issue: #44358
Implement complete snapshot management system including creation,
deletion, listing, description, and restoration capabilities across all
system components.
Key features:
- Create snapshots for entire collections
- Drop snapshots by name with proper cleanup
- List snapshots with collection filtering
- Describe snapshot details and metadata
Components added/modified:
- Client SDK with full snapshot API support and options
- DataCoord snapshot service with metadata management
- Proxy layer with task-based snapshot operations
- Protocol buffer definitions for snapshot RPCs
- Comprehensive unit tests with mockey framework
- Integration tests for end-to-end validation
Technical implementation:
- Snapshot metadata storage in etcd with proper indexing
- File-based snapshot data persistence in object storage
- Garbage collection integration for snapshot cleanup
- Error handling and validation across all operations
- Thread-safe operations with proper locking mechanisms
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- Core invariant/assumption: snapshots are immutable point‑in‑time
captures identified by (collection, snapshot name/ID); etcd snapshot
metadata is authoritative for lifecycle (PENDING → COMMITTED → DELETING)
and per‑segment manifests live in object storage (Avro / StorageV2). GC
and restore logic must see snapshotRefIndex loaded
(snapshotMeta.IsRefIndexLoaded) before reclaiming or relying on
segment/index files.
- New capability added: full end‑to‑end snapshot subsystem — client SDK
APIs (Create/Drop/List/Describe/Restore + restore job queries),
DataCoord SnapshotWriter/Reader (Avro + StorageV2 manifests),
snapshotMeta in meta, SnapshotManager orchestration
(create/drop/describe/list/restore), copy‑segment restore
tasks/inspector/checker, proxy & RPC surface, GC integration, and
docs/tests — enabling point‑in‑time collection snapshots persisted to
object storage and restorations orchestrated across components.
- Logic removed/simplified and why: duplicated recursive
compaction/delta‑log traversal and ad‑hoc lookup code were consolidated
behind two focused APIs/owners (Handler.GetDeltaLogFromCompactTo for
delta traversal and SnapshotManager/SnapshotReader for snapshot I/O).
MixCoord/coordinator broker paths were converted to thin RPC proxies.
This eliminates multiple implementations of the same traversal/lookup,
reducing divergence and simplifying responsibility boundaries.
- Why this does NOT introduce data loss or regressions: snapshot
create/drop use explicit two‑phase semantics (PENDING → COMMIT/DELETING)
with SnapshotWriter writing manifests and metadata before commit; GC
uses snapshotRefIndex guards and
IsRefIndexLoaded/GetSnapshotBySegment/GetSnapshotByIndex checks to avoid
removing referenced files; restore flow pre‑allocates job IDs, validates
resources (partitions/indexes), performs rollback on failure
(rollbackRestoreSnapshot), and converts/updates segment/index metadata
only after successful copy tasks. Extensive unit and integration tests
exercise pending/deleting/GC/restore/error paths to ensure idempotence
and protection against premature deletion.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
issue: https://github.com/milvus-io/milvus/issues/46678
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- Core invariant: Text index log keys are canonicalized at KV
(serialization) boundaries — etcd stores compressed filename-only
entries, while in-memory and runtime consumers must receive full
object-storage keys so Datanode/QueryNode can load text indexes
directly.
- Logic removed/simplified: ad-hoc reconstruction of full text-log paths
scattered across components (garbage_collector.getTextLogs,
querynodev2.LoadTextIndex, compactor/index task code) was removed;
consumers now use TextIndexStats.Files as-provided (full keys). Path
compression/decompression was centralized into KV marshal/unmarshal
utilities (metautil.ExtractTextLogFilenames in marshalSegmentInfo and
metautil.BuildTextLogPaths in kv_catalog.listSegments), eliminating
redundant, inconsistent prefix-rebuilding logic that broke during
rolling upgrades.
- Why this does NOT cause data loss or regressions: before persist,
marshalSegmentInfo compresses TextStatsLogs.Files to filenames
(metautil.ExtractTextLogFilenames) so stored KV remains compact; on
load, kv_catalog.listSegments calls metautil.BuildTextLogPaths to
restore full paths and includes compatibility logic that leaves
already-full keys unchanged. Thus every persisted filename is
recoverable to a valid full key and consumers receive correct full paths
(see marshalSegmentInfo → KV write path and kv_catalog.listSegments →
reload path), preventing dropped or malformed keys.
- Bug fix (refs #46678): resolves text-log loading failures during
cluster upgrades by centralizing path handling at KV encode/decode and
removing per-component path reconstruction — the immediate fix is
changing consumers to read TextIndexStats.Files directly and relying on
marshal/unmarshal to perform compression/expansion, preventing
mixed-format failures during rolling upgrades.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: sijie-ni-0214 <sijie.ni@zilliz.com>
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).
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: Cai Zhang <cai.zhang@zilliz.com>
issue: #45841
- CPP log make the multi log line in one debug, remove the "\n\t".
- remove some log that make no sense.
- slow down some log like ChannelDistManager.
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- Core invariant: logging is purely observational — this PR only
reduces, consolidates, or reformats diagnostic output (removing
per-item/noise logs, consolidating batched logs, and converting
multi-line log strings) while preserving all control flow, return
values, and state mutations across affected code paths.
- Removed / simplified logic: deleted low-value per-operation debug/info
logs (e.g., ListIndexes, GetRecoveryInfo, GcConfirm,
push-to-reorder-buffer, several streaming/wal/debug traces), replaced
per-item inline logs with single batched deferred logs in
querynodev2/delegator (logExcludeInfo) and CleanInvalid, changed C++
PlanNode ToString() multi-line output to compact single-line bracketed
format (removed "\n\t"), and added thresholded interceptor logging
(InterceptorMetrics.ShouldBeLogged) and message-type-driven log levels
to avoid verbose entries.
- Why this does NOT cause data loss or behavioral regression: no
function signatures, branching, state updates, persistence calls, or
return values were changed — examples: ListIndexes still returns the
same Status/IndexInfos; GcConfirm still constructs and returns
resp.GetGcFinished(); Insert and CleanInvalid still perform the same
insert/removal operations (only their per-item logging was aggregated);
PlanNode ToString changes only affect emitted debug strings. All error
handling and control flow paths remain intact.
- Enhancement intent: reduce log volume and improve signal-to-noise for
debugging by removing redundant, noisy logs and emitting concise,
rate-/threshold-limited summaries while preserving necessary diagnostics
and original program behavior.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
---------
Signed-off-by: chyezh <chyezh@outlook.com>
issue: https://github.com/milvus-io/milvus/issues/46410
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- Core invariant: etcd metadata and in-memory Segment/TextIndex records
must store only compact filenames for text-index files; full object keys
are deterministically reconstructed at use-sites from a stable root +
common.TextIndexPath + IDs via metautil.BuildTextLogPaths.
- Bug & fix (issue #46410): the etcd RPC size overflow was caused by
persisting full upload keys in segment/TextIndex metadata. Fix: at
upload/creation sites (internal/datanode/compactor/sort_compaction.go
and internal/datanode/index/task_stats.go) store only filenames using
metautil.ExtractTextLogFilenames; at consumption/use sites
(internal/datacoord/garbage_collector.go,
internal/querynodev2/segments/segment.go, and other GC/loader code)
reconstruct full paths with metautil.BuildTextLogPaths before accessing
object storage.
- Simplified/removed logic: removed the redundant practice of carrying
full object keys through metadata and in-memory structures; callers now
persist compact filenames and perform on-demand path reconstruction.
This eliminates large payloads in etcd and reduces memory pressure while
preserving the same runtime control flow and error handling.
- No data loss / no regression: filename extraction is a deterministic
suffix operation (metautil.ExtractTextLogFilenames) and reloadFromKV
performs backward compatibility (internal/datacoord/meta.go converts
existing full-path entries to filenames before caching). All read paths
reconstruct full paths at runtime (garbage_collector.getTextLogs,
LocalSegment.LoadTextIndex, GC/loader), so no files are modified/deleted
and access semantics remain identical.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
Signed-off-by: sijie-ni-0214 <sijie.ni@zilliz.com>
relate:https://github.com/milvus-io/milvus/issues/43687
Support use file resource with sync mode.
Auto download or remove file resource to local when user add or remove
file resource.
Sync file resource to node when find new node session.
---------
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>
Related #44956
This commit integrates the Storage V2 FFI (Foreign Function Interface)
interface throughout the Milvus codebase, enabling unified storage
access through the Loon FFI layer. This is a significant step towards
standardizing storage operations across different storage versions.
1. Configuration Support
- **configs/milvus.yaml**: Added `useLoonFFI` configuration flag under
`common.storage.file.splitByAvgSize` section
- Allows runtime toggle between traditional binlog readers and new
FFI-based manifest readers
- Default: `false` (maintains backward compatibility)
2. Core FFI Infrastructure
Enhanced Utilities (internal/core/src/storage/loon_ffi/util.cpp/h)
- **ToCStorageConfig()**: Converts Go's `StorageConfig` to C's
`CStorageConfig` struct for FFI calls
- **GetManifest()**: Parses manifest JSON and retrieves latest column
groups using FFI
- Accepts manifest path with `base_path` and `ver` fields
- Calls `get_latest_column_groups()` FFI function
- Returns column group information as string
- Comprehensive error handling for JSON parsing and FFI errors
3. Dependency Updates
- **internal/core/thirdparty/milvus-storage/CMakeLists.txt**:
- Updated milvus-storage version from `0883026` to `302143c`
- Ensures compatibility with latest FFI interfaces
4. Data Coordinator Changes
All compaction task builders now include manifest path in segment
binlogs:
- **compaction_task_clustering.go**: Added `Manifest:
segInfo.GetManifestPath()` to segment binlogs
- **compaction_task_l0.go**: Added manifest path to both L0 segment
selection and compaction plan building
- **compaction_task_mix.go**: Added manifest path to mixed compaction
segment binlogs
- **meta.go**: Updated metadata completion logic:
- `completeClusterCompactionMutation()`: Set `ManifestPath` in new
segment info
- `completeMixCompactionMutation()`: Preserve manifest path in compacted
segments
- `completeSortCompactionMutation()`: Include manifest path in sorted
segments
5. Data Node Compactor Enhancements
All compactors updated to support dual-mode reading (binlog vs
manifest):
6. Flush & Sync Manager Updates
Pack Writer V2 (pack_writer_v2.go)
- **BulkPackWriterV2.Write()**: Extended return signature to include
`manifest string`
- Implementation:
- Generate manifest path: `path.Join(pack.segmentID, "manifest.json")`
- Write packed data using FFI-based writer
- Return manifest path along with binlogs, deltas, and stats
Task Handling (task.go)
- Updated all sync task result handling to accommodate new manifest
return value
- Ensured backward compatibility for callers not using manifest
7. Go Storage Layer Integration
New Interfaces and Implementations
- **record_reader.go**: Interface for unified record reading across
storage versions
- **record_writer.go**: Interface for unified record writing across
storage versions
- **binlog_record_writer.go**: Concrete implementation for traditional
binlog-based writing
Enhanced Schema Support (schema.go, schema_test.go)
- Schema conversion utilities to support FFI-based storage operations
- Ensures proper Arrow schema mapping for V2 storage
Serialization Updates
- **serde.go, serde_events.go, serde_events_v2.go**: Updated to work
with new reader/writer interfaces
- Test files updated to validate dual-mode serialization
8. Storage V2 Packed Format
FFI Common (storagev2/packed/ffi_common.go)
- Common FFI utilities and type conversions for packed storage format
Packed Writer FFI (storagev2/packed/packed_writer_ffi.go)
- FFI-based implementation of packed writer
- Integrates with Loon storage layer for efficient columnar writes
Packed Reader FFI (storagev2/packed/packed_reader_ffi.go)
- Already existed, now complemented by writer implementation
9. Protocol Buffer Updates
data_coord.proto & datapb/data_coord.pb.go
- Added `manifest` field to compaction segment messages
- Enables passing manifest metadata through compaction pipeline
worker.proto & workerpb/worker.pb.go
- Added compaction parameter for `useLoonFFI` flag
- Allows workers to receive FFI configuration from coordinator
10. Parameter Configuration
component_param.go
- Added `UseLoonFFI` parameter to compaction configuration
- Reads from `common.storage.file.useLoonFFI` config path
- Default: `false` for safe rollout
11. Test Updates
- **clustering_compactor_storage_v2_test.go**: Updated signatures to
handle manifest return value
- **mix_compactor_storage_v2_test.go**: Updated test helpers for
manifest support
- **namespace_compactor_test.go**: Adjusted writer calls to expect
manifest
- **pack_writer_v2_test.go**: Validated manifest generation in pack
writing
This integration follows a **dual-mode approach**:
1. **Legacy Path**: Traditional binlog-based reading/writing (when
`useLoonFFI=false` or no manifest)
2. **FFI Path**: Manifest-based reading/writing through Loon FFI (when
`useLoonFFI=true` and manifest exists)
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
Related to #44956
Add manifest_path field throughout the data path to support LOON Storage
V2 manifest tracking. The manifest stores metadata for segment data
files and enables the unified Storage V2 FFI interface.
Changes include:
- Add manifest_path field to SegmentInfo and SaveBinlogPathsRequest
proto messages
- Add UpdateManifest operator to datacoord meta operations
- Update metacache, sync manager, and meta writer to propagate manifest
paths
- Include manifest_path in segment load info for query coordinator
This is part of the Storage V2 FFI interface integration.
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
This commit addresses issue #44788 where the
`datacoord_stored_binlog_size` metric could become inaccurate when
multiple concurrent `GetMetrics` calls arrived at DataCoord.
### Problem
The original implementation called `Reset()` followed by `Add()`
operations on Prometheus metrics within the `GetQuotaInfo()` method.
When multiple goroutines invoked this method concurrently, race
conditions occurred:
- Thread 1: Reset() → Add(value1)
- Thread 2: Reset() → Add(value2)
- Result: Metrics could be reset multiple times and values added in an
interleaved fashion, leading to inaccurate and inflated metric values
### Solution
Changed the approach from `Reset() + Add()` to aggregating metric values
in local maps first, then using `Set()` to update metrics atomically:
1. Collect segment size data into local maps:
- `storedBinlogSize`: tracks size per collection per segment state
- `binlogFileSize`: tracks total file count per collection
- `coll2DbName`: maps collection IDs to database names
2. After aggregation is complete, use `Set()` (instead of `Add()`) to
update metrics in a single operation per label combination
This ensures that concurrent `GetMetrics` calls don't interfere with
each other, as each invocation works with its own local state and only
updates the final metric value atomically.
---------
Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
issue: #43858
- Remove full-collection index handling in getCollectionMetrics
- Avoid heavy metadata scans and RPC calls during metrics
- Reduce latency and CPU/memory usage on large datasets
- No functional change to metrics semantics
Signed-off-by: Wei Liu <wei.liu@zilliz.com>
We’ve frequently observed data loss caused by broken mutual exclusion in
compaction tasks. This PR introduces a post-check: before modifying
metadata upon compaction task completion, it verifies the state of the
input segments. If any input segment has been dropped, the compaction
task will be marked as failed.
issue: https://github.com/milvus-io/milvus/issues/43513
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
When autoID is enabled, the preimport task estimates row distribution by
evenly dividing the total row count (numRows) across all vchannels:
`estimatedCount = numRows / vchannelNum`.
However, the actual import task hashes real auto-generated IDs to
determine
the target vchannel. This mismatch can lead to inaccurate row
distribution estimation
in such corner cases:
- Importing 1 row into 2 vchannels:
• Preimport: 1 / 2 = 0 → both v0 and v1 are estimated to have 0 rows
• Import: real autoID (e.g., 457975852966809057) hashes to v1
→ actual result: v0 = 0, v1 = 1
To resolve such corner case, we now allocate at least one segment for
each vchannel
when autoID is enabled, ensuring all vchannels are prepared to receive
data even
if no rows are estimated for them.
issue: https://github.com/milvus-io/milvus/issues/41759
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
With concurrenct L0 compaction
(https://github.com/milvus-io/milvus/pull/36816), delta logs might be
written to the same L1 segment, causing logID duplication when using the
incremental beginLogID. This PR removes the beginLogID mechanism and
instead passes a log ID range, where the number of IDs in the range
equals the number of compaction segment binlogs multiplied by an
expansion factor.
issue: https://github.com/milvus-io/milvus/issues/40207
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
Read metadata such as segments, binlogs, and partitions concurrently at
the collection level.
issue: https://github.com/milvus-io/milvus/issues/37630
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
1. Using secondary index to avoid retrieving all segments at
`GetSegmentsChanPart`.
2. Perform batch SetAllocations to reduce the number of times the meta
lock is acquired.
issue: https://github.com/milvus-io/milvus/issues/37630
---------
Signed-off-by: bigsheeper <yihao.dai@zilliz.com>
