排序特征字段类型
编辑排序特征字段类型
编辑rank_features 字段可以索引数值特征向量，以便稍后在查询中使用 rank_feature 查询来提升文档的相关性。
它类似于 rank_feature 数据类型，但当特征列表稀疏时更适合使用，这样为每个特征在映射中添加一个字段是不合理的。
resp = client.indices.create(
index="my-index-000001",
mappings={
"properties": {
"topics": {
"type": "rank_features"
},
"negative_reviews": {
"type": "rank_features",
"positive_score_impact": False
}
}
},
)
print(resp)
resp1 = client.index(
index="my-index-000001",
id="1",
document={
"topics": {
"politics": 20,
"economics": 50.8
},
"negative_reviews": {
"1star": 10,
"2star": 100
}
},
)
print(resp1)
resp2 = client.index(
index="my-index-000001",
id="2",
document={
"topics": {
"politics": 5.2,
"sports": 80.1
},
"negative_reviews": {
"1star": 1,
"2star": 10
}
},
)
print(resp2)
resp3 = client.search(
index="my-index-000001",
query={
"rank_feature": {
"field": "topics.politics"
}
},
)
print(resp3)
resp4 = client.search(
index="my-index-000001",
query={
"rank_feature": {
"field": "negative_reviews.1star"
}
},
)
print(resp4)
resp5 = client.search(
index="my-index-000001",
query={
"term": {
"topics": "economics"
}
},
)
print(resp5)
const response = await client.indices.create({
index: "my-index-000001",
mappings: {
properties: {
topics: {
type: "rank_features",
},
negative_reviews: {
type: "rank_features",
positive_score_impact: false,
},
},
},
});
console.log(response);
const response1 = await client.index({
index: "my-index-000001",
id: 1,
document: {
topics: {
politics: 20,
economics: 50.8,
},
negative_reviews: {
"1star": 10,
"2star": 100,
},
},
});
console.log(response1);
const response2 = await client.index({
index: "my-index-000001",
id: 2,
document: {
topics: {
politics: 5.2,
sports: 80.1,
},
negative_reviews: {
"1star": 1,
"2star": 10,
},
},
});
console.log(response2);
const response3 = await client.search({
index: "my-index-000001",
query: {
rank_feature: {
field: "topics.politics",
},
},
});
console.log(response3);
const response4 = await client.search({
index: "my-index-000001",
query: {
rank_feature: {
field: "negative_reviews.1star",
},
},
});
console.log(response4);
const response5 = await client.search({
index: "my-index-000001",
query: {
term: {
topics: "economics",
},
},
});
console.log(response5);
PUT my-index-000001
{
"mappings": {
"properties": {
"topics": {
"type": "rank_features"
},
"negative_reviews" : {
"type": "rank_features",
"positive_score_impact": false
}
}
}
}
PUT my-index-000001/_doc/1
{
"topics": {
"politics": 20,
"economics": 50.8
},
"negative_reviews": {
"1star": 10,
"2star": 100
}
}
PUT my-index-000001/_doc/2
{
"topics": {
"politics": 5.2,
"sports": 80.1
},
"negative_reviews": {
"1star": 1,
"2star": 10
}
}
GET my-index-000001/_search
{
"query": {
"rank_feature": {
"field": "topics.politics"
}
}
}
GET my-index-000001/_search
{
"query": {
"rank_feature": {
"field": "negative_reviews.1star"
}
}
}
GET my-index-000001/_search
{
"query": {
"term": {
"topics": "economics"
}
}
}
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排序特征字段必须使用 |
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与分数负相关的排序特征需要声明它 |
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排序特征字段必须是具有字符串键和严格正数值的哈希 |
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此查询根据文档与 “政治” 主题的相关程度对其进行排序。 |
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此查询根据文档收到的 “1星” 评价数量的反比对其进行排序。 |
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此查询返回在 “topics” 字段中存储 “economics” 特征的文档。 |
rank_features 字段仅支持单值特征和严格正值。多值字段和零值或负值将被拒绝。
rank_features 字段不支持排序或聚合，并且只能使用 rank_feature 或 term 查询进行查询。
对 rank_features 字段的 term 查询是通过将匹配的存储特征值乘以提供的 boost 来评分的。
rank_features 字段仅保留 9 个有效位用于精度，这转化为大约 0.4% 的相对误差。
与分数负相关的排序特征应将 positive_score_impact 设置为 false（默认为 true）。这将由 rank_feature 查询使用，以修改评分公式，使得分数随着特征值的增加而减少，而不是增加。