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DQL数据查询(旧版)



POST /api/v1/df/query_data

概述

DQL数据查询

Query 请求参数

参数名 类型 必选 说明
body string dql查询query结构体
允许为空: False
queries_body string dql查询query结构体(2023-08-11日下架该参数)
允许为空: False
search_after string 分页查询请求参数(2023-08-11日下架该参数)
允许为空: False

参数补充说明

查询说明


1、 查询字符串 元素字段说明

参数名 type 必选 说明
body string Y 查询请求体
queries_body[*] string (旧版参数,2023-08-10 日下架) 查询列表
search_after string (旧版参数,2023-08-10 日下架, 新版参数位置挪移至 query 结构体中) 查询分页数据. 首次查询默认为[], 需要查询更多分页数据时,将上次查询结果中的search_after字段加上,用于查询后续数据

2、 body 中 JSON结构参数说明

参数名 type 必选 说明
queries array Y 多命令查询,其内容为 query 对象组成的列表
fieldTagDescNeeded boolean 是否需要field 或者tag描述信息

3、 queries[*]成员参数结构说明

参数名 type 必选 说明
qtype string Y 查询语句的类型
dql: 表示dql类型查询语句;
promql: 表示 PromQl类型查询语句
query json Y 查询结构
query.q string 与 qtype 类型保持一致的 查询语句,例如 dql 或者 promql 查询语句
query.highlight boolean 是否显示高亮数据
query.timeRange array 时间范围的时间戳列表
query.disableMultipleField bool 是否打开单列模式,默认为 true
query.showLabel bool 是否显示对象的lables,默认无
query.funcList array 再次聚合修饰dql返回值,注意 disableMultipleField=Flse时, 当前参数无效
query.slimit integer 时间线分组大小,只针对指标查询有效
query.soffset integer 时间线分组偏移量
query.limit integer 分页大小
query.offset integer 分页偏移量
query.orderby array 排序列表,{fieldName:method} , 注意指标集查询的排序只支持 fieldName=time; method in ["desc", "asc"];注意指标集查询的排序只支持 fieldName=time
query.density string 响应的点密度, 优先级小于 autoDensity 且大于 dql语句中设置的密度
query.interval integer 单位是秒,时间分片间隔,用于计算响应点数;计算出的点数小于等于density=high时的点数,则有效,否则无效
query.search_after array 分页标记, 由当前接口返回的分页标记,用于下一次请求时传入
query.maxPointCount integer 最大点数
query.workspaceUUID string 要查询工作空间的uuid
query.workspaceUUIDs array 要查询工作空间的uuids, 优先级 高于 query.workspaceUUID.
query.output_format string lineprotocol: 行协议输出,默认不填的话,默认保持现有输出格式不变
query.cursor_time integer 分段查询阀值: 第一次分段查询时,需要把 cursor_time 设置为 end_time;之后的分段查询,需要把 cursor_time 设置为响应中的 next_cursor_time
query.disable_sampling bool 采样禁用开关, 默认值为 false

4、 响应点密度density 参数值说明

可选值 说明
lower 较低,60个点
low 低,180个点
medium 中等,360个点
high 低,720个点
  • 注意点密度参数的优先级,最大密度density[high] * maxPointCount > interval > density > dql语句中的控制参数

5、 常见查询说明

请求例子

curl 'https://openapi.guance.com/api/v1/df/query_data?body=\{%22queries%22:\[\{%22uuid%22:%2205ea25f0-2fa3-11ee-aa03-57233270ef0c%22,%22qtype%22:%22dql%22,%22query%22:\{%22q%22:%22L::re(`.*`):(`*`)\{+`index`+IN+\[%27default%27\]+\}%22,%22highlight%22:true,%22limit%22:50,%22orderby%22:\[\{%22time%22:%22desc%22\}\],%22_funcList%22:\[\],%22funcList%22:\[\],%22disableMultipleField%22:false,%22align_time%22:false,%22is_optimized%22:true,%22offset%22:0,%22search_after%22:\[1690808645037,538070,%22L_1690808645037_cj3r2itnel8fnfu5tlag%22\],%22timeRange%22:\[1690807857000,1690808757999\],%22tz%22:%22Asia/Shanghai%22\}\}\],%22expensiveQueryCheck%22:true\}' \
-H 'DF-API-KEY: <DF-API-KEY>' \
--compressed

响应

{
    "code": 200,
    "content": {
        "data": [
            {
                "AsyncTaskPayload": null,
                "async_id": "",
                "column_names": [
                    "container_id",
                    "source",
                    "filepath",
                    "image",
                    "index",
                    "df_metering_size",
                    "__namespace",
                    "host",
                    "log_read_offset",
                    "__docid",
                    "filename",
                    "service",
                    "image_name",
                    "image_short_name",
                    "image_tag",
                    "log_read_lines",
                    "message",
                    "log_read_time",
                    "container_name",
                    "container_type",
                    "message_length",
                    "create_time",
                    "container_runtime_name",
                    "date_ns",
                    "status"
                ],
                "complete": false,
                "cost": "19ms",
                "index_name": "",
                "index_names": "",
                "index_store_type": "es",
                "is_running": false,
                "points": null,
                "query_type": "",
                "raw_query": "{\\\"aggs\\\":{},\\\"_source\\\":{\\\"excludes\\\":[\\\"message@json\\\"],\\\"includes\\\":[]},\\\"query\\\":{\\\"bool\\\":{\\\"filter\\\":[{\\\"term\\\":{\\\"__namespace\\\":\\\"logging\\\"}},{\\\"range\\\":{\\\"date\\\":{\\\"gte\\\":\\\"1680187562081\\\",\\\"lte\\\":\\\"1680230762081\\\"}}},{\\\"bool\\\":{\\\"should\\\":[{\\\"terms\\\":{\\\"index\\\":[\\\"default\\\"]}}]}}]}},\\\"size\\\":50,\\\"sort\\\":[{\\\"date\\\":{\\\"missing\\\":\\\"_last\\\",\\\"order\\\":\\\"desc\\\",\\\"unmapped_type\\\":\\\"long\\\"}},{\\\"date_ns\\\":{\\\"missing\\\":\\\"_last\\\",\\\"order\\\":\\\"desc\\\",\\\"unmapped_type\\\":\\\"long\\\"}},{\\\"__docid\\\":{\\\"missing\\\":\\\"_first\\\",\\\"order\\\":\\\"desc\\\",\\\"unmapped_type\\\":\\\"string\\\"}}],\\\"search_after\\\":[1680226330509,8572,\\\"L_1680226330509_cgj4hqbrhi85kl1m6os0\\\"],\\\"timeout\\\":\\\"54s\\\"}",
                "search_after": [
                    1680226330508,
                    82936,
                    "L_1680226330508_cgj4hbdepb7fcn07sf60"
                ],
                "series": [
                    {
                        "columns": [
                            "container_id",
                            "time",
                            "source",
                            "filepath",
                            "image",
                            "index",
                            "df_metering_size",
                            "__namespace",
                            "host",
                            "log_read_offset",
                            "__docid",
                            "filename",
                            "service",
                            "image_name",
                            "image_short_name",
                            "image_tag",
                            "log_read_lines",
                            "message",
                            "log_read_time",
                            "container_name",
                            "container_type",
                            "message_length",
                            "create_time",
                            "container_runtime_name",
                            "date_ns",
                            "status"
                        ],
                        "values": [
                            [
                                "2fef685801c80b5cb7d04b7b5e859007de94752aadbe801df812a058acf5e380",
                                1680226330509,
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                                "/var/lib/docker/containers/2fef685801c80b5cb7d04b7b5e859007de94752aadbe801df812a058acf5e380/2fef685801c80b5cb7d04b7b5e859007de94752aadbe801df812a058acf5e380-json.log",
                                "test:test",
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                                "test",
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                                147890,
                                "ddtrace.profiling.exporter.http.UploadFailed: [Errno 101] Network is unreachable",
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                                "2fef685801c80b5cb7d04b7b5e859007de94752aadbe801df812a058acf5e380",
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                                "  File \\\"/usr/local/lib/python3.7/site-packages/tenacity/__init__.py\\\", line 361, in iter",
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                        ]
                    }
                ],
                "total_hits": 10000
            }
        ]
    },
    "errorCode": "",
    "message": "",
    "success": true,
    "traceId": "TRACE-CD50CBBD-E29B-4F58-BD6B-618EED50920A"
} 

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