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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