search_analyzer
编辑search_analyzer
编辑通常，应该在索引时和搜索时应用相同的分析器，以确保查询中的词项与倒排索引中的词项格式相同。
但是，有时在搜索时使用不同的分析器是有意义的，例如，当使用edge_ngram分词器进行自动完成，或者使用搜索时同义词时。
默认情况下，查询将使用字段映射中定义的analyzer，但是可以使用search_analyzer设置来覆盖它。
resp = client.indices.create(
index="my-index-000001",
settings={
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": 1,
"max_gram": 20
}
},
"analyzer": {
"autocomplete": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"autocomplete_filter"
]
}
}
}
},
mappings={
"properties": {
"text": {
"type": "text",
"analyzer": "autocomplete",
"search_analyzer": "standard"
}
}
},
)
print(resp)
resp1 = client.index(
index="my-index-000001",
id="1",
document={
"text": "Quick Brown Fox"
},
)
print(resp1)
resp2 = client.search(
index="my-index-000001",
query={
"match": {
"text": {
"query": "Quick Br",
"operator": "and"
}
}
},
)
print(resp2)
response = client.indices.create(
index: 'my-index-000001',
body: {
settings: {
analysis: {
filter: {
autocomplete_filter: {
type: 'edge_ngram',
min_gram: 1,
max_gram: 20
}
},
analyzer: {
autocomplete: {
type: 'custom',
tokenizer: 'standard',
filter: [
'lowercase',
'autocomplete_filter'
]
}
}
}
},
mappings: {
properties: {
text: {
type: 'text',
analyzer: 'autocomplete',
search_analyzer: 'standard'
}
}
}
}
)
puts response
response = client.index(
index: 'my-index-000001',
id: 1,
body: {
text: 'Quick Brown Fox'
}
)
puts response
response = client.search(
index: 'my-index-000001',
body: {
query: {
match: {
text: {
query: 'Quick Br',
operator: 'and'
}
}
}
}
)
puts response
const response = await client.indices.create({
index: "my-index-000001",
settings: {
analysis: {
filter: {
autocomplete_filter: {
type: "edge_ngram",
min_gram: 1,
max_gram: 20,
},
},
analyzer: {
autocomplete: {
type: "custom",
tokenizer: "standard",
filter: ["lowercase", "autocomplete_filter"],
},
},
},
},
mappings: {
properties: {
text: {
type: "text",
analyzer: "autocomplete",
search_analyzer: "standard",
},
},
},
});
console.log(response);
const response1 = await client.index({
index: "my-index-000001",
id: 1,
document: {
text: "Quick Brown Fox",
},
});
console.log(response1);
const response2 = await client.search({
index: "my-index-000001",
query: {
match: {
text: {
query: "Quick Br",
operator: "and",
},
},
},
});
console.log(response2);
PUT my-index-000001
{
"settings": {
"analysis": {
"filter": {
"autocomplete_filter": {
"type": "edge_ngram",
"min_gram": 1,
"max_gram": 20
}
},
"analyzer": {
"autocomplete": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"autocomplete_filter"
]
}
}
}
},
"mappings": {
"properties": {
"text": {
"type": "text",
"analyzer": "autocomplete",
"search_analyzer": "standard"
}
}
}
}
PUT my-index-000001/_doc/1
{
"text": "Quick Brown Fox"
}
GET my-index-000001/_search
{
"query": {
"match": {
"text": {
"query": "Quick Br",
"operator": "and"
}
}
}
}
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定义自定义 |
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此字段被索引为词项：[ |
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该查询搜索以下两个词项：[ |
有关此示例的完整说明，请参见索引时即时搜索。
可以使用更新映射 API 在现有字段上更新search_analyzer设置。请注意，要执行此操作，需要在更新的字段定义中重复任何现有的“analyzer”设置和“type”。