索引信息：
image.png
{
"version": 31,
"mapping_version": 4,
"settings_version": 3,
"aliases_version": 3,
"routing_num_shards": 30,
"state": "open",
"settings": {
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"limit": "2000"
}
},
"refresh_interval": "1s",
"translog": {
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"durability": "request"
},
"provided_name": "",
"query": {
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]
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"creation_date": "1676671594061",
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"default": {
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}
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"priority": "100",
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"uuid": "B5nJu3SMTCqO4M6_nQ89wA",
"version": {
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},
"lifecycle": {
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"indexing_complete": "true"
},
"codec": "best_compression",
"routing": {
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}
},
"number_of_shards": "3"
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},
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"match": "message_full"
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{
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{
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{
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{
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{
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{
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{
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{
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{
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{
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{
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{
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"type": "scaled_float"
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{
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}
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{
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}
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{
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}
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"server": {
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"ip": {
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"domain": {
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"name": {
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"id": {
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"email": {
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"hash": {
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}
}
}
}
},
"mac": {
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"packets": {
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}
}
},
"agent": {
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"name": {
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"type": {
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"version": {
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}
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"log": {
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"level": {
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"logger": {
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}
},
"view spans": {
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"type": "keyword"
},
"destination": {
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},
"region_iso_code": {
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"type": "keyword"
},
"city_name": {
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"country_iso_code": {
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"country_name": {
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"name": {
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},
"location": {
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"region_name": {
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"type": "keyword"
}
}
},
"nat": {
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},
"ip": {
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}
}
},
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"organization": {
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}
}
}
}
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"user": {
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image.png
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}
Elasticsearch是一个分布式搜索和分析引擎，分片是它的核心概念之一。简单来说，分片是将数据拆分成更小的部分，以便在不同的节点上进行存储和处理，从而提高系统的性能和可扩展性。
在Elasticsearch中，每个索引都可以被分成多个分片，这些分片可以分布在不同的节点上。每个分片都是一个完整的Lucene索引，可以独立地进行搜索和索引操作。当一个查询被发送到Elasticsearch集群时，查询将被分发到每个相关分片上，分片返回结果并汇总到一个单一的结果集中。
分片对于Elasticsearch的可扩展性非常重要。当需要处理更大的数据集时，可以通过增加节点和分片来提高系统的性能和吞吐量。但是，分片的过多也会带来一些问题，如增加了复杂性和管理成本，以及可能会导致分片之间的数据不一致性。因此，在设计分片时，需要权衡系统的需求和限制，以确保系统的可靠性和性能。