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elasticsearch文档操作的方法有哪些

发表于：2024-10-21 作者：千家信息网编辑

千家信息网最后更新 2024年10月21日，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

千家信息网最后更新 2024年10月21日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！

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))

[    {        "_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))

[]

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))

[    {        "_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))

[    {        "_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))

[    {        "_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))

[]

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))

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"]))

{ "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))

[    {        "_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))

{    "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))

{    "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))

{    "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))

{    "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 } }    ]}

到此，关于"elasticsearch文档操作的方法有哪些"的学习就结束了，希望能够解决大家的疑惑。理论与实践的搭配能更好的帮助大家学习，快去试试吧！若想继续学习更多相关知识，请继续关注网站，小编会继续努力为大家带来更多实用的文章！

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