k-NN 查询解释
3.0 版本引入
您可以提供 explain 参数来了解 knn 查询中分数是如何计算、归一化和组合的。启用后，它会提供每个搜索结果评分过程的详细信息。这包括显示所使用的分数归一化技术、不同分数如何组合以及单个子查询分数的计算。这种全面的洞察力使您更容易理解和优化您的 knn 查询结果。有关 explain 的更多信息，请参阅 Explain API。
就资源和时间而言，explain 是一种开销较大的操作。对于生产集群，我们建议仅在故障排除时谨慎使用。
在使用以下语法对 Faiss 引擎运行完整的 knn 查询时，可以在 URL 中提供 explain 参数：
GET <index>/_search?explain=true
POST <index>/_search?explain=true
对于所有类型的 Lucene 引擎的 k-NN 搜索，explain 不会像 Faiss 引擎那样返回详细的解释。
在 Faiss 引擎下，explain 参数适用于以下类型的 k-NN 搜索：
- 近似 k-NN 搜索
- 使用精确搜索的近似 k-NN 搜索
- 基于磁盘的搜索
- 带高效过滤的 k-NN 搜索
- 径向搜索
- 带
term查询的 k-NN 搜索
对于带有嵌套字段的 k-NN 搜索，explain 不会像其他搜索那样返回详细的解释。
您可以将 explain 参数作为查询参数提供
GET my-knn-index/_search?explain=true
{
"query": {
"knn": {
"my_vector": {
"vector": [2, 3, 5, 7],
"k": 2
}
}
}
}
或者，您可以在请求体中提供 explain 参数
GET my-knn-index/_search
{
"query": {
"knn": {
"my_vector": {
"vector": [2, 3, 5, 7],
"k": 2
}
}
},
"explain": true
}
示例：近似 k-NN 搜索
示例响应
{
"took": 216038,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 88.4,
"hits": [
{
"_shard": "[my-knn-index-1][0]",
"_node": "VHcyav6OTsmXdpsttX2Yug",
"_index": "my-knn-index-1",
"_id": "5",
"_score": 88.4,
"_source": {
"my_vector1": [
2.5,
3.5,
5.5,
7.4
],
"price": 8.9
},
"_explanation": {
"value": 88.4,
"description": "the type of knn search executed was Approximate-NN",
"details": [
{
"value": 88.4,
"description": "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = innerproduct where score is computed as `-rawScore + 1` from:",
"details": [
{
"value": -87.4,
"description": "rawScore, returned from FAISS library",
"details": []
}
]
}
]
}
},
{
"_shard": "[my-knn-index-1][0]",
"_node": "VHcyav6OTsmXdpsttX2Yug",
"_index": "my-knn-index-1",
"_id": "2",
"_score": 84.7,
"_source": {
"my_vector1": [
2.5,
3.5,
5.6,
6.7
],
"price": 5.5
},
"_explanation": {
"value": 84.7,
"description": "the type of knn search executed was Approximate-NN",
"details": [
{
"value": 84.7,
"description": "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = innerproduct where score is computed as `-rawScore + 1` from:",
"details": [
{
"value": -83.7,
"description": "rawScore, returned from FAISS library",
"details": []
}
]
}
]
}
}
]
}
}
示例：带精确搜索的近似 k-NN 搜索
示例响应
{
"took": 87,
"timed_out": false,
"_shards": {
"total": 1,
"successful": 1,
"skipped": 0,
"failed": 0
},
"hits": {
"total": {
"value": 2,
"relation": "eq"
},
"max_score": 84.7,
"hits": [
{
"_shard": "[my-knn-index-1][0]",
"_node": "MQVux8dZRWeznuEYKhMq0Q",
"_index": "my-knn-index-1",
"_id": "7",
"_score": 84.7,
"_source": {
"my_vector2": [
2.5,
3.5,
5.6,
6.7
],
"price": 5.5
},
"_explanation": {
"value": 84.7,
"description": "the type of knn search executed was Approximate-NN",
"details": [
{
"value": 84.7,
"description": "the type of knn search executed at leaf was Exact with spaceType = INNER_PRODUCT, vectorDataType = FLOAT, queryVector = [2.0, 3.0, 5.0, 6.0]",
"details": []
}
]
}
},
{
"_shard": "[my-knn-index-1][0]",
"_node": "MQVux8dZRWeznuEYKhMq0Q",
"_index": "my-knn-index-1",
"_id": "8",
"_score": 82.2,
"_source": {
"my_vector2": [
4.5,
5.5,
6.7,
3.7
],
"price": 4.4
},
"_explanation": {
"value": 82.2,
"description": "the type of knn search executed was Approximate-NN",
"details": [
{
"value": 82.2,
"description": "the type of knn search executed at leaf was Exact with spaceType = INNER_PRODUCT, vectorDataType = FLOAT, queryVector = [2.0, 3.0, 5.0, 6.0]",
"details": []
}
]
}
}
]
}
示例：基于磁盘的搜索
示例响应
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 1,
"relation" : "eq"
},
"max_score" : 381.0,
"hits" : [
{
"_shard" : "[my-vector-index][0]",
"_node" : "pLaiqZftTX-MVSKdQSu7ow",
"_index" : "my-vector-index",
"_id" : "9",
"_score" : 381.0,
"_source" : {
"my_vector_field" : [
9.5,
9.5,
9.5,
9.5,
9.5,
9.5,
9.5,
9.5
],
"price" : 8.9
},
"_explanation" : {
"value" : 381.0,
"description" : "the type of knn search executed was Disk-based and the first pass k was 100 with vector dimension of 8, over sampling factor of 5.0, shard level rescoring enabled",
"details" : [
{
"value" : 381.0,
"description" : "the type of knn search executed at leaf was Approximate-NN with spaceType = HAMMING, vectorDataType = FLOAT, queryVector = [1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.5]",
"details" : [ ]
}
]
}
}
]
}
}
示例：带高效过滤的 k-NN 搜索
示例响应
{
"took" : 51,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.8620689,
"hits" : [
{
"_shard" : "[products-shirts][0]",
"_node" : "9epk8WoFT8yvnUI0tAaJgQ",
"_index" : "products-shirts",
"_id" : "8",
"_score" : 0.8620689,
"_source" : {
"item_vector" : [
2.4,
4.0,
3.0
],
"size" : "small",
"rating" : 8
},
"_explanation" : {
"value" : 0.8620689,
"description" : "the type of knn search executed was Approximate-NN",
"details" : [
{
"value" : 0.8620689,
"description" : "the type of knn search executed at leaf was Exact since filteredIds = 2 is less than or equal to K = 10 with spaceType = L2, vectorDataType = FLOAT, queryVector = [2.0, 4.0, 3.0]",
"details" : [ ]
}
]
}
},
{
"_shard" : "[products-shirts][0]",
"_node" : "9epk8WoFT8yvnUI0tAaJgQ",
"_index" : "products-shirts",
"_id" : "6",
"_score" : 0.029691212,
"_source" : {
"item_vector" : [
6.4,
3.4,
6.6
],
"size" : "small",
"rating" : 9
},
"_explanation" : {
"value" : 0.029691212,
"description" : "the type of knn search executed was Approximate-NN",
"details" : [
{
"value" : 0.029691212,
"description" : "the type of knn search executed at leaf was Exact since filteredIds = 2 is less than or equal to K = 10 with spaceType = L2, vectorDataType = FLOAT, queryVector = [2.0, 4.0, 3.0]",
"details" : [ ]
}
]
}
}
]
}
}
示例：径向搜索
GET my-knn-index/_search?explain=true
{
"query": {
"knn": {
"my_vector": {
"vector": [7.1, 8.3],
"max_distance": 2
}
}
}
}
示例响应
{
"took" : 376529,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 0.98039204,
"hits" : [
{
"_shard" : "[knn-index-test][0]",
"_node" : "c9b4aPe4QGO8eOtb8P5D3g",
"_index" : "knn-index-test",
"_id" : "1",
"_score" : 0.98039204,
"_source" : {
"my_vector" : [
7.0,
8.2
],
"price" : 4.4
},
"_explanation" : {
"value" : 0.98039204,
"description" : "the type of knn search executed was Radial with the radius of 2.0",
"details" : [
{
"value" : 0.98039204,
"description" : "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = l2 where score is computed as `1 / (1 + rawScore)` from:",
"details" : [
{
"value" : 0.020000057,
"description" : "rawScore, returned from FAISS library",
"details" : [ ]
}
]
}
]
}
},
{
"_shard" : "[knn-index-test][0]",
"_node" : "c9b4aPe4QGO8eOtb8P5D3g",
"_index" : "knn-index-test",
"_id" : "3",
"_score" : 0.9615384,
"_source" : {
"my_vector" : [
7.3,
8.3
],
"price" : 19.1
},
"_explanation" : {
"value" : 0.9615384,
"description" : "the type of knn search executed was Radial with the radius of 2.0",
"details" : [
{
"value" : 0.9615384,
"description" : "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = l2 where score is computed as `1 / (1 + rawScore)` from:",
"details" : [
{
"value" : 0.040000115,
"description" : "rawScore, returned from FAISS library",
"details" : [ ]
}
]
}
]
}
}
]
}
}
示例：带 term 查询的 k-NN 搜索
GET my-knn-index/_search?explain=true
{
"query": {
"bool": {
"should": [
{
"knn": {
"my_vector2": { // vector field name
"vector": [2, 3, 5, 6],
"k": 2
}
}
},
{
"term": {
"price": "4.4"
}
}
]
}
}
}
示例响应
{
"took" : 51,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : 84.7,
"hits" : [
{
"_shard" : "[my-knn-index-1][0]",
"_node" : "c9b4aPe4QGO8eOtb8P5D3g",
"_index" : "my-knn-index-1",
"_id" : "7",
"_score" : 84.7,
"_source" : {
"my_vector2" : [
2.5,
3.5,
5.6,
6.7
],
"price" : 5.5
},
"_explanation" : {
"value" : 84.7,
"description" : "sum of:",
"details" : [
{
"value" : 84.7,
"description" : "the type of knn search executed was Approximate-NN",
"details" : [
{
"value" : 84.7,
"description" : "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = innerproduct where score is computed as `-rawScore + 1` from:",
"details" : [
{
"value" : -83.7,
"description" : "rawScore, returned from FAISS library",
"details" : [ ]
}
]
}
]
}
]
}
},
{
"_shard" : "[my-knn-index-1][0]",
"_node" : "c9b4aPe4QGO8eOtb8P5D3g",
"_index" : "my-knn-index-1",
"_id" : "8",
"_score" : 83.2,
"_source" : {
"my_vector2" : [
4.5,
5.5,
6.7,
3.7
],
"price" : 4.4
},
"_explanation" : {
"value" : 83.2,
"description" : "sum of:",
"details" : [
{
"value" : 82.2,
"description" : "the type of knn search executed was Approximate-NN",
"details" : [
{
"value" : 82.2,
"description" : "the type of knn search executed at leaf was Approximate-NN with vectorDataType = FLOAT, spaceType = innerproduct where score is computed as `-rawScore + 1` from:",
"details" : [
{
"value" : -81.2,
"description" : "rawScore, returned from FAISS library",
"details" : [ ]
}
]
}
]
},
{
"value" : 1.0,
"description" : "price:[1082969293 TO 1082969293]",
"details" : [ ]
}
]
}
}
]
}
}
响应正文字段
| 字段 | 描述 |
|---|---|
解释 | explanation 对象包含以下字段：- value：包含计算结果。- description：解释执行了哪种类型的计算。对于分数归一化，description 字段中的信息包括用于归一化或组合的技术以及相应的分数。- details：显示执行的任何子计算。 |