如何配置Elasticsearch以在单词的最后一个字符（而不是中间）找到子字符串？ [英] How do I configure Elasticsearch to find substrings at the beginning OR at the end of a word (but not in middle)?
问题描述
我知道有边缘n克标记器，但一个分析器只能有一个标记器和边缘n-gram可以是前面还是后面（但不能同时两个）。
如果我理解正确，应用两个版本的过滤器（正面和背面）分析器，那么我也找不到，因为这两个过滤器都需要返回true，不是吗？因为堆栈不会在单词的结尾，所以后边缘格式过滤器将返回false，并且将找不到stackoverflow一词。
那么，如何配置我的分析器来找到一个单词的结尾或开头的子串，而不是在中间？
可以做的是定义两个分析器，一个用于在字符串开始匹配，另一个用于在字符串末尾进行匹配。在下面的索引设置中，我命名前一个 prefix_edge_ngram_analyzer ，后一个 suffix_edge_ngram_analyzer 。这两个分析器可以应用于多字段字符串字段到 text.prefix 子字段，分别到 text.suffix string field。
{
settings：{
analysis
analyzer：{
prefix_edge_ngram_analyzer：{
tokenizer：prefix_edge_ngram_tokenizer，
filter：[smallcase]
}，
suffix_edge_ngram_analyzer：{
tokenizer：keyword，
filter：[smallcase，reverse，suffix_edge_ngram_filter，reverse]
}
}，
tokenizer：{
prefix_edge_ngram_tokenizer：{
type：edgeNGram，
min_gram：2，
max_gram：25
}
}，
filter：{
suffix_edge_ngram_filter：{
type：edgeNGram
min_gram：2，
max_gram：25
}
}
}
}，
mappings：{
test_type：{
properties：{
text ：{
type：string，
fields：{
前缀：{
type：string，
分析器：prefix_edge_ngram_analyzer
}，
后缀：{
type：string，
analyzer：suffix_edge_ngram_analyzer
}
}
}
}
}
}
}
然后让我们索引以下测试文档：
PUT test_index / test_type / 1
{text：stackoverflow}
然后我们可以通过前缀或后缀使用以下查询：
＃input为stack=> 1个结果
GET test_index / test_type / _search？q = text.prefix：stack或text.suffix：stack
＃input为flow=> 1个结果
GET test_index / test_type / _search？q = text.prefix：flow OR text.suffix：flow
＃input是ackov=> 0结果
GET test_index / test_type / _search？q = text.prefix：ackov或text.suffix：ackov
使用查询DSL查询的另一种方法：
POST test_index / test_type / _search
{
query：{
multi_match：{
query：stack，
fields：[text。*]
}
}
}
更新
如果您已经有一个字符串字段，则可以将其升级到多字段，并使用其分析器创建两个必需的子字段。执行此操作的方法是按顺序执行此操作：
-
关闭索引以创建分析器
POST test_index / _close
-
更新索引设置
PUT test_index / _settings
{
分析：{
analyzer：{
prefix_edge_ngram_analyzer：{
tokenizer：prefix_edge_ngram_tokenizer，
filter：[smallcase]
}
suffix_edge_ngram_analyzer：{
tokenizer：keyword，
filter：[smallcase，reverse，suffix_edge_ngram_filter
$ b}，
tokenizer：{
prefix_edge_ngram_tokenizer：{
type：edgeNGram，
min_gram：2 ，
max_gram：25
}
}，
过滤器：{
suffix_edge_ngram_filter：{
type edgeNGram，
min_gram：2，
max_gram：25
}
}
}
}
-
重新打开您的索引
POST test_index / _open
-
最后，更新文本字段的映射
PUT test_index / _mapping / test_type
{
properties：{
text：{
type：string，
fields：{
b $ btype：string，
analyzer：prefix_edge_ngram_analyzer
}，
suffix：{
type：string b $ banalyzer：suffix_edge_ngram_analyzer
}
}
}
}
}
-
您仍然需要重新索引所有文档，以便新的子字段
text.prefix和text.suffix进行填充和分析。
I'm starting to learn Elasticsearch and now I am trying to write my first analyser configuration. What I want to achieve is that substrings are found if they are at the beginning or ending of a word. If I have the word "stackoverflow" and I search for "stack" I want to find it and when I search for "flow" I want to find it, but I do not want to find it when searching for "ackov" (in my use case this would not make sense).
I know there is the "Edge n gram tokenizer", but one analyser can only have one tokenizer and the edge n-gram can either be front or back (but not both at the same time).
And if I understood correctly, applying both version of the "Edge ngram filter" (front and back) to the analyzer, then I would not find either, because both filters need to return true, isn't it? Because "stack" wouldn't be in the ending of the word, so the back edge n gram filter would return false and the word "stackoverflow" would not be found.
So, how do I configure my analyzer to find substrings either in the end or in the beginning of a word, but not in the middle?
What can be done is to define two analyzers, one for matching at the start of a string and another to match at the end of a string. In the index settings below, I named the former one prefix_edge_ngram_analyzer and the latter one suffix_edge_ngram_analyzer. Those two analyzers can be applied to a multi-field string field to the text.prefix sub-field, respectively to the text.suffix string field.
{
"settings": {
"analysis": {
"analyzer": {
"prefix_edge_ngram_analyzer": {
"tokenizer": "prefix_edge_ngram_tokenizer",
"filter": ["lowercase"]
},
"suffix_edge_ngram_analyzer": {
"tokenizer": "keyword",
"filter" : ["lowercase","reverse","suffix_edge_ngram_filter","reverse"]
}
},
"tokenizer": {
"prefix_edge_ngram_tokenizer": {
"type": "edgeNGram",
"min_gram": "2",
"max_gram": "25"
}
},
"filter": {
"suffix_edge_ngram_filter": {
"type": "edgeNGram",
"min_gram": 2,
"max_gram": 25
}
}
}
},
"mappings": {
"test_type": {
"properties": {
"text": {
"type": "string",
"fields": {
"prefix": {
"type": "string",
"analyzer": "prefix_edge_ngram_analyzer"
},
"suffix": {
"type": "string",
"analyzer": "suffix_edge_ngram_analyzer"
}
}
}
}
}
}
}
Then let's say we index the following test document:
PUT test_index/test_type/1
{ "text": "stackoverflow" }
We can then search either by prefix or suffix using the following queries:
# input is "stack" => 1 result
GET test_index/test_type/_search?q=text.prefix:stack OR text.suffix:stack
# input is "flow" => 1 result
GET test_index/test_type/_search?q=text.prefix:flow OR text.suffix:flow
# input is "ackov" => 0 result
GET test_index/test_type/_search?q=text.prefix:ackov OR text.suffix:ackov
Another way to query with the query DSL:
POST test_index/test_type/_search
{
"query": {
"multi_match": {
"query": "stack",
"fields": [ "text.*" ]
}
}
}
UPDATE
If you already have a string field, you can "upgrade" it to a multi-field and create the two required sub-fields with their analyzers. The way to do this would be to do this in order:
Close your index in order to create the analyzers
POST test_index/_closeUpdate the index settings
PUT test_index/_settings { "analysis": { "analyzer": { "prefix_edge_ngram_analyzer": { "tokenizer": "prefix_edge_ngram_tokenizer", "filter": ["lowercase"] }, "suffix_edge_ngram_analyzer": { "tokenizer": "keyword", "filter" : ["lowercase","reverse","suffix_edge_ngram_filter","reverse"] } }, "tokenizer": { "prefix_edge_ngram_tokenizer": { "type": "edgeNGram", "min_gram": "2", "max_gram": "25" } }, "filter": { "suffix_edge_ngram_filter": { "type": "edgeNGram", "min_gram": 2, "max_gram": 25 } } } }Re-open your index
POST test_index/_openFinally, update the mapping of your text field
PUT test_index/_mapping/test_type { "properties": { "text": { "type": "string", "fields": { "prefix": { "type": "string", "analyzer": "prefix_edge_ngram_analyzer" }, "suffix": { "type": "string", "analyzer": "suffix_edge_ngram_analyzer" } } } } }You still need to re-index all your documents in order for the new sub-fields
text.prefixandtext.suffixto be populated and analyzed.
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