initial commit

vendor/github.com/blevesearch/bleve/index/firestorm/analysis.go

@@ -0,0 +1,169 @@
+//  Copyright (c) 2015 Couchbase, Inc.
+//  Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file
+//  except in compliance with the License. You may obtain a copy of the License at
+//    http://www.apache.org/licenses/LICENSE-2.0
+//  Unless required by applicable law or agreed to in writing, software distributed under the
+//  License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND,
+//  either express or implied. See the License for the specific language governing permissions
+//  and limitations under the License.
+
+package firestorm
+
+import (
+	"math"
+
+	"github.com/blevesearch/bleve/analysis"
+	"github.com/blevesearch/bleve/document"
+	"github.com/blevesearch/bleve/index"
+)
+
+func (f *Firestorm) Analyze(d *document.Document) *index.AnalysisResult {
+
+	rv := &index.AnalysisResult{
+		DocID: d.ID,
+		Rows:  make([]index.IndexRow, 0, 100),
+	}
+
+	docIDBytes := []byte(d.ID)
+
+	// add the _id row
+	rv.Rows = append(rv.Rows, NewTermFreqRow(0, nil, docIDBytes, d.Number, 0, 0, nil))
+
+	// information we collate as we merge fields with same name
+	fieldTermFreqs := make(map[uint16]analysis.TokenFrequencies)
+	fieldLengths := make(map[uint16]int)
+	fieldIncludeTermVectors := make(map[uint16]bool)
+	fieldNames := make(map[uint16]string)
+
+	analyzeField := func(field document.Field, storable bool) {
+		fieldIndex, newFieldRow := f.fieldIndexOrNewRow(field.Name())
+		if newFieldRow != nil {
+			rv.Rows = append(rv.Rows, newFieldRow)
+		}
+		fieldNames[fieldIndex] = field.Name()
+
+		if field.Options().IsIndexed() {
+			fieldLength, tokenFreqs := field.Analyze()
+			existingFreqs := fieldTermFreqs[fieldIndex]
+			if existingFreqs == nil {
+				fieldTermFreqs[fieldIndex] = tokenFreqs
+			} else {
+				existingFreqs.MergeAll(field.Name(), tokenFreqs)
+				fieldTermFreqs[fieldIndex] = existingFreqs
+			}
+			fieldLengths[fieldIndex] += fieldLength
+			fieldIncludeTermVectors[fieldIndex] = field.Options().IncludeTermVectors()
+		}
+
+		if storable && field.Options().IsStored() {
+			storeRow := f.storeField(docIDBytes, d.Number, field, fieldIndex)
+			rv.Rows = append(rv.Rows, storeRow)
+		}
+	}
+
+	for _, field := range d.Fields {
+		analyzeField(field, true)
+	}
+
+	if len(d.CompositeFields) > 0 {
+		for fieldIndex, tokenFreqs := range fieldTermFreqs {
+			// see if any of the composite fields need this
+			for _, compositeField := range d.CompositeFields {
+				compositeField.Compose(fieldNames[fieldIndex], fieldLengths[fieldIndex], tokenFreqs)
+			}
+		}
+
+		for _, compositeField := range d.CompositeFields {
+			analyzeField(compositeField, false)
+		}
+	}
+
+	rowsCapNeeded := len(rv.Rows)
+	for _, tokenFreqs := range fieldTermFreqs {
+		rowsCapNeeded += len(tokenFreqs)
+	}
+
+	rows := make([]index.IndexRow, 0, rowsCapNeeded)
+	rv.Rows = append(rows, rv.Rows...)
+
+	// walk through the collated information and process
+	// once for each indexed field (unique name)
+	for fieldIndex, tokenFreqs := range fieldTermFreqs {
+		fieldLength := fieldLengths[fieldIndex]
+		includeTermVectors := fieldIncludeTermVectors[fieldIndex]
+
+		rv.Rows = f.indexField(docIDBytes, d.Number, includeTermVectors, fieldIndex, fieldLength, tokenFreqs, rv.Rows)
+	}
+
+	return rv
+}
+
+func (f *Firestorm) indexField(docID []byte, docNum uint64, includeTermVectors bool, fieldIndex uint16, fieldLength int, tokenFreqs analysis.TokenFrequencies, rows []index.IndexRow) []index.IndexRow {
+
+	tfrs := make([]TermFreqRow, len(tokenFreqs))
+
+	fieldNorm := float32(1.0 / math.Sqrt(float64(fieldLength)))
+
+	if !includeTermVectors {
+		i := 0
+		for _, tf := range tokenFreqs {
+			rows = append(rows, InitTermFreqRow(&tfrs[i], fieldIndex, tf.Term, docID, docNum, uint64(tf.Frequency()), fieldNorm, nil))
+			i++
+		}
+		return rows
+	}
+
+	i := 0
+	for _, tf := range tokenFreqs {
+		var tv []*TermVector
+		tv, rows = f.termVectorsFromTokenFreq(fieldIndex, tf, rows)
+		rows = append(rows, InitTermFreqRow(&tfrs[i], fieldIndex, tf.Term, docID, docNum, uint64(tf.Frequency()), fieldNorm, tv))
+		i++
+	}
+	return rows
+}
+
+func (f *Firestorm) termVectorsFromTokenFreq(field uint16, tf *analysis.TokenFreq, rows []index.IndexRow) ([]*TermVector, []index.IndexRow) {
+	rv := make([]*TermVector, len(tf.Locations))
+
+	for i, l := range tf.Locations {
+		var newFieldRow *FieldRow
+		fieldIndex := field
+		if l.Field != "" {
+			// lookup correct field
+			fieldIndex, newFieldRow = f.fieldIndexOrNewRow(l.Field)
+			if newFieldRow != nil {
+				rows = append(rows, newFieldRow)
+			}
+		}
+		tv := NewTermVector(fieldIndex, uint64(l.Position), uint64(l.Start), uint64(l.End), l.ArrayPositions)
+		rv[i] = tv
+	}
+
+	return rv, rows
+}
+
+func (f *Firestorm) storeField(docID []byte, docNum uint64, field document.Field, fieldIndex uint16) index.IndexRow {
+	fieldValue := make([]byte, 1+len(field.Value()))
+	fieldValue[0] = encodeFieldType(field)
+	copy(fieldValue[1:], field.Value())
+	storedRow := NewStoredRow(docID, docNum, fieldIndex, field.ArrayPositions(), fieldValue)
+	return storedRow
+}
+
+func encodeFieldType(f document.Field) byte {
+	fieldType := byte('x')
+	switch f.(type) {
+	case *document.TextField:
+		fieldType = 't'
+	case *document.NumericField:
+		fieldType = 'n'
+	case *document.DateTimeField:
+		fieldType = 'd'
+	case *document.BooleanField:
+		fieldType = 'b'
+	case *document.CompositeField:
+		fieldType = 'c'
+	}
+	return fieldType
+}