elasticsearch文档操作的方法有哪些
这篇文章主要介绍“elasticsearch文档操作的方法有哪些”,在日常操作中,相信很多人在elasticsearch文档操作的方法有哪些问题上存在疑惑,小编查阅了各式资料,整理出简单好用的操作方法,希望对大家解答”elasticsearch文档操作的方法有哪些”的疑惑有所帮助!接下来,请跟着小编一起来学习吧!
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文档
查找name=hnatao
的数据
rst, _ := client.Search().Index("user").Query(elastic.NewMatchQuery("name", "hnatao")).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[ { "_score": 1.3862942, "_index": "user", "_type": "_doc", "_id": "1", "_seq_no": null, "_primary_term": null, "_source": { "name": "hnatao", "age": 21, "score": 80 } } ]
查找 20 岁的 hnatao 的数据
q := elastic.NewBoolQuery().Must( elastic.NewMatchQuery("name", "hnatao"), elastic.NewMatchQuery("age", "20"), ) rst, _ := client.Search().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[]
查找 20 岁,21 岁的所有用户信息
q := elastic.NewRangeQuery("age").Gte("20").Lte("21") rst, _ := client.Search().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[ { "_score": 1, "_index": "user", "_type": "_doc", "_id": "1", "_seq_no": null, "_primary_term": null, "_source": { "name": "hnatao", "age": 21, "score": 80 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "5", "_seq_no": null, "_primary_term": null, "_source": { "name": "guofucheng", "age": 20, "score": 0 } } ]
查找大于 21 岁的所有用户信息
q := elastic.NewRangeQuery("age").Gte("21") rst, _ := client.Search().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[ { "_score": 1, "_index": "user", "_type": "_doc", "_id": "1", "_seq_no": null, "_primary_term": null, "_source": { "name": "hnatao", "age": 21, "score": 80 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "2", "_seq_no": null, "_primary_term": null, "_source": { "name": "lqt", "age": 22, "score": 90 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "3", "_seq_no": null, "_primary_term": null, "_source": { "name": "liudehua", "age": 23, "score": 85 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "4", "_seq_no": null, "_primary_term": null, "_source": { "name": "zhangxueyou", "age": 24, "score": 86 } } ]
查找有得分记录的用户
q := elastic.NewExistsQuery("score") rst, _ := client.Search().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[ { "_score": 1, "_index": "user", "_type": "_doc", "_id": "1", "_seq_no": null, "_primary_term": null, "_source": { "name": "hnatao", "age": 21, "score": 80 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "2", "_seq_no": null, "_primary_term": null, "_source": { "name": "lqt", "age": 22, "score": 90 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "3", "_seq_no": null, "_primary_term": null, "_source": { "name": "liudehua", "age": 23, "score": 85 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "4", "_seq_no": null, "_primary_term": null, "_source": { "name": "zhangxueyou", "age": 24, "score": 86 } }, { "_score": 1, "_index": "user", "_type": "_doc", "_id": "5", "_seq_no": null, "_primary_term": null, "_source": { "name": "guofucheng", "age": 20, "score": 0 } } ]
查找没有得分记录的用户
q := elastic.NewBoolQuery().MustNot(elastic.NewExistsQuery("score")) rst, _ := client.Search().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[]
20 岁用户总人数
q := elastic.NewTermQuery("age", "20") rst, _ := client.Count().Index("user").Query(q).Do(ctx) buf, _ := json.Marshal(rst) fmt.Println(string(buf))
返回
数字:1
用户的平均人数
q := elastic.NewAvgAggregation().Field("age") rst, _ := client.Search().Index("user").Aggregation("avg_age", q).Size(0).Do(ctx) fmt.Println(string(rst.Aggregations["avg_age"]))
返回
{ "value": 22.0 }
查找年龄最小的用户
rst, _ := client.Search().Index("user").Sort("age", true).Size(1).Do(ctx) buf, _ := json.Marshal(rst.Hits.Hits) fmt.Println(string(buf))
返回
[ { "_index": "user", "_type": "_doc", "_id": "5", "_seq_no": null, "_primary_term": null, "sort": [20], "_source": { "name": "guofucheng", "age": 20, "score": 0 } } ]
统计年龄的各个维度
agg := elastic.NewStatsAggregation().Field("age") rst, _ := client.Search().Index("user").Aggregation("stats_age", agg).Do(ctx) buf, _ := rst.Aggregations["stats_age"].MarshalJSON() fmt.Println(string(buf))
返回
{ "count": 5, "min": 20.0, "max": 24.0, "avg": 22.0, "sum": 110.0 }
统计年龄占比百分位
agg := elastic.NewPercentilesAggregation().Field("age") rst, _ := client.Search().Index("user").Aggregation("stats_age", agg).Do(ctx) buf, _ := rst.Aggregations["stats_age"].MarshalJSON() fmt.Println(string(buf))
返回
{ "values": { "1.0": 20.0, "5.0": 20.0, "25.0": 20.75, "50.0": 22.0, "75.0": 23.25, "95.0": 24.0, "99.0": 24.0 } }
查询每个年龄的平均分数,并按年龄从小到大排序
agg := elastic.NewTermsAggregation().Field("age"). SubAggregation("avg_score", elastic.NewAvgAggregation().Field("score")).OrderByKeyAsc() rst, _ := client.Search().Index("user").Aggregation("stats_age", agg).Do(ctx) buf, _ := rst.Aggregations["stats_age"].MarshalJSON() fmt.Println(string(buf))
返回
{ "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 20, "doc_count": 1, "avg_score": { "value": 0.0 } }, { "key": 21, "doc_count": 2, "avg_score": { "value": 85.0 } }, { "key": 22, "doc_count": 2, "avg_score": { "value": 85.5 } } ] }
查询每个年龄的平均分数,并按平均分数从大到小排序
agg := elastic.NewTermsAggregation().Field("age"). SubAggregation("avg_score", elastic.NewAvgAggregation().Field("score")).OrderByAggregation("avg_score", false) rst, _ := client.Search().Index("user").Aggregation("stats_age", agg).Do(ctx) buf, _ := rst.Aggregations["stats_age"].MarshalJSON() fmt.Println(string(buf))
返回
{ "doc_count_error_upper_bound": 0, "sum_other_doc_count": 0, "buckets": [ { "key": 22, "doc_count": 2, "avg_score": { "value": 85.5 } }, { "key": 21, "doc_count": 2, "avg_score": { "value": 85.0 } }, { "key": 20, "doc_count": 1, "avg_score": { "value": 0.0 } } ] }
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