7e36109b3c
This API (unexported) will estimate the amount of memory needed to execute
a search query over an index before the collector begins data collection.
Sample estimates for certain queries:
{Size: 10, BenchmarkUpsidedownSearchOverhead}
ESTIMATE BENCHMEM
TermQuery 4616 4796
MatchQuery 5210 5405
DisjunctionQuery (Match queries) 7700 8447
DisjunctionQuery (Term queries) 6514 6591
ConjunctionQuery (Match queries) 7524 8175
Nested disjunction query (disjunction of disjunctions) 10306 10708
…
118 lines
2.5 KiB
Go
118 lines
2.5 KiB
Go
// Copyright (c) 2014 Couchbase, Inc.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// 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 facet
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import (
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"reflect"
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"sort"
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"github.com/blevesearch/bleve/search"
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"github.com/blevesearch/bleve/size"
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)
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var reflectStaticSizeTermsFacetBuilder int
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func init() {
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var tfb TermsFacetBuilder
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reflectStaticSizeTermsFacetBuilder = int(reflect.TypeOf(tfb).Size())
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}
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type TermsFacetBuilder struct {
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size int
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field string
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termsCount map[string]int
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total int
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missing int
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sawValue bool
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}
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func NewTermsFacetBuilder(field string, size int) *TermsFacetBuilder {
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return &TermsFacetBuilder{
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size: size,
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field: field,
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termsCount: make(map[string]int),
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}
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}
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func (fb *TermsFacetBuilder) Size() int {
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sizeInBytes := reflectStaticSizeTermsFacetBuilder + size.SizeOfPtr +
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len(fb.field)
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for k, _ := range fb.termsCount {
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sizeInBytes += size.SizeOfString + len(k) +
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size.SizeOfInt
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}
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return sizeInBytes
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}
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func (fb *TermsFacetBuilder) Field() string {
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return fb.field
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}
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func (fb *TermsFacetBuilder) UpdateVisitor(field string, term []byte) {
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if field == fb.field {
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fb.sawValue = true
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fb.termsCount[string(term)] = fb.termsCount[string(term)] + 1
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fb.total++
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}
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}
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func (fb *TermsFacetBuilder) StartDoc() {
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fb.sawValue = false
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}
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func (fb *TermsFacetBuilder) EndDoc() {
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if !fb.sawValue {
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fb.missing++
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}
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}
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func (fb *TermsFacetBuilder) Result() *search.FacetResult {
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rv := search.FacetResult{
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Field: fb.field,
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Total: fb.total,
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Missing: fb.missing,
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}
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rv.Terms = make([]*search.TermFacet, 0, len(fb.termsCount))
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for term, count := range fb.termsCount {
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tf := &search.TermFacet{
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Term: term,
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Count: count,
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}
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rv.Terms = append(rv.Terms, tf)
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}
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sort.Sort(rv.Terms)
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// we now have the list of the top N facets
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trimTopN := fb.size
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if trimTopN > len(rv.Terms) {
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trimTopN = len(rv.Terms)
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}
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rv.Terms = rv.Terms[:trimTopN]
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notOther := 0
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for _, tf := range rv.Terms {
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notOther += tf.Count
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}
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rv.Other = fb.total - notOther
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return &rv
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}
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