signatures, and reduces
surface area for future maintenance while keeping DML/DDL persistence,
ordering, and seek semantics intact.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
issue: #44320
Replace the DeduplicateFieldData function with CheckDuplicatePkExist
that returns an error when duplicate primary keys are detected in the
same batch, instead of silently deduplicating.
Changes:
- Replace DeduplicateFieldData with CheckDuplicatePkExist in util.go
- Update upsertTask.PreExecute to return error on duplicate PKs
- Simplify helper function from findLastOccurrenceIndices to
hasDuplicates
- Update unit tests to verify the new error behavior
- Add Python integration tests for duplicate PK error cases
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
https://github.com/milvus-io/milvus/issues/45544
- Add batch_factor configuration parameter (default: 5) to control
embedding provider batch sizes
- Add disable_func_runtime_check property to bypass function validation
during collection creation
- Add database interceptor support for AddCollectionFunction,
AlterCollectionFunction, and DropCollectionFunction requests
Signed-off-by: junjie.jiang <junjie.jiang@zilliz.com>
issue: #44320
This change adds deduplication logic to handle duplicate primary keys
within a single upsert batch, keeping the last occurrence of each
primary key.
Key changes:
- Add DeduplicateFieldData function to remove duplicate PKs from field
data, supporting both Int64 and VarChar primary keys
- Refactor fillFieldPropertiesBySchema into two separate functions:
validateFieldDataColumns for validation and fillFieldPropertiesOnly for
property filling, improving code clarity and reusability
- Integrate deduplication logic in upsertTask.PreExecute to
automatically deduplicate data before processing
- Add comprehensive unit tests for deduplication with various PK types
(Int64, VarChar) and field types (scalar, vector)
- Add Python integration tests to verify end-to-end behavior
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
relate: https://github.com/milvus-io/milvus/issues/43687
We used to run the temporary analyzer and validate analyzer on the
proxy, but the proxy should not be a computation-heavy node. This PR
move all analyzer calculations to the streaming node.
---------
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
Related to #44761
This commit refactors the privilege management system in the proxy
component by:
1. **Separation of Concerns**: Extracts privilege-related functionality
from MetaCache into a dedicated `internal/proxy/privilege` package,
improving code organization and maintainability.
2. **New Package Structure**: Creates `internal/proxy/privilege/` with:
- `cache.go`: Core privilege cache implementation (PrivilegeCache)
- `result_cache.go`: Privilege enforcement result caching
- `model.go`: Casbin model and policy enforcement functions
- `meta_cache_adapter.go`: Casbin adapter for MetaCache integration
- Corresponding test files and mock implementations
3. **MetaCache Simplification**: Removes privilege and credential
management methods from MetaCache interface and implementation:
- Removed: GetCredentialInfo, RemoveCredential, UpdateCredential
- Removed: GetPrivilegeInfo, GetUserRole, RefreshPolicyInfo,
InitPolicyInfo
- Deleted: meta_cache_adapter.go, privilege_cache.go and their tests
4. **Updated References**: Updates all callsites to use the new
privilegeCache global:
- Authentication interceptor now uses privilegeCache for password
verification
- Credential cache operations (InvalidateCredentialCache,
UpdateCredentialCache, UpdateCredential) now use privilegeCache
- Policy refresh operations (RefreshPolicyInfoCache) now use
privilegeCache
- Privilege interceptor uses new privilege.GetEnforcer() and privilege
result cache
5. **Improved API**: Renames cache functions for clarity:
- GetPrivilegeCache → GetResultCache
- SetPrivilegeCache → SetResultCache
- CleanPrivilegeCache → CleanResultCache
This refactoring makes the codebase more modular, separates privilege
management concerns from general metadata caching, and provides a
clearer API for privilege enforcement operations.
---------
Signed-off-by: Congqi Xia <congqi.xia@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: https://github.com/milvus-io/milvus/issues/27467
>My plan is as follows.
>- [x] M1 Create collection with timestamptz field
>- [x] M2 Insert timestamptz field data
>- [x] M3 Retrieve timestamptz field data
>- [x] M4 Implement handoff
>- [x] M5 Implement compare operator
>- [x] M6 Implement extract operator
>- [x] M8 Support database/collection level default timezone
>- [x] M7 Support STL-SORT index for datatype timestamptz
---
The third PR of issue: https://github.com/milvus-io/milvus/issues/27467,
which completes M5, M6, M7, M8 described above.
## M8 Default Timezone
We will be able to use alter_collection() and alter_database() in a
future Python SDK release to modify the default timezone at the
collection or database level.
For insert requests, the timezone will be resolved using the following
order of precedence: String Literal-> Collection Default -> Database
Default.
For retrieval requests, the timezone will be resolved in this order:
Query Parameters -> Collection Default -> Database Default.
In both cases, the final fallback timezone is UTC.
## M5: Comparison Operators
We can now use the following expression format to filter on the
timestamptz field:
- `timestamptz_field [+/- INTERVAL 'interval_string'] {comparison_op}
ISO 'iso_string' `
- The interval_string follows the ISO 8601 duration format, for example:
P1Y2M3DT1H2M3S.
- The iso_string follows the ISO 8601 timestamp format, for example:
2025-01-03T00:00:00+08:00.
- Example expressions: "tsz + INTERVAL 'P0D' != ISO
'2025-01-03T00:00:00+08:00'" or "tsz != ISO
'2025-01-03T00:00:00+08:00'".
## M6: Extract
We will be able to extract sepecific time filed by kwargs in a future
Python SDK release.
The key is `time_fields`, and value should be one or more of "year,
month, day, hour, minute, second, microsecond", seperated by comma or
space. Then the result of each record would be an array of int64.
## M7: Indexing Support
Expressions without interval arithmetic can be accelerated using an
STL-SORT index. However, expressions that include interval arithmetic
cannot be indexed. This is because the result of an interval calculation
depends on the specific timestamp value. For example, adding one month
to a date in February results in a different number of added days than
adding one month to a date in March.
---
After this PR, the input / output type of timestamptz would be iso
string. Timestampz would be stored as timestamptz data, which is int64_t
finally.
> for more information, see https://en.wikipedia.org/wiki/ISO_8601
---------
Signed-off-by: xtx <xtianx@smail.nju.edu.cn>
issue: #44212
Implement search/query storage usage statistics in go side(result
reduce), only record storage usage in vector search C++ path. Need to be
implemented in query c++ path in next prs.
---------
Signed-off-by: chasingegg <chao.gao@zilliz.com>
Signed-off-by: marcelo.chen <marcelo.chen@zilliz.com>
Co-authored-by: marcelo.chen <marcelo.chen@zilliz.com>
related: #42417
- Add NameValidationAllowedChars and RoleNameValidationAllowedChars
configuration parameters to specify additional characters allowed
respectively in (generic) names and a role names
- All validations in validateName method is moved to a the new method
validateNameWithCustomChars which is called by both validateName
and ValidateRoleName while specifying characters allowed
Signed-off-by: Jean-Francois Weber-Marx <jfwm@hotmail.com>
Signed-off-by: Jean-Francois Weber-Marx <jf.webermarx@criteo.com>
issue: #43980
Fixes a panic that occurred when a partial update was converted to an
insert due to a non-existent primary key. The panic was caused by
missing nullable fields that were not provided in the original partial
update request.
The upsert pre-execution logic is refactored to handle this correctly:
- Explicitly splits upsert data into 'insert' and 'update' batches.
- Automatically generates data for missing nullable or default-value
fields during inserts, preventing the panic.
- Enhances `typeutil.UpdateFieldData` to support different source and
destination indexes for flexible data merging.
- Adds comprehensive unit tests for mixed upsert, pure insert, and pure
update scenarios.
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Ref https://github.com/milvus-io/milvus/issues/42148
This PR supports create index for vector array (now, only for
`DataType.FLOAT_VECTOR`) and search on it.
The index type supported in this PR is `EMB_LIST_HNSW` and the metric
type is `MAX_SIM` only.
The way to use it:
```python
milvus_client = MilvusClient("xxx:19530")
schema = milvus_client.create_schema(enable_dynamic_field=True, auto_id=True)
...
struct_schema = milvus_client.create_struct_array_field_schema("struct_array_field")
...
struct_schema.add_field("struct_float_vec", DataType.ARRAY_OF_VECTOR, element_type=DataType.FLOAT_VECTOR, dim=128, max_capacity=1000)
...
schema.add_struct_array_field(struct_schema)
index_params = milvus_client.prepare_index_params()
index_params.add_index(field_name="struct_float_vec", index_type="EMB_LIST_HNSW", metric_type="MAX_SIM", index_params={"nlist": 128})
...
milvus_client.create_index(COLLECTION_NAME, schema=schema, index_params=index_params)
```
Note: This PR uses `Lims` to convey offsets of the vector array to
knowhere where vectors of multiple vector arrays are concatenated and we
need offsets to specify which vectors belong to which vector array.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.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>
Ref https://github.com/milvus-io/milvus/issues/42148https://github.com/milvus-io/milvus/pull/42406 impls the segcore part of
storage for handling with VectorArray.
This PR:
1. impls the go part of storage for VectorArray
2. impls the collection creation with StructArrayField and VectorArray
3. insert and retrieve data from the collection.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <tangchenjie1210@gmail.com>
Signed-off-by: SpadeA-Tang <u6748471@anu.edu.au>
related: #42417
- update the isValidUsername function to accept dots and hyphens in
addition to letters, digits, and underscores
- this change improves compatibility with common username formats and
addresses feedback in issue #42417
Signed-off-by: Jean-Francois Weber-Marx <jfwm@hotmail.com>
Signed-off-by: Jean-Francois Weber-Marx <jf.webermarx@criteo.com>
Related to #42489
Since load list works as hint after cachelayer implemented, the related
check logic could be removed to keep code logic clean.
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
Related to #39718
The absent nullable field shall be filled at server-side in nullable
design. While the implementation here was buggy causing the feature was
not able to serve.
This PR make proxy fill the field data in correct format so that field
data with absent column(s) will be accepted.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
