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
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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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: #46740
- Add duplicate ID check before query execution (fail fast)
- Auto infer anns_field when only one vector field exists in schema
Signed-off-by: Li Liu <li.liu@zilliz.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>
issue: #45640
- After async logging, the C log and go log has no order promise,
meanwhile the C log format is not consistent with Go Log; so we close
the output of glog, just forward the log result operation into Go side
which will be handled by the async zap logger.
- Use CGO to filter all cgo logging and promise the order between c log
and go log.
- Also fix the metric name, add new metric to count the logging.
- TODO: after woodpecker use the logger of milvus, we can add bigger
buffer for logging.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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- Core invariant: all C (glog) and Go logs must be routed through the
same zap async pipeline so ordering and formatting are preserved; this
PR ensures every glog emission is captured and forwarded to zap before
any async buffering diverges the outputs.
- Logic removed/simplified: direct glog outputs and hard
stdout/stderr/log_dir settings are disabled (configs/glog.conf and flags
in internal/core/src/config/ConfigKnowhere.cpp) because they are
redundant once a single zap sink handles all logs; logging metrics were
simplified from per-length/volatile gauges to totalized counters
(pkg/metrics/logging_metrics.go & pkg/log/*), removing duplicate
length-tracking and making accounting consistent.
- No data loss or behavior regression (concrete code paths): Google
logging now adds a GoZapSink (internal/core/src/common/logging_c.h,
logging_c.cpp) that calls the exported CGO bridge goZapLogExt
(internal/util/cgo/logging/logging.go). Go side uses
C.GoStringN/C.GoString to capture full message and file, maps glog
severities to zapcore levels, preserves caller info, and writes via the
existing zap async core (same write path used by Go logs). The C++
send() trims glog's trailing newline and forwards exact buffers/lengths,
so message content, file, line, and severity are preserved and
serialized through the same async writer—no log entries are dropped or
reordered relative to Go logs.
- Capability added (where it takes effect): a CGO bridge that forwards
glog into zap—new Go-exported function goZapLogExt
(internal/util/cgo/logging/logging.go), a GoZapSink in C++ that forwards
glog sends (internal/core/src/common/logging_c.h/.cpp), and blank
imports of the cgo initializer across multiple packages (various
internal/* files) to ensure the bridge is registered early so all C logs
are captured.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: chyezh <chyezh@outlook.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: #46500
- simplify the run_go_codecov.sh to make sure the set -e to protect any
sub command failure.
- remove all embed etcd in test to make full test can be run at local.
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## PR Summary: Simplify Go Unit Tests by Removing Embedded etcd and
Async Startup Scaffolding
**Core Invariant:**
This PR assumes that unit tests can be simplified by running without
embedded etcd servers (delegating to environment-based or external etcd
instances via `kvfactory.GetEtcdAndPath()` or `ETCD_ENDPOINTS`) and by
removing goroutine-based async startup scaffolding in favor of
synchronous component initialization. Tests remain functionally
equivalent while becoming simpler to run and debug locally.
**What is Removed or Simplified:**
1. **Embedded etcd test infrastructure deleted**: Removes
`EmbedEtcdUtil` type and its public methods (SetupEtcd,
TearDownEmbedEtcd) from `pkg/util/testutils/embed_etcd.go`, removes the
`StartTestEmbedEtcdServer()` helper from `pkg/util/etcd/etcd_util.go`,
and removes etcd embedding from test suites (e.g., `TaskSuite`,
`EtcdSourceSuite`, `mixcoord/client_test.go`). Tests now either skip
etcd-dependent tests (via `MILVUS_UT_WITHOUT_KAFKA=1` environment flag
in `kafka_test.go`) or source etcd from external configuration (via
`kvfactory.GetEtcdAndPath()` in `task_test.go`, or `ETCD_ENDPOINTS`
environment variable in `etcd_source_test.go`). This eliminates the
overhead of spinning up temporary etcd servers for unit tests.
2. **Async startup scaffolding replaced with synchronous
initialization**: In `internal/proxy/proxy_test.go` and
`proxy_rpc_test.go`, the `startGrpc()` method signature removes the
`sync.WaitGroup` parameter; components are now created, prepared, and
run synchronously in-place rather than in goroutines (e.g., `go
testServer.startGrpc(ctx, &p)` becomes `testServer.startGrpc(ctx, &p)`
running synchronously). Readiness checks (e.g., `waitForGrpcReady()`)
remain in place to ensure startup safety without concurrency constructs.
This simplifies control flow and reduces debugging complexity.
3. **Shell script orchestration unified with proper error handling**: In
`scripts/run_go_codecov.sh` and `scripts/run_intergration_test.sh`,
per-package inline test invocations are consolidated into a single
`test_cmd()` function with unified `TEST_CMD_WITH_ARGS` array containing
race, coverage, verbose, and other flags. The problematic `set -ex` is
replaced with `set -e` alone (removing debug output noise while
preserving strict error semantics), ensuring the scripts fail fast on
any command failure.
**Why No Regression:**
- Test assertions and code paths remain unchanged; only deployment
source of etcd (embedded → external) and startup orchestration (async →
sync) change.
- Readiness verification (e.g., `waitForGrpcReady()`) is retained,
ensuring components are initialized before test execution.
- Test flags (race detection, coverage, verbosity) are uniformly applied
across all packages via unified `TEST_CMD_WITH_ARGS`, preserving test
coverage and quality.
- `set -e` alone is sufficient for strict failure detection without the
`-x` flag's verbose output.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: chyezh <chyezh@outlook.com>
https://github.com/milvus-io/milvus/issues/42589
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Semantic Highlighting Feature
**Core Invariant**: Semantic highlighting operates on a per-field basis
with independent text processing through an external Zilliz highlight
provider. The implementation maintains field ID to field name mapping
and correlates highlight results back to original field outputs.
**What is Added**: This PR introduces semantic highlighting capability
for search results alongside the existing lexical highlighting. The
feature consists of:
- New `SemanticHighlight` orchestrator that validates queries/input
fields against collection schema, instantiates a Zilliz-based provider,
and batches text processing across multiple queries
- New `SemanticHighlighter` proxy wrapper implementing the `Highlighter`
interface for search pipeline integration
- New `semanticHighlightOperator` that processes search results by
delegating per-field text processing to the provider and attaching
correlated `HighlightResult` data to search outputs
- New gRPC service definition (`HighlightService`) and
`ZillizClient.Highlight()` method for external provider communication
**No Data Loss or Regression**: The change is purely additive without
modifying existing logic:
- Lexical highlighting path remains unchanged (separate switch case in
`createHighlightTask`)
- New `HighlightResults` field is only populated when semantic
highlighting is explicitly requested via `HighlightType_Semantic` enum
value
- Gracefully handles missing fields by returning explicit errors rather
than silent failures
- Pipeline operator integration follows existing patterns and only
processes when semantic highlighter is instantiated
**Why This Design**: Semantic highlighting is routed through the same
pipeline operator pattern as lexical highlighting, ensuring consistent
integration into search workflows. The per-field model allows flexible
highlighting across different text columns and batch processing ensures
efficient handling of multiple queries with configurable provider
constraints.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: junjie.jiang <junjie.jiang@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: https://github.com/milvus-io/milvus/issues/46651
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Enhancement: Add Context-Aware Logging for Proxy and RootCoord Meta
Table Operations
**Core Invariant**: All changes maintain existing cache behavior and
state transition logic by purely enhancing observability through
context-aware logging without modifying control flow, return values, or
data structures.
**Logic Simplified Without Regression**:
- Removed internal helper method `getFullCollectionInfo` from MetaCache
by inlining its logic directly into GetCollectionInfo, eliminating an
unnecessary abstraction layer while preserving the exact same
cache-hit/miss and fetch-or-update paths
- This consolidation has no impact on behavior because the helper was
only called from one location and the inlined logic executes identically
**Enhanced Logging for Observability (No Behavior Changes)**:
- Added context-aware logging (log.Ctx(ctx)) to cache miss scenarios and
timestamp comparisons in proxy MetaCache, enabling request tracing
without altering cache lookup logic
- Expanded RootCoord MetaTable's internal helper method signatures to
propagate context for contextual logging across collection lifecycle
events (begin truncate, update state, remove names/aliases, delete from
collections map), while keeping all call sites and state transitions
unchanged
- Enhanced DescribeCollection logging in proxy to capture request scope
(role, database, collection IDs, timestamp) and response schema at
operation boundaries
**Type**: Enhancement focused on improved observability. All
modifications are strictly additive logging; no data structures, caching
strategies, or core logic paths were altered.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
relate: https://github.com/milvus-io/milvus/issues/46498
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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- Core invariant: text fields configured with multi_analyzer_params must
include a "by_field" string that names another field containing per-row
analyzer choices; schemaInfo.GetMultiAnalyzerNameFieldID caches and
returns the dependent field ID (or 0 if none) and relies on that mapping
to make per-row analyzer names available to the highlighter.
- What changed / simplified: the highlighter is now schema-aware —
addTaskWithSearchText accepts *schemaInfo and uses
GetMultiAnalyzerNameFieldID to resolve the analyzer-name field;
resolution and caching moved into schemaInfo.multiAnalyzerFieldMap
(meta_cache.go), eliminating ad-hoc/typeutil-only lookups and duplicated
logic; GetMultiAnalyzerParams now gates on EnableAnalyzer(),
centralizing analyzer enablement checks.
- Why this fixes the bug (root cause): fixes#46498 — previously the
highlighter failed when the analyzer-by-field was not in output_fields.
The change (1) populates task.AnalyzerNames (defaulting missing names to
"default") when multi-analyzer is configured and (2) appends the
analyzer-name field ID to LexicalHighlighter.extraFields so FieldIDs
includes it; the operator then requests the analyzer-name column at
search time, ensuring per-row analyzer selection is available for
highlighting.
- No data-loss or regression: when no multi-analyzer is configured
GetMultiAnalyzerNameFieldID returns 0 and behavior is unchanged; the
patch only adds the analyzer-name field to requested output IDs (no
mutation of stored data). Error handling on malformed params is
preserved (errors are returned instead of silently changing data), and
single-analyzer behavior remains untouched.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/45919
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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- Core invariant: FlushAll verification must accept both per-channel
FlushAllTss (new schema) and the legacy single FlushAllTs;
GetFlushAllState chooses the verification path based on which field is
present and treats a channel as flushed only if its channel checkpoint
timestamp >= the applicable threshold (per-channel timestamp or legacy
FlushAllTs).
- Logic removed/simplified: The previous mixed/ambiguous checks were
split into two focused
routines—verifyFlushAllStateByChannelFlushAllTs(logger, channel,
flushAllTss) and verifyFlushAllStateByLegacyFlushAllTs(logger, channel,
flushAllTs)—and GetFlushAllState now selects one path. This centralizes
compatibility logic, eliminates interleaved/duplicated checks, and
retains the outer-loop short-circuiting on the first unflushed channel.
- Why this does NOT cause data loss or regressions: Changes only affect
read-only verification paths (GetFlushAllState/GetFlushState) that
compare in-memory channel checkpoints (meta.GetChannelCheckpoint) to
provided thresholds; no writes to checkpoints or persisted state occur
and FlushAll enqueue/wait behavior is unchanged. Unit tests were added
to cover legacy FlushAllTs behavior and the new FlushAllMsgs→FlushAllTs
extraction, exercising both code paths.
- Enhancement scope and location: Adds backward-compatible support and
concrete FlushAllTs extraction from streaming FlushAllMsgs in Proxy
(internal/proxy/task_flush_all_streaming.go) and compatibility verifiers
in DataCoord (internal/datacoord/services.go), plus corresponding tests
(internal/datacoord/services_test.go, internal/proxy/*_test.go).
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
Related to #46594
Remove the temporary config override that forced EnableStorageV2 to
false in TestProxy. This override caused test failures with the new load
logic, as segments could not be loaded with v1 format.
This PR is a quick fix to make ut back to normal
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
relate: https://github.com/milvus-io/milvus/issues/43687
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **Chores**
* File resource operations (add, remove, list) are now unavailable and
return a not-implemented response.
* **Tests**
* Tests updated to expect error responses for those file resource
operations and removed some previous coordination-path assertions.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
Introduce a ScannerStartupDelay configuration to enable WAL write-only
recovery, allowing fence messages to be persisted during
primary–secondary switchover when the StreamingNode is trapped in crash
loops.
issue: https://github.com/milvus-io/milvus/issues/46368
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit
* **New Features**
* Added a configurable WAL scanner pause/resume and a consumer request
flag to optionally ignore pause signals.
* **Metrics**
* Added a scanner pause gauge and pause-duration tracking for WAL
scanning.
* **Tests**
* Added coverage for pause-consumption behavior and cleanup in stream
client tests.
* **Chores**
* Consolidated flush-all logging into a single field and added a helper
for bulk message conversion.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
related: #45993
This commit extends nullable vector support to the proxy layer,
querynode,
and adds comprehensive validation, search reduce, and field data
handling
for nullable vectors with sparse storage.
Proxy layer changes:
- Update validate_util.go checkAligned() with getExpectedVectorRows()
helper
to validate nullable vector field alignment using valid data count
- Update checkFloatVectorFieldData/checkSparseFloatVectorFieldData for
nullable vector validation with proper row count expectations
- Add FieldDataIdxComputer in typeutil/schema.go for logical-to-physical
index translation during search reduce operations
- Update search_reduce_util.go reduceSearchResultData to use
idxComputers
for correct field data indexing with nullable vectors
- Update task.go, task_query.go, task_upsert.go for nullable vector
handling
- Update msg_pack.go with nullable vector field data processing
QueryNode layer changes:
- Update segments/result.go for nullable vector result handling
- Update segments/search_reduce.go with nullable vector offset
translation
Storage and index changes:
- Update data_codec.go and utils.go for nullable vector serialization
- Update indexcgowrapper/dataset.go and index.go for nullable vector
indexing
Utility changes:
- Add FieldDataIdxComputer struct with Compute() method for efficient
logical-to-physical index mapping across multiple field data
- Update EstimateEntitySize() and AppendFieldData() with fieldIdxs
parameter
- Update funcutil.go with nullable vector support functions
<!-- This is an auto-generated comment: release notes by coderabbit.ai
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## Summary by CodeRabbit
* **New Features**
* Full support for nullable vector fields (float, binary, float16,
bfloat16, int8, sparse) across ingest, storage, indexing, search and
retrieval; logical↔physical offset mapping preserves row semantics.
* Client: compaction control and compaction-state APIs.
* **Bug Fixes**
* Improved validation for adding vector fields (nullable + dimension
checks) and corrected search/query behavior for nullable vectors.
* **Chores**
* Persisted validity maps with indexes and on-disk formats.
* **Tests**
* Extensive new and updated end-to-end nullable-vector tests.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: marcelo-cjl <marcelo.chen@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/45525
see added README.md for added optimizations
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
* **New Features**
* Added query expression optimization feature with a new `optimizeExpr`
configuration flag to enable automatic simplification of filter
predicates, including range predicate optimization, merging of IN/NOT IN
conditions, and flattening of nested logical operators.
* **Bug Fixes**
* Adjusted delete operation behavior to correctly handle expression
evaluation.
<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Buqian Zheng <zhengbuqian@gmail.com>
issue: https://github.com/milvus-io/milvus/issues/45890
ComputePhraseMatchSlop accepts three pararms:
1. A string: query text
2. Some trings: data texts
3. Analyzer params,
Slop will be calculated for the query text with each data text in the
context of phrase match where they are tokenized with tokenizer with
analyzer params.
So two array will be returned:
1. is_match: is phrase match can sucess
2. slop: the related slop if phrase match can sucess, or -1 is cannot.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
issue: #43897
also for issue: #46166
add ack_sync_up flag into broadcast message header, which indicates that
whether the broadcast operation is need to be synced up between the
streaming node and the coordinator.
If the ack_sync_up is false, the broadcast operation will be acked once
the recovery storage see the message at current vchannel, the fast ack
operation can be applied to speed up the broadcast operation.
If the ack_sync_up is true, the broadcast operation will be acked after
the checkpoint of current vchannel reach current message.
The fast ack operation can not be applied to speed up the broadcast
operation, because the ack operation need to be synced up with streaming
node.
e.g. if truncate collection operation want to call ack once callback
after the all segment are flushed at current vchannel, it should set the
ack_sync_up to be true.
TODO: current implementation doesn't promise the ack sync up semantic,
it only promise FastAck operation will not be applied, wait for 3.0 to
implement the ack sync up semantic. only for truncate api now.
---------
Signed-off-by: chyezh <chyezh@outlook.com>
issue: https://github.com/milvus-io/milvus/issues/42148
For a vector field inside a STRUCT, since a STRUCT can only appear as
the element type of an ARRAY field, the vector field in STRUCT is
effectively an array of vectors, i.e. an embedding list.
Milvus already supports searching embedding lists with metrics whose
names start with the prefix MAX_SIM_.
This PR allows Milvus to search embeddings inside an embedding list
using the same metrics as normal embedding fields. Each embedding in the
list is treated as an independent vector and participates in ANN search.
Further, since STRUCT may contain scalar fields that are highly related
to the embedding field, this PR introduces an element-level filter
expression to refine search results.
The grammar of the element-level filter is:
element_filter(structFieldName, $[subFieldName] == 3)
where $[subFieldName] refers to the value of subFieldName in each
element of the STRUCT array structFieldName.
It can be combined with existing filter expressions, for example:
"varcharField == 'aaa' && element_filter(struct_field, $[struct_int] ==
3)"
A full example:
```
struct_schema = milvus_client.create_struct_field_schema()
struct_schema.add_field("struct_str", DataType.VARCHAR, max_length=65535)
struct_schema.add_field("struct_int", DataType.INT32)
struct_schema.add_field("struct_float_vec", DataType.FLOAT_VECTOR, dim=EMBEDDING_DIM)
schema.add_field(
"struct_field",
datatype=DataType.ARRAY,
element_type=DataType.STRUCT,
struct_schema=struct_schema,
max_capacity=1000,
)
...
filter = "varcharField == 'aaa' && element_filter(struct_field, $[struct_int] == 3 && $[struct_str] == 'abc')"
res = milvus_client.search(
COLLECTION_NAME,
data=query_embeddings,
limit=10,
anns_field="struct_field[struct_float_vec]",
filter=filter,
output_fields=["struct_field[struct_int]", "varcharField"],
)
```
TODO:
1. When an `element_filter` expression is used, a regular filter
expression must also be present. Remove this restriction.
2. Implement `element_filter` expressions in the `query`.
---------
Signed-off-by: SpadeA <tangchenjie1210@gmail.com>
This PR:
1. Define and implement the new FlushAllMessage.
2. Refactor FlushAll to flush the entire cluster.
issue: https://github.com/milvus-io/milvus/issues/45919
---------
Signed-off-by: bigsheeper <yihao.dai@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>
issue: #46176
- Add checkAligned validation before processing partial update field
data to prevent index out of range panic when field data arrays have
mismatched lengths
- Fix GetNumRowOfFieldDataWithSchema to handle Timestamptz string format
and Geometry WKT format properly
- Add unit tests for empty data array scenarios in partial update
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
Add collection-level granularity to the garbage collector pause/resume
mechanism. Previously, GC pause affected all collections globally. Now
operators can pause GC for specific collections while allowing other
collections to continue normal GC operations.
Changes:
- Add `pausedCollection` concurrent map to track per-collection pause
state
- Extend `Pause()` and `Resume()` methods with `collectionID` parameter
- Add `collectionGCPaused()` helper to check collection pause status
- Skip dropped segment recycling when collection GC is paused
- Update management API to accept optional `collection_id` query
parameter
- Add `GetInt64Value()` utility function for parsing int64 from KV pairs
- Maintain backward compatibility: collectionID <= 0 triggers global
pause
This provides DevOps with finer control over Milvus data lifecycle.
issue: #45941
---------
Signed-off-by: Congqi Xia <congqi.xia@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>
Previously, search with highlight only supported using BM25 search text
as the highlight target.
This PR adds support for highlighting with user-defined queries.
relate: https://github.com/milvus-io/milvus/issues/42589
---------
Signed-off-by: aoiasd <zhicheng.yue@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/45691
Add persistent task management for external collections with automatic
detection of external_source and external_spec changes. When source
changes, the system aborts running tasks and creates new ones, ensuring
only one active task per collection. Tasks validate their source on
completion to prevent superseded tasks from committing results.
---------
Signed-off-by: sunby <sunbingyi1992@gmail.com>
