Elasticsearch Update By Query详解

大叶子不小

3093人浏览 · 2024-02-22 16:07:29

大叶子不小 · 2024-02-22 16:07:29 发布

1. 使用场景
一般在以下几种情况时，我们需要重建索引：

索引的 Mappings 发生变更：字段类型更改，分词器及字典更新
索引的 Setting 发生变更：索引的主分片数发生改变
集群内，集群间需要做数据迁移
ElastiicSearch 的内置提供的 API

Update By Query : 在现有索引上重建
Reindex：在其他索引上重建索引
2. Update By Query
2.1 案例一：为索引增加子字段
改变 Mapping ，增加子字段，使用英文分词器
此时尝试对子字段进行查询
虽然有数据已经存在，但是没有返回结果

执行 Update By Query
尝试对 Multi-Fields 查询查询
返回结果

# 写入文档
PUT blogs/_doc/1
{
"content":"Hadoop is cool",
"keyword":"hadoop"
}
# 修改 Mapping，增加子字段，使用英文分词器
PUT blogs/_mapping
{
"properties" : {
"content" : {
"type" : "text",
"fields" : {
"english" : {
"type" : "text",
"analyzer":"english"
}
}
}
}
}

# 写入文档
PUT blogs/_doc/2
{
"content":"Elasticsearch rocks",
"keyword":"elasticsearch"
}

# 查询新写入文档
POST blogs/_search
{
"query": {
"match": {
"content.english": "Elasticsearch"
}
}
}

# 查询 Mapping 变更前写入的文档
POST blogs/_search
{
"query": {
"match": {
"content.english": "hadoop"
}
}
}

# Update所有文档
POST blogs/_update_by_query
{

}

2.2 案例二：更改已有字段类型的 Mappings
ES 不允许在原有 Mapping 上对字段类型进行修改
只能创建新的索引，并设定正确的字段类型，在重新导入数据

# 查询
GET blogs/_mapping

PUT blogs/_mapping
{
"properties" : {
"content" : {
"type" : "text",
"fields" : {
"english" : {
"type" : "text",
"analyzer" : "english"
}
}
},
"keyword" : {
"type" : "keyword"
}
}
}

返回输出：
{
"error": {
"root_cause": [
{
"type": "illegal_argument_exception",
"reason": "mapper [keyword] of different type, current_type [text], merged_type [keyword]"
}
],
"type": "illegal_argument_exception",
"reason": "mapper [keyword] of different type, current_type [text], merged_type [keyword]"
},
"status": 400
}

# 创建新的索引并且设定新的Mapping
PUT blogs_fix/
{
"mappings": {
"properties": {
"content": {
"type": "text",
"fields": {
"english": {
"type": "text",
"analyzer": "english"
}
}
},
"keyword": {
"type": "keyword"
}
}
}
}

# Reindx API
POST _reindex
{
"source": {
"index": "blogs"
},
"dest": {
"index": "blogs_fix"
}
}
返回输出：
{
"took" : 17,
"timed_out" : false,
"total" : 2,
"updated" : 0,
"created" : 2,
"deleted" : 0,
"batches" : 1,
"version_conflicts" : 0,
"noops" : 0,
"retries" : {
"bulk" : 0,
"search" : 0
},
"throttled_millis" : 0,
"requests_per_second" : -1.0,
"throttled_until_millis" : 0,
"failures" : [ ]
}

GET blogs_fix/_doc/1
返回输出：
{
"_index" : "blogs_fix",
"_type" : "_doc",
"_id" : "1",
"_version" : 1,
"_seq_no" : 0,
"_primary_term" : 1,
"found" : true,
"_source" : {
"content" : "Hadoop is cool",
"keyword" : "hadoop"
}
}

# 测试 Term Aggregation
POST blogs_fix/_search
{
"size": 0,
"aggs": {
"blog_keyword": {
"terms": {
"field": "keyword",
"size": 10
}
}
}
}

返回输出：
{
"took" : 4,
"timed_out" : false,
"_shards" : {
"total" : 1,
"successful" : 1,
"skipped" : 0,
"failed" : 0
},
"hits" : {
"total" : {
"value" : 2,
"relation" : "eq"
},
"max_score" : null,
"hits" : [ ]
},
"aggregations" : {
"blog_keyword" : {
"doc_count_error_upper_bound" : 0,
"sum_other_doc_count" : 0,
"buckets" : [
{
"key" : "elasticsearch",
"doc_count" : 1
},
{
"key" : "hadoop",
"doc_count" : 1
}
]
}
}
}
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