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))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 } }
]
}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，请继续关注天达云网站，小编会继续努力为大家带来更多实用的文章！