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214 lines
5.7 KiB
Go
214 lines
5.7 KiB
Go
/*
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* # 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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*/
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package chain
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import "github.com/milvus-io/milvus/pkg/v3/util/merr"
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// ColumnSet is a small set helper for column names.
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type ColumnSet map[string]struct{}
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// NewColumnSet creates a ColumnSet from column names.
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func NewColumnSet(cols ...string) ColumnSet {
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set := make(ColumnSet, len(cols))
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for _, col := range cols {
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set.Add(col)
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}
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return set
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}
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// Add adds a column name to the set.
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func (s ColumnSet) Add(col string) {
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if col == "" {
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return
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}
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s[col] = struct{}{}
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}
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// Remove removes a column name from the set.
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func (s ColumnSet) Remove(col string) {
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delete(s, col)
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}
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// Contains reports whether the set contains a column name.
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func (s ColumnSet) Contains(col string) bool {
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_, ok := s[col]
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return ok
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}
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// Clone returns a copy of the set.
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func (s ColumnSet) Clone() ColumnSet {
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clone := make(ColumnSet, len(s))
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for col := range s {
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clone[col] = struct{}{}
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}
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return clone
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}
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// RemoveSystemColumns removes function-chain system columns from the set.
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func (s ColumnSet) RemoveSystemColumns() {
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for col := range s {
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if IsFunctionChainSystemName(col) {
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delete(s, col)
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}
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}
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}
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// DownstreamSpec describes non-system columns consumed after FuncChain execution.
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// It is the liveness root for optimization, not the final API response projection.
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type DownstreamSpec struct {
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RequiredColumns []string
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}
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// SystemColumnPolicy controls how pruning treats function-chain system columns.
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type SystemColumnPolicy struct {
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KeepAllSystemColumns bool
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}
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func normalizeSystemColumnPolicy(policy SystemColumnPolicy) SystemColumnPolicy {
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// The current conservative default is to retain all existing system columns.
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if !policy.KeepAllSystemColumns {
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policy.KeepAllSystemColumns = true
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}
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return policy
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}
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// ExecuteOptions controls optional FuncChain execution optimizations.
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type ExecuteOptions struct {
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EnableColumnPruning bool
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EnableParallel bool // reserved for future schedule support
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Downstream DownstreamSpec
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SystemColumnPolicy SystemColumnPolicy
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}
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// LivenessInfo contains non-system column liveness for each operator.
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type LivenessInfo struct {
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LiveBefore []ColumnSet
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LiveAfter []ColumnSet
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}
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// OptimizationPlan is non-executable metadata used by FuncChain.ExecuteWithOptions.
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type OptimizationPlan struct {
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Liveness *LivenessInfo
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PruneBefore []ColumnSet
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PruneAfter []ColumnSet
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SystemColumnPolicy SystemColumnPolicy
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}
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type functionChainPlanner struct {
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operators []Operator
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opts ExecuteOptions
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}
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func (fc *FuncChain) buildOptimizationPlan(opts ExecuteOptions) (*OptimizationPlan, error) {
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planner := functionChainPlanner{
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operators: fc.operators,
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opts: opts,
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}
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return planner.Plan()
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}
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func (p functionChainPlanner) Plan() (*OptimizationPlan, error) {
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if !p.opts.EnableColumnPruning && !p.opts.EnableParallel {
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return nil, nil
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}
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if p.opts.EnableParallel {
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return nil, merr.WrapErrServiceInternal("function chain parallel execution is not implemented")
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}
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if err := p.validateOperatorMetadata(); err != nil {
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return nil, err
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}
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liveness := p.analyzeLiveness()
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return &OptimizationPlan{
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Liveness: liveness,
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PruneBefore: liveness.LiveBefore,
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PruneAfter: liveness.LiveAfter,
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SystemColumnPolicy: normalizeSystemColumnPolicy(p.opts.SystemColumnPolicy),
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}, nil
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}
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func (p functionChainPlanner) validateOperatorMetadata() error {
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for i, op := range p.operators {
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if op == nil {
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return merr.WrapErrServiceInternalMsg("operator[%d] is nil", i)
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}
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for _, input := range op.Inputs() {
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if input == "" {
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return merr.WrapErrServiceInternalMsg("operator[%d] %s has empty input column", i, op.Name())
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}
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}
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seenOutputs := make(map[string]struct{}, len(op.Outputs()))
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for _, output := range op.Outputs() {
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if output == "" {
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return merr.WrapErrServiceInternalMsg("operator[%d] %s has empty output column", i, op.Name())
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}
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if _, ok := seenOutputs[output]; ok {
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return merr.WrapErrServiceInternalMsg("operator[%d] %s has duplicate output column %q", i, op.Name(), output)
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}
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seenOutputs[output] = struct{}{}
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}
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}
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for _, col := range p.opts.Downstream.RequiredColumns {
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if col == "" {
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return merr.WrapErrServiceInternal("downstream required column is empty")
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}
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}
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return nil
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}
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func (p functionChainPlanner) analyzeLiveness() *LivenessInfo {
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n := len(p.operators)
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liveBefore := make([]ColumnSet, n)
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liveAfter := make([]ColumnSet, n)
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live := NewColumnSet(p.opts.Downstream.RequiredColumns...)
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live.RemoveSystemColumns()
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for i := n - 1; i >= 0; i-- {
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op := p.operators[i]
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liveAfter[i] = live.Clone()
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next := live.Clone()
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for _, output := range op.Outputs() {
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if IsFunctionChainSystemName(output) {
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continue
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}
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next.Remove(output)
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}
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for _, input := range op.Inputs() {
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if IsFunctionChainSystemName(input) {
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continue
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}
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next.Add(input)
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}
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liveBefore[i] = next.Clone()
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live = next
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}
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return &LivenessInfo{
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LiveBefore: liveBefore,
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LiveAfter: liveAfter,
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}
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}
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