mirror of
https://github.com/milvus-io/milvus.git
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congqixiaandGitHub
c8dd73314c
Related to #51419 Update the Go client module path, imports, dependencies, tests, examples, and documentation from client/v2 to client/v3. Set the SDK version to 3.0.0 in preparation for the Milvus 3.0 release. Signed-off-by: Congqi Xia <congqi.xia@zilliz.com>
452 lines
12 KiB
Go
452 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 column
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import (
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"fmt"
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"math"
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"math/rand"
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"testing"
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"time"
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"github.com/stretchr/testify/suite"
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"github.com/milvus-io/milvus/client/v3/entity"
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)
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type ScalarSuite struct {
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suite.Suite
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}
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func (s *ScalarSuite) TestBasic() {
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s.Run("column_bool", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []bool{true, false}
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column := NewColumnBool(name, data)
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s.Equal(entity.FieldTypeBool, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetBoolData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnBool)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeBool, column.Type())
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}
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})
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s.Run("column_int8", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []int8{1, 2, 3}
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column := NewColumnInt8(name, data)
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s.Equal(entity.FieldTypeInt8, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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fdData := fd.GetScalars().GetIntData().GetData()
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for i, row := range data {
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s.EqualValues(row, fdData[i])
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}
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnInt8)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeInt8, column.Type())
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}
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})
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s.Run("column_int16", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []int16{1, 2, 3}
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column := NewColumnInt16(name, data)
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s.Equal(entity.FieldTypeInt16, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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fdData := fd.GetScalars().GetIntData().GetData()
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for i, row := range data {
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s.EqualValues(row, fdData[i])
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}
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnInt16)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeInt16, column.Type())
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}
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})
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s.Run("column_int32", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []int32{1, 2, 3}
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column := NewColumnInt32(name, data)
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s.Equal(entity.FieldTypeInt32, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetIntData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnInt32)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeInt32, column.Type())
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}
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})
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s.Run("column_int64", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []int64{1, 2, 3}
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column := NewColumnInt64(name, data)
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s.Equal(entity.FieldTypeInt64, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetLongData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnInt64)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeInt64, column.Type())
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}
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})
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s.Run("column_float", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []float32{1.1, 2.2, 3.3}
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column := NewColumnFloat(name, data)
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s.Equal(entity.FieldTypeFloat, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetFloatData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnFloat)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeFloat, column.Type())
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}
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})
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s.Run("column_double", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []float64{1.1, 2.2, 3.3}
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column := NewColumnDouble(name, data)
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s.Equal(entity.FieldTypeDouble, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetDoubleData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnDouble)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeDouble, column.Type())
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}
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})
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s.Run("column_varchar", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []string{"a", "b", "c"}
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column := NewColumnVarChar(name, data)
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s.Equal(entity.FieldTypeVarChar, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetStringData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnVarChar)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeVarChar, column.Type())
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}
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})
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s.Run("column_timestamptz", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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now := time.Now().UTC()
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data := []time.Time{now, now.Add(time.Hour), now.Add(2 * time.Hour)}
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column := NewColumnTimestamptz(name, data)
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s.Equal(entity.FieldTypeTimestamptz, column.Type())
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s.Equal(name, column.Name())
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// verify data is converted to RFC3339Nano format
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expectedStrings := []string{
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data[0].Format(time.RFC3339Nano),
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data[1].Format(time.RFC3339Nano),
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data[2].Format(time.RFC3339Nano),
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}
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s.Equal(expectedStrings, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(expectedStrings, fd.GetScalars().GetStringData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnTimestampTzIsoString)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(expectedStrings, parsed.Data())
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s.Equal(entity.FieldTypeTimestamptz, parsed.Type())
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}
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})
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s.Run("column_timestamptz_iso_string", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := []string{
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"2024-01-01T00:00:00Z",
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"2024-06-15T12:30:45.123456789Z",
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"2024-12-31T23:59:59.999999999+08:00",
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}
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column := NewColumnTimestamptzIsoString(name, data)
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s.Equal(entity.FieldTypeTimestamptz, column.Type())
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s.Equal(name, column.Name())
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s.Equal(data, column.Data())
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fd := column.FieldData()
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s.Equal(name, fd.GetFieldName())
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s.Equal(data, fd.GetScalars().GetStringData().GetData())
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result, err := FieldDataColumn(fd, 0, -1)
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s.NoError(err)
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parsed, ok := result.(*ColumnTimestampTzIsoString)
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if s.True(ok) {
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s.Equal(name, parsed.Name())
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s.Equal(data, parsed.Data())
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s.Equal(entity.FieldTypeTimestamptz, parsed.Type())
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}
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})
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}
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func (s *ScalarSuite) TestSlice() {
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n := 100
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s.Run("column_bool", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]bool, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, rand.Int()%2 == 0)
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}
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column := NewColumnBool(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnBool)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_int8", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]int8, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, int8(rand.Intn(math.MaxInt8)))
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}
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column := NewColumnInt8(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnInt8)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_int16", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]int16, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, int16(rand.Intn(math.MaxInt16)))
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}
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column := NewColumnInt16(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnInt16)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_int32", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]int32, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, rand.Int31())
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}
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column := NewColumnInt32(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnInt32)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_int64", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]int64, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, rand.Int63())
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}
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column := NewColumnInt64(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnInt64)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_float", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]float32, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, rand.Float32())
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}
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column := NewColumnFloat(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnFloat)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_double", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]float64, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, rand.Float64())
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}
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column := NewColumnDouble(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnDouble)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_varchar", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]string, 0, n)
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for i := 0; i < 100; i++ {
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data = append(data, fmt.Sprintf("%d", rand.Int()))
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}
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column := NewColumnVarChar(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnVarChar)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_timestamptz", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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now := time.Now().UTC()
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timeData := make([]time.Time, 0, n)
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for i := 0; i < n; i++ {
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timeData = append(timeData, now.Add(time.Duration(i)*time.Hour))
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}
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column := NewColumnTimestamptz(name, timeData)
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data := column.Data()
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnTimestamptz)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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s.Run("column_timestamptz_iso_string", func() {
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name := fmt.Sprintf("field_%d", rand.Intn(1000))
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data := make([]string, 0, n)
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for i := 0; i < n; i++ {
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data = append(data, fmt.Sprintf("2024-01-%02dT00:00:00Z", (i%28)+1))
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}
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column := NewColumnTimestamptzIsoString(name, data)
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l := rand.Intn(n)
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sliced := column.Slice(0, l)
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slicedColumn, ok := sliced.(*ColumnTimestampTzIsoString)
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if s.True(ok) {
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s.Equal(column.Type(), slicedColumn.Type())
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s.Equal(data[:l], slicedColumn.Data())
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}
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})
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}
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func TestScalarColumn(t *testing.T) {
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suite.Run(t, new(ScalarSuite))
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}
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