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https://github.com/milvus-io/milvus.git
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## Summary issue: #51217 Load requests introduce resource demand before QueryNode waterlines reflect the new data. This PR adds optional QueryCoord resource prechecks before LoadCollection/LoadPartitions configuration broadcasts and publishes cumulative demand counters for external autoscaling decisions. Design: [Autoscale-Aware Load Resource Admission in QueryCoord](https://github.com/sijie-ni-0214/milvus/blob/querycoord-autoscale-kernel/docs/design-docs/design_docs/20260721-querycoord-autoscale-load-resource-precheck.md). ## Admission behavior - Estimate incremental final sealed-segment memory and local-disk demand per resource group from the requested and current load configurations. - With tiered eviction disabled, compare demand with memory availability and each Worker's configured `LOCAL_STORAGE_SIZE` quota minus cached local-directory usage after admission thresholds. Optionally admit shortages within configured global autoscale upper bounds. - With tiered eviction enabled, retain demand estimation and skip QN capacity sampling, node availability checks, and global autoscale-limit checks. Existing evictable caches make physical usage unsuitable for this admission decision; Worker QN retains its loading-stage guard. - Fail open on metadata, estimation, and capacity-metrics failures. Capacity-metrics failures preserve successfully estimated demand; metadata or estimation failures leave no demand to publish. - Return a resource-insufficient status with `suggested_expand_percent` when a complete capacity evaluation rejects the request. Proxy preserves the status and ExtraInfo. - Admission remains best-effort, without reservations or accounting for concurrent accepted requests. QueryCoord does not subtract Worker in-flight load reservations; the Worker guard remains authoritative. The existing replica node-count prerequisite remains; node provisioning and scale-from-zero are outside this PR. ## Load demand counters Expose cumulative counters labeled by resource group: - `milvus_querycoord_load_demand_memory_bytes` - `milvus_querycoord_load_demand_disk_bytes` Counters increase only when demand estimation succeeds, the request proceeds, and its configuration broadcast succeeds. This includes tiered loads and loads admitted through capacity-metrics fail-open. Disabled prechecks, unchanged configurations, zero incremental demand, estimation failures, explicit rejections, and failed broadcasts do not increase counters. Load completion and release do not decrement them. Series start at zero for existing resource groups and are removed on RG deletion. The dashboard displays cumulative values in MiB; the control plane computes interval increments, handles counter resets, and combines demand with QN waterlines and provisioning state. These counters are observations, not durable reservations. Internal handoff and balancing tasks do not contribute to them. ## Resource estimation and sampling - Share segment/index estimation in `internal/util/segcore/loadresource`, retaining separate final-resource and loading-peak APIs. Worker QN uses its CGo pool; QueryCoord estimates sequentially within each request. - Fetch recovery metadata, full segment metadata, and batched index metadata. Support Storage V3 resource summaries and dropped-field metadata. Filter indexes by loaded fields, retaining multiple JSON-path indexes on one field. - Apply the load-request collection mmap inheritance logic to cloned expected/current schemas while preserving field overrides. The final estimator applies cache ratios only with tiered eviction enabled. Delegator-side Bloom/BM25 resources are outside the Worker estimate. - Deduplicate QN resource sampling by node ID, use at most 16 concurrent requests and one attempt per node, and bound the entire sampling round to ten seconds. Reuse the snapshot for RG and global calculations. Exclude embedded SQNs from global capacity and sampling; empty eligible-node sets are unevaluable and fail open. - Worker QNs report `LOCAL_STORAGE_SIZE` and cached local-directory usage through `system_info`. QueryCoord uses these byte values for disk availability, RG suggestions, and the global disk-capacity sum; filesystem-wide disk metrics remain for monitoring. Shared filesystems require per-QN quotas consistent with the shared capacity. ## Configuration - `queryCoord.autoscale.precheckEnabled`: enable demand estimation and precheck; default `false`. - `queryCoord.autoscale.enabled`: allow admission within global autoscale bounds when current capacity is insufficient; default `false`, effective only with precheck enabled and tiered eviction disabled. - `queryCoord.autoscale.maxMemoryLimit`: maximum global Worker QN physical memory capacity after scaling, in GiB; default `0` means no additional memory autoscale capacity. - `queryCoord.autoscale.maxDiskLimit`: maximum sum of Worker QN `LOCAL_STORAGE_SIZE` quotas after scaling, in GiB; default `0` means no additional disk autoscale capacity. Both limits use `1 GiB = 1024^3 bytes`. For non-tiered deployments, configure QueryCoord's memory high-water level no higher than the Worker admission threshold. This relationship is a rollout prerequisite and is not enforced by this PR. ## Validation Local autoscale estimator and targeted QueryCoord tests passed, including multiple-index filtering, collection mmap overrides, the ten-second sampling timeout, empty-node fail-open, embedded-SQN exclusion, tiered demand preservation, capacity-metrics failure behavior, and local-storage quota accounting for QueryNodes sharing a filesystem. Both load callbacks are tested for precheck rejection, broadcast failure, successful counter updates, tiered loads, and capacity-metrics failures followed by successful or failed broadcasts. Tests assert counters remain unchanged during Broadcast and increment only after it succeeds. These are local unit/callback checks, not end-to-end external autoscaler validation. Local `make static-check` passed across core, pkg, client, and go_client with zero issues, and segcore error-boundary checks passed. Targeted QueryCoord and QueryNode tests, YAML consistency, and `make build-go` passed. External autoscaler behavior remains subject to CI and rollout validation. --------- Signed-off-by: sijie-ni-0214 <[email protected]>
403 lines
12 KiB
Go
403 lines
12 KiB
Go
// Licensed to the LF AI & Data foundation under one
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// or more contributor license agreements. See the NOTICE file
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// distributed with this work for additional information
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// regarding copyright ownership. The ASF licenses this file
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// to you under the Apache License, Version 2.0 (the
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// "License"); you may not use this file except in compliance
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// with the License. You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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package loadresource
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import (
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"context"
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"testing"
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"github.com/stretchr/testify/require"
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"github.com/milvus-io/milvus-proto/go-api/v3/commonpb"
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"github.com/milvus-io/milvus-proto/go-api/v3/schemapb"
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"github.com/milvus-io/milvus/pkg/v3/common"
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"github.com/milvus-io/milvus/pkg/v3/proto/datapb"
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"github.com/milvus-io/milvus/pkg/v3/proto/querypb"
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"github.com/milvus-io/milvus/pkg/v3/util/metric"
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"github.com/milvus-io/milvus/pkg/v3/util/paramtable"
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)
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func TestEstimateTantivyValidityBitmapBytesWordAligned(t *testing.T) {
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require.EqualValues(t, 0, estimateTantivyValidityBitmapBytes(-1))
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require.EqualValues(t, 0, estimateTantivyValidityBitmapBytes(0))
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require.EqualValues(t, 8, estimateTantivyValidityBitmapBytes(1))
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require.EqualValues(t, 8, estimateTantivyValidityBitmapBytes(64))
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require.EqualValues(t, 16, estimateTantivyValidityBitmapBytes(65))
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require.EqualValues(t, 24, estimateTantivyValidityBitmapBytes(129))
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}
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func TestEstimateSegmentFinalResourceUsesBinlogStatsAndTieredRatio(t *testing.T) {
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schema := &schemapb.CollectionSchema{
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Name: "test_final_estimate",
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Fields: []*schemapb.FieldSchema{
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{FieldID: common.TimeStampField, Name: common.TimeStampFieldName, DataType: schemapb.DataType_Int64},
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{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true},
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{FieldID: 101, Name: "vec", DataType: schemapb.DataType_FloatVector, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "4"}}},
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{FieldID: 102, Name: "json", DataType: schemapb.DataType_JSON},
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{FieldID: 103, Name: "bm25", DataType: schemapb.DataType_SparseFloatVector},
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},
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}
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loadInfo := &querypb.SegmentLoadInfo{
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CollectionID: 1,
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PartitionID: 2,
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SegmentID: 3,
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NumOfRows: 10,
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BinlogPaths: []*datapb.FieldBinlog{
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{
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FieldID: common.TimeStampField,
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Binlogs: []*datapb.Binlog{
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{MemorySize: 80, LogSize: 50, EntriesNum: 10},
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},
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},
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{
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FieldID: 101,
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Binlogs: []*datapb.Binlog{
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{LogSize: 160},
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},
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},
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{
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FieldID: 102,
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Binlogs: []*datapb.Binlog{
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{MemorySize: 200, LogSize: 120},
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},
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},
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},
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Statslogs: []*datapb.FieldBinlog{
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{Binlogs: []*datapb.Binlog{{MemorySize: 30, LogSize: 20}}},
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},
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Deltalogs: []*datapb.FieldBinlog{
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{Binlogs: []*datapb.Binlog{{MemorySize: 40, LogSize: 40}}},
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},
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Bm25Logs: []*datapb.FieldBinlog{
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{FieldID: 103, Binlogs: []*datapb.Binlog{{MemorySize: 40, LogSize: 20}}},
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},
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JsonKeyStatsLogs: map[int64]*datapb.JsonKeyStats{
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102: {MemorySize: 100, LogSize: 90},
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},
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TextStatsLogs: map[int64]*datapb.TextIndexStats{
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102: {MemorySize: 50, LogSize: 40},
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},
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}
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for _, test := range []struct {
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name string
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tieredEnabled bool
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expectedMemory uint64
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expectedDisk uint64
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}{
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{name: "disabled uses full evictable resource", expectedMemory: 778, expectedDisk: 310},
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{name: "enabled applies cache ratios", tieredEnabled: true, expectedMemory: 484, expectedDisk: 78},
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} {
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t.Run(test.name, func(t *testing.T) {
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, loadInfo, SegmentFinalEstimateOptions{
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MmapVectorField: true,
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MmapScalarField: false,
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MmapJSONStats: true,
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TieredEvictionEnabled: test.tieredEnabled,
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TieredEvictableMemoryCacheRatio: 0.5,
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TieredEvictableDiskCacheRatio: 0.25,
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DeltaDataExpansionFactor: 2,
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JSONKeyStatsExpansionFactor: 1.5,
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TextIndexExpansionFactor: 2,
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PreferFieldDataWhenIndexHasRawData: false,
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}, nil)
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require.NoError(t, err)
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require.Equal(t, test.expectedMemory, usage.MemoryBytes)
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require.Equal(t, test.expectedDisk, usage.DiskBytes)
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})
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}
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}
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func TestEstimateSegmentLoadingResourceAccountsForTantivyValidityBitmap(t *testing.T) {
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schema := &schemapb.CollectionSchema{
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Name: "test_text_loading_estimate",
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Fields: []*schemapb.FieldSchema{
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{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true},
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{FieldID: 101, Name: "text", DataType: schemapb.DataType_VarChar},
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},
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}
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loadInfo := &querypb.SegmentLoadInfo{
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NumOfRows: 65,
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TextStatsLogs: map[int64]*datapb.TextIndexStats{
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101: {FieldID: 101, MemorySize: 100},
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},
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}
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for _, test := range []struct {
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name string
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mmap bool
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tiered bool
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expectedMemory uint64
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expectedDisk uint64
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}{
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{name: "non-mmap", expectedMemory: 116},
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{name: "mmap", mmap: true, expectedMemory: 16, expectedDisk: 100},
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{name: "tiered skips loading reservation", tiered: true},
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} {
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t.Run(test.name, func(t *testing.T) {
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usage, err := EstimateSegmentLoadingResource(context.Background(), schema, loadInfo, SegmentLoadingEstimateOptions{
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MmapScalarField: test.mmap,
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TieredEvictionEnabled: test.tiered,
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TextIndexExpansionFactor: 1,
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}, nil)
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require.NoError(t, err)
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require.Equal(t, test.expectedMemory, usage.MemoryBytes)
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require.Equal(t, test.expectedDisk, usage.DiskBytes)
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})
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}
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}
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func TestEstimateSegmentFinalResourceAllowsZeroTieredRatio(t *testing.T) {
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schema := &schemapb.CollectionSchema{
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Name: "test_zero_tiered_ratio",
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Fields: []*schemapb.FieldSchema{
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{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true},
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{FieldID: 101, Name: "vec", DataType: schemapb.DataType_FloatVector, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "4"}}},
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},
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}
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loadInfo := &querypb.SegmentLoadInfo{
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CollectionID: 1,
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PartitionID: 2,
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SegmentID: 3,
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NumOfRows: 10,
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BinlogPaths: []*datapb.FieldBinlog{
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{
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FieldID: 100,
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Binlogs: []*datapb.Binlog{
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{MemorySize: 100, LogSize: 80},
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},
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},
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{
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FieldID: 101,
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Binlogs: []*datapb.Binlog{
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{MemorySize: 200, LogSize: 160},
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},
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},
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},
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Statslogs: []*datapb.FieldBinlog{
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{Binlogs: []*datapb.Binlog{{MemorySize: 30, LogSize: 20}}},
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},
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}
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, loadInfo, SegmentFinalEstimateOptions{
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MmapVectorField: true,
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TieredEvictionEnabled: true,
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TieredEvictableMemoryCacheRatio: 0,
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TieredEvictableDiskCacheRatio: 0,
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}, nil)
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require.NoError(t, err)
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require.EqualValues(t, 30, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
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}
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func TestEstimateSegmentFinalResourceOnlyExpandsLegacyDelta(t *testing.T) {
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schema := &schemapb.CollectionSchema{Name: "test_delta_estimate"}
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for _, test := range []struct {
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name string
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memorySize int64
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logSize int64
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expectedMemory uint64
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}{
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{
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name: "storage v3 summary has no disk size",
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memorySize: 100,
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expectedMemory: 100,
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},
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{
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name: "legacy compressed size uses expansion",
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memorySize: 100,
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logSize: 100,
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expectedMemory: 300,
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},
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} {
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t.Run(test.name, func(t *testing.T) {
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, &querypb.SegmentLoadInfo{
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Deltalogs: []*datapb.FieldBinlog{{
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Binlogs: []*datapb.Binlog{{MemorySize: test.memorySize, LogSize: test.logSize}},
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}},
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}, SegmentFinalEstimateOptions{DeltaDataExpansionFactor: 3}, nil)
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require.NoError(t, err)
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require.Equal(t, test.expectedMemory, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
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})
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}
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}
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func TestEstimateSegmentFinalResourceSkipsDroppedFields(t *testing.T) {
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schema := &schemapb.CollectionSchema{
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Name: "test_dropped_fields",
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Fields: []*schemapb.FieldSchema{
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{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true},
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},
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}
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t.Run("index", func(t *testing.T) {
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runnerCalled := false
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, &querypb.SegmentLoadInfo{
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IndexInfos: []*querypb.FieldIndexInfo{
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{FieldID: 999, IndexFilePaths: []string{"index"}},
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},
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BinlogPaths: []*datapb.FieldBinlog{
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{FieldID: 100, Binlogs: []*datapb.Binlog{{MemorySize: 64}}},
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},
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}, SegmentFinalEstimateOptions{}, func(fn func() error) error {
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runnerCalled = true
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return fn()
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})
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require.NoError(t, err)
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require.False(t, runnerCalled)
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require.EqualValues(t, 64, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
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})
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t.Run("binlog group with only dropped fields", func(t *testing.T) {
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, &querypb.SegmentLoadInfo{
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BinlogPaths: []*datapb.FieldBinlog{
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{
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FieldID: 200,
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ChildFields: []int64{999},
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Binlogs: []*datapb.Binlog{{MemorySize: 128}},
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},
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{
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FieldID: 998,
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Binlogs: []*datapb.Binlog{{MemorySize: 128}},
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},
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},
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}, SegmentFinalEstimateOptions{}, nil)
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require.NoError(t, err)
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require.Zero(t, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
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})
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t.Run("binlog group with live and dropped fields", func(t *testing.T) {
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usage, err := EstimateSegmentFinalResource(context.Background(), schema, &querypb.SegmentLoadInfo{
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BinlogPaths: []*datapb.FieldBinlog{
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{
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FieldID: 200,
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ChildFields: []int64{999, 100},
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Binlogs: []*datapb.Binlog{{MemorySize: 128}},
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},
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},
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}, SegmentFinalEstimateOptions{MmapVectorField: true}, nil)
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require.NoError(t, err)
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require.EqualValues(t, 128, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
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})
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}
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func TestEstimateSegmentLoadingResourceSkipsCAGRAGPUMemoryWhenAdaptForCPU(t *testing.T) {
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paramtable.Init()
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schema := &schemapb.CollectionSchema{
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Name: "test_gpu_adapt_for_cpu",
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Fields: []*schemapb.FieldSchema{
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{FieldID: 100, Name: "pk", DataType: schemapb.DataType_Int64, IsPrimaryKey: true},
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{FieldID: 101, Name: "vec", DataType: schemapb.DataType_FloatVector, TypeParams: []*commonpb.KeyValuePair{{Key: common.DimKey, Value: "4"}}},
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},
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}
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loadInfo := &querypb.SegmentLoadInfo{
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CollectionID: 1,
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PartitionID: 2,
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SegmentID: 3,
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NumOfRows: 10,
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IndexInfos: []*querypb.FieldIndexInfo{
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{
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FieldID: 101,
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IndexID: 10,
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BuildID: 11,
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IndexFilePaths: []string{"index"},
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IndexParams: []*commonpb.KeyValuePair{
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{Key: common.IndexTypeKey, Value: "GPU_CAGRA"},
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{Key: common.MetricTypeKey, Value: metric.L2},
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{Key: "adapt_for_cpu", Value: "true"},
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},
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},
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},
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}
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usage, err := EstimateSegmentLoadingResource(context.Background(), schema, loadInfo, SegmentLoadingEstimateOptions{}, func(func() error) error {
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return nil
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})
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require.NoError(t, err)
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require.Empty(t, usage.FieldGPUMemoryBytes)
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}
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func TestEstimateSegmentLoadingResourceKeepsMilvusTableRealPKEager(t *testing.T) {
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paramtable.Init()
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schema := &schemapb.CollectionSchema{
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Name: "test_milvus_table_real_pk",
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ExternalSource: "s3://bucket/source",
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ExternalSpec: `{"format":"milvus-table"}`,
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Fields: []*schemapb.FieldSchema{
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{
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FieldID: 100,
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Name: "pk",
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DataType: schemapb.DataType_Int64,
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IsPrimaryKey: true,
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ExternalField: "pk",
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TypeParams: []*commonpb.KeyValuePair{
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{Key: common.WarmupKey, Value: common.WarmupDisable},
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},
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},
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{
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FieldID: 101,
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Name: "vec",
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DataType: schemapb.DataType_FloatVector,
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ExternalField: "vec",
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TypeParams: []*commonpb.KeyValuePair{
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{Key: common.DimKey, Value: "4"},
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{Key: common.WarmupKey, Value: common.WarmupDisable},
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},
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},
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},
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}
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loadInfo := &querypb.SegmentLoadInfo{
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CollectionID: 1,
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PartitionID: 2,
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SegmentID: 3,
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NumOfRows: 10,
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BinlogPaths: []*datapb.FieldBinlog{
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{
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FieldID: 0,
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ChildFields: []int64{100, 101},
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Binlogs: []*datapb.Binlog{
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{MemorySize: 1000, LogSize: 1000, EntriesNum: 10},
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},
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},
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},
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}
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usage, err := EstimateSegmentLoadingResource(context.Background(), schema, loadInfo, SegmentLoadingEstimateOptions{
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ExternalRawDataFactor: 2,
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}, nil)
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require.NoError(t, err)
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require.EqualValues(t, 2000, usage.MemoryBytes)
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require.Zero(t, usage.DiskBytes)
|
|
require.EqualValues(t, 100, loadInfo.GetEstimatedBytesPerRow())
|
|
}
|