elasticsearc 参考资料
_source 和store
http://stackoverflow.com/questions/17103047/why-do-i-need-storeyes-in-elasticsearch
You usually send a field to elasticsearch because you either want to search on it, or retrieve it. But it's true that if you don't store the field explicitly and you don't disable the source you can still retrieve the field using the _source
. This means that in some cases it might actually make sense to have a field that is not indexed nor stored.
When you store a field, that's done in the underlying lucene. Lucene is an inverted index, that allows for fast full-text search and gives back document ids given text queries. Beyond the inverted index Lucene has some kind of storage where the field values can be stored in order to be retrieved given a document id. You usually store in lucene the fields that you want to return as search results. Elasticsearch doesn't require to store every field that you want to return because it always stores by default every document that you send to it, thus it's always able to return everything you sent to it as search result.
In just a few cases it might be useful to store fields explicitly in lucene: when the _source
field is disabled, or when we want to avoid parsing it, even if the parsing is done automatically by elasticsearch. Keep in mind though that retrieving many stored fields from lucene might require one disk seek per field while with retrieving only the _source
from lucene and parsing it in order to retrieve the needed fields is just a single disk seek and just faster in most of the cases.
如果字段的属性store 被设置为no,也可以通过_source获取文档,然后解析出该字段的内容,但是前提是_source的属性"enabled": true。
Aggregation
http://chrissimpson.co.uk/elasticsearch-aggregations-overview.html
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations.html
https://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-bucket-terms-aggregation.html#search-aggregations-bucket-terms-aggregation-order
Top Hit Aggregation
https://www.elastic.co/guide/en/elasticsearch/reference/1.6/search-aggregations-metrics-top-hits-aggregation.html
Shards and replicas
一个shard 实际上是一个lucence index
主分片可以接受index,副本不行;但是查询都可以
http://blog.trifork.com/2014/01/07/elasticsearch-how-many-shards/
Aggregation
http://www.elasticsearch.org/guide/en/elasticsearch/reference/current/search-aggregations.html
Aggregation不准确
Mapping
http://www.elasticsearch.org/guide/en/elasticsearch/guide/current/mapping-intro.html
每个文档在索引中都有一个类型,每个类型有自己的mapping或者叫模型定义。mapping定义类型中的字段,每个字段的数据类型,以及在弹性搜索中字段是被如何处理的。mapping也用来配置与类型相关的元数据。
弹性搜索支持如下的简单字段数据类型:
- String:
string
- Whole number:
byte
,short
,integer
,long
- Floating-point:
float
,double
- Boolean:
boolean
- Date:
date
当你索引一个包含新字段的文档时,弹性搜索根据JSON的基本数据类型来猜测文档字段的数据类型。具体的对应关系如下:
JSON type |
Field type |
Boolean: |
|
Whole number: |
|
Floating point: |
|
String, valid date: |
|
String: |
|
analyzed
- 先分词,再索引。
not_analyzed
- 直接索引,所以它是可搜索的,但是用全值建索引,不分词。
no
- 不建索引,所以该字段是不可搜索的。
String类型的属性,默认值是analyzed,所以想要用原始值建索引,需要设置为 not_analyzed。
其他类型(例如long,double,date)也有index属性,但是备选值只有no和not_analyzed,这些值永远不会被分词