宁波模板建站定制网站,appui设计图,国外psd网页模板网站,成都市建设局权益卡网站索引介绍
sw_records-all
这个索引用于存储所有的采样记录#xff0c;包括但不限于慢SQL查询、Agent分析得到的数据等。这些记录数据包括Traces、Logs、TopN采样语句和告警信息。它们被用于性能分析和故障排查#xff0c;帮助开发者和运维团队理解服务的行为和性能特点。
…索引介绍
sw_records-all
这个索引用于存储所有的采样记录包括但不限于慢SQL查询、Agent分析得到的数据等。这些记录数据包括Traces、Logs、TopN采样语句和告警信息。它们被用于性能分析和故障排查帮助开发者和运维团队理解服务的行为和性能特点。
mapping {sw_records-all: {aliases: {sw_records-all: {}},mappings: {_source: {excludes: [tags]},properties: {alarm_message: {type: keyword,copy_to: [alarm_message_match},alarm_message_match: {type: text,analyzer: oap_analyzer},continuous_profiling_json: {type: keyword,index: false},create_time: {type: long},data_binary: {type: binary},dump_binary: {type: binary},dump_period: {type: integer},dump_time: {type: long},duration: {type: integer},end_time_nanos: {type: integer},end_time_second: {type: long},endpoint_name: {type: keyword},entity_id: {type: keyword},event: {type: keyword},extension_config_json: {type: keyword,index: false},fixed_trigger_duration: {type: long},id0: {type: keyword,index: false},id1: {type: keyword,index: false},instance_id: {type: keyword},last_update_time: {type: long},latency: {type: long},logical_id: {type: keyword},max_sampling_count: {type: integer},min_duration_threshold: {type: integer},name: {type: keyword,index: false},operation_time: {type: long},operation_type: {type: integer,index: false},process_labels_json: {type: keyword},record_table: {type: keyword},related_trace_id: {type: keyword},rule_name: {type: keyword},schedule_id: {type: keyword},scope: {type: integer},segment_id: {type: keyword},sequence: {type: integer},service_id: {type: keyword},stack_binary: {type: binary},stack_id: {type: keyword},start_time: {type: long},start_time_nanos: {type: integer},start_time_second: {type: long},statement: {type: keyword,index: false},tags: {type: keyword},tags_raw_data: {type: binary},target_type: {type: integer},task_id: {type: keyword},time_bucket: {type: long},timestamp: {type: long},trace_id: {type: keyword,index: false},trace_ref_type: {type: integer},trace_segment_id: {type: keyword},trace_span_id: {type: keyword},trigger_type: {type: integer},upload_time: {type: long}}},settings: {index: {routing: {allocation: {include: {_tier_preference: data_content}}},refresh_interval: 30s,number_of_shards: 1,provided_name: sw_records-all-20241125,creation_date: 1732464023751,analysis: {analyzer: {oap_analyzer: {type: stop}}},number_of_replicas: 1,uuid: qrRVCMSNSnO90iz9hHWD0Q,version: {created: 7170799}}}}
} sw_metrics-all 这个索引存储服务、服务实例及端点的元数据即指标信息。这些指标数据包括服务的响应时间、吞吐量、错误率等关键性能指标以分钟级别存储。这些数据对于监控服务性能至关重要因为它们提供了实时的性能反馈使得团队能够快速识别和解决性能问题。
metric_table枚举值
1、endpoint_cpm端点的每分钟调用次数CPM
2、endpoint_percentile端点的响应时间百分位数
3、endpoint_resp_time端点的平均响应时间
4、endpoint_sla服务等级协议SLA指标
5、endpoint_sidecar_internal_req_latency_nanos 和 endpoint_sidecar_internal_resp_latency_nanos端点Sidecar内部请求和响应延迟的纳秒数
6、instance_jvm_xxx服务实例的JVM相关指标如类加载数量、CPU使用率、内存使用情况、垃圾回收次数和线程状态等
7、meter_thread_pool线程池相关的度量
8、service_instance_cpm、service_instance_resp_time、service_instance_sla服务实例级别的CPM、响应时间和SLA指标
9、service_instance_sidecar_internal_req_latency_nanos 和 service_instance_sidecar_internal_resp_latency_nanos服务实例级别的Sidecar内部请求和响应延迟的纳秒数
result {key: endpoint_cpm,doc_count: 5763},{key: endpoint_percentile,doc_count: 5763},{key: endpoint_resp_time,doc_count: 5763},{key: endpoint_sla,doc_count: 5763},{key: endpoint_sidecar_internal_req_latency_nanos,doc_count: 5754},{key: endpoint_sidecar_internal_resp_latency_nanos,doc_count: 5754},{key: instance_jvm_class_loaded_class_count,doc_count: 2811},{key: instance_jvm_class_total_loaded_class_count,doc_count: 2811},{key: instance_jvm_class_total_unloaded_class_count,doc_count: 2811},{key: instance_jvm_cpu,doc_count: 2811},{key: instance_jvm_memory_heap,doc_count: 2811},{key: instance_jvm_memory_heap_max,doc_count: 2811},{key: instance_jvm_memory_noheap,doc_count: 2811},{key: instance_jvm_memory_noheap_max,doc_count: 2811},{key: instance_jvm_old_gc_count,doc_count: 2811},{key: instance_jvm_old_gc_time,doc_count: 2811},{key: instance_jvm_thread_blocked_state_thread_count,doc_count: 2811},{key: instance_jvm_thread_daemon_count,doc_count: 2811},{key: instance_jvm_thread_live_count,doc_count: 2811},{key: instance_jvm_thread_peak_count,doc_count: 2811},{key: instance_jvm_thread_runnable_state_thread_count,doc_count: 2811},{key: instance_jvm_thread_timed_waiting_state_thread_count,doc_count: 2811},{key: instance_jvm_thread_waiting_state_thread_count,doc_count: 2811},{key: instance_jvm_young_gc_count,doc_count: 2811},{key: instance_jvm_young_gc_time,doc_count: 2811},{key: meter_thread_pool,doc_count: 2811},{key: service_instance_cpm,doc_count: 1661},{key: service_instance_resp_time,doc_count: 1661},{key: service_instance_sla,doc_count: 1661},{key: service_instance_sidecar_internal_req_latency_nanos,doc_count: 1659},{key: service_instance_sidecar_internal_resp_latency_nanos,doc_count: 1659} mapping {sw_metrics-all-20241125: {aliases: {sw_metrics-all: {}},mappings: {properties: {address: {type: keyword},agent_id: {type: keyword},component_id: {type: integer,index: false},component_ids: {type: keyword,index: false},count: {type: long,index: false},dataset: {type: text,index: false},datatable_count: {type: text,index: false},datatable_summation: {type: text,index: false},datatable_value: {type: text,index: false},denominator: {type: long},dest_endpoint: {type: keyword},dest_process_id: {type: keyword},dest_service_id: {type: keyword},dest_service_instance_id: {type: keyword},detect_type: {type: integer},double_summation: {type: double,index: false},double_value: {type: double},ebpf_profiling_schedule_id: {type: keyword},end_time: {type: long},endpoint: {type: keyword},endpoint_traffic_name: {type: keyword,copy_to: [endpoint_traffic_name_match]},endpoint_traffic_name_match: {type: text,analyzer: oap_analyzer},entity_id: {type: keyword},instance_id: {type: keyword},instance_traffic_name: {type: keyword,index: false},int_value: {type: integer},label: {type: keyword},labels_json: {type: keyword,index: false},last_ping: {type: long},last_update_time_bucket: {type: long},layer: {type: integer},match: {type: long,index: false},message: {type: keyword},metric_table: {type: keyword},name: {type: keyword},numerator: {type: long},parameters: {type: keyword,index: false},percentage: {type: integer},precision: {type: integer,index: false},process_id: {type: keyword},profiling_support_status: {type: integer},properties: {type: text,index: false},ranks: {type: text,index: false},remote_service_name: {type: keyword},represent_service_id: {type: keyword},represent_service_instance_id: {type: keyword},s_num: {type: long,index: false},service: {type: keyword},service_group: {type: keyword},service_id: {type: keyword},service_instance: {type: keyword},service_instance_id: {type: keyword},service_name: {type: keyword},service_traffic_name: {type: keyword,copy_to: [service_traffic_name_match]},service_traffic_name_match: {type: text,analyzer: oap_analyzer},short_name: {type: keyword},source_endpoint: {type: keyword},source_process_id: {type: keyword},source_service_id: {type: keyword},source_service_instance_id: {type: keyword},span_name: {type: keyword},start_time: {type: long},summation: {type: long,index: false},t_num: {type: long,index: false},tag_key: {type: keyword},tag_type: {type: keyword},tag_value: {type: keyword},task_id: {type: keyword},time_bucket: {type: long},total: {type: long,index: false},total_num: {type: long,index: false},type: {type: keyword},uuid: {type: keyword},value: {type: long}}},settings: {index: {routing: {allocation: {include: {_tier_preference: data_content}}},refresh_interval: 30s,number_of_shards: 1,provided_name: sw_metrics-all-20241125,creation_date: 1732464018472,analysis: {analyzer: {oap_analyzer: {type: stop}}},number_of_replicas: 1,uuid: WzZSWrHRSKaHFFwbm5D75A,version: {created: 7170799}}}}
}
字段解释
address服务实例的网络地址
agent_idSkyWalking Agent的唯一标识符
component_id组件的唯一标识符
component_ids一个包含多个组件ID的列表用于标识服务中使用的所有组件
count计数器记录调用次数等
dataset数据集的标识符用于区分不同类型的监控数据
datatable_count、datatable_summation、datatable_value与数据表相关的字段用于存储汇总数据
denominator用于计算比率的分母值
dest_endpoint目标端点的名称用于标识服务调用的目标
dest_process_id、dest_service_id、dest_service_instance_id目标进程、服务和实例的唯一标识符
detect_type检测类型的标识符
double_summation双精度浮点数的总和
double_value双精度浮点数值
ebpf_profiling_schedule_ideBPF性能分析任务的标识符
end_time事件或记录的结束时间戳
endpoint端点的名称用于标识服务中的特定操作
endpoint_traffic_name端点流量的名称用于标识端点的流量
entity_id实体的唯一标识符用于标识服务、端点或实例
instance_id服务实例的唯一标识符
instance_traffic_name服务实例流量的名称
int_value整数值
label用于分类或标记数据的标签
labels_json包含多个标签的JSON字符串
last_ping服务实例最后一次发送心跳的时间戳
last_update_time_bucket数据最后一次更新的时间桶
layer服务的层次或层级
match用于匹配规则的标识符
message与事件或日志相关的信息
metric_table度量表的名称用于标识特定的度量数据
name实体、服务或端点的名称
numerator用于计算比率的分子值
parameters与事件或操作相关的参数
percentage百分比值
precision数据的精度
process_id进程的唯一标识符
profiling_support_status性能分析支持的状态
properties实体的属性
ranks排名或等级
remote_service_name远程服务的名称
represent_service_id、represent_service_instance_id表示服务或实例的唯一标识符
s_num用于统计的数值
service服务的名称
service_group服务组的名称
service_id服务的唯一标识符
service_instance服务实例的名称
service_instance_id服务实例的唯一标识符
service_name服务的名称
service_traffic_name服务流量的名称
short_name实体的简称或缩写
source_endpoint源端点的名称
source_process_id、source_service_id、source_service_instance_id源进程、服务和实例的唯一标识符
span_name跨度Span的名称用于分布式追踪
start_time事件或记录的开始时间戳
summation数值的总和
t_num用于统计的数值
tag_key、tag_type、tag_value标签的键、类型和值
task_id任务的唯一标识符
time_bucket时间桶用于数据的时序聚合
total、total_num总数和数量
type数据的类型
uuid全局唯一标识符
value度量值 sw_segment
sw_segment索引用于收集链路信息日志。在SkyWalking中一个Segment代表一个分布式追踪的路径它由多个Span组成记录了一次完整的请求处理过程。这些数据对于理解服务之间的调用关系和性能特性非常重要它们是实现分布式追踪和性能监控的基础。
sw_zipkin_span
sw_zipkin_span索引用于存储Zipkin跟踪的Span数据。SkyWalking可以作为Zipkin的替代服务器提供高级功能这个索引就是用来兼容Zipkin格式的追踪数据。
sw_browser_error_log
sw_browser_error_log索引用于收集浏览器日志特别是错误日志。这些日志对于前端监控和错误分析非常有用可以帮助开发者了解用户在使用应用时遇到的前端问题。
sw_log
sw_log索引用于收集除浏览器外的日志。这些日志可能来自于后端服务、中间件或其他系统组件对于整体的系统监控和日志分析非常重要。
sw_continuous_profiling_policy
这个索引用于存储连续性能分析Continuous Profiling的策略配置。连续性能分析是SkyWalking的一个特性它允许基于预设的策略自动触发性能分析任务。这些策略可以定义何时以及如何对特定的目标如进程或服务进行性能分析以便及时发现和诊断性能问题。例如当eBPF Agent检测到某个进程的指标符合策略规则时它会立即触发对该进程的性能分析任务从而减少中间步骤加快定位性能问题的能力
sw_ui_template
sw_ui_template索引用于存储SkyWalking UI的模板配置。这些模板定义了SkyWalking UI中的仪表板和视图包括官方提供的默认仪表板以及用户自定义的仪表板。用户可以通过这些模板来创建新的仪表板添加新的标签/页面/小部件并根据自己的偏好重新配置仪表板。模板支持层Layer和实体类型Entity Type的概念这对于理解和自定义SkyWalking UI中的仪表板至关重要
查询语句整理
查询sw_metrics-all索引
1、查找特定时间范围内与特定服务相关的服务关系指标 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{bool: {should: [{term: {source_service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}},{term: {dest_service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},{term: {metric_table: {value: service_relation_server_side,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1000,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {component_ids: {terms: {field: component_ids,size: 10,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first}}}}}
}
2、对特定时间范围内的服务间关系数据进行聚合分析 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{bool: {should: [{term: {source_service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}},{term: {dest_service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},{term: {metric_table: {value: service_relation_client_side,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1000,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {component_ids: {terms: {field: component_ids,size: 10,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first}}}}}
}
3、统计服务下的实例流量 {size: 5000,query: {bool: {must: [{range: {last_ping: {from: 202411221112,to: null,include_lower: true,include_upper: true,boost: 1.0}}},{term: {service_id: {value: c2VydmljZTo6dGVuZGF0YS1tZXNzYWdlLXNlcnZpY2U.1,boost: 1.0}}},{term: {metric_table: {value: instance_traffic,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}}
}
4、统计服务下的端点流量 {size: 20,query: {bool: {must: [{term: {service_id: {value: c2VydmljZTo6dGVuZGF0YS1tZXNzYWdlLXNlcnZpY2U.1,boost: 1.0}}},{term: {metric_table: {value: endpoint_traffic,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}}
}
5、查询标签数据 {query: {bool: {must: [{term: {tag_type: {value: TRACE,boost: 1.0}}},{term: {metric_table: {value: tag_autocomplete,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {tag_key: {terms: {field: tag_key,size: 100,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,order: [{_count: desc},{_key: asc}]}}}
}
6、统计服务流量 {size: 5000,query: {bool: {must: [{term: {layer: {value: 2,boost: 1.0}}},{term: {metric_table: {value: service_traffic,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}}
}
7、计算服务间的服务每分钟调用次数 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [MTkyLjE2OC4zMC4xOjkwOTI7MTkyLjE2OC4zMC4zOjkwOTI.1-c2VydmljZTo6dGVuZGF0YS1jb3JwLXNlcnZpY2U.1],boost: 1.0}},{term: {metric_table: {value: service_relation_server_cpm,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
8、计算服务间的服务响应时间 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS1iaXpyLXNlcnZpY2U.1-c2VydmljZTo6dGVuZGF0YS1nbG9jby1zZXJ2aWNl.1],boost: 1.0}},{term: {metric_table: {value: service_relation_server_resp_time,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
9、计算服务间的服务客户端响应时间 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS1tY3Mtc2VydmljZQ.1-MTkyLjE2OC4zMC4xOjkwOTI7MTkyLjE2OC4zMC4zOjkwOTI.0],boost: 1.0}},{term: {metric_table: {value: service_relation_client_resp_time,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
10、计算服务间的客户端每分钟调用次数 {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS10cmFuc2xhdGlvbi1zZXJ2aWNl.1-YXBpLnRyYW5zbGF0b3IuYXp1cmUuY246NDQz.1],boost: 1.0}},{term: {metric_table: {value: service_relation_client_cpm,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
11、计算服务响应时间service_resp_time {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS1tY3Mtc2VydmljZQ.1],boost: 1.0}},{term: {metric_table: {value: service_resp_time,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
12、计算服务级别协议的成功百分比service_sla {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS1vcGVuYXBpLWdhdGV3YXktc2VydmljZQ.1],boost: 1.0}},{term: {metric_table: {value: service_sla,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {percentage: {avg: {field: percentage}}}}}
}
13、计算服务每分钟请求数service_cpm {size: 0,query: {bool: {must: [{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}},{terms: {entity_id: [c2VydmljZTo6dGVuZGF0YS1kZnMtc2VydmljZQ.1],boost: 1.0}},{term: {metric_table: {value: service_cpm,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 1,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{_count: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
14、查询网络地址别名 {size: 5000,query: {bool: {must: [{term: {metric_table: {value: network_address_alias,boost: 1.0}}},{range: {last_update_time_bucket: {from: 202411221132,to: null,include_lower: true,include_upper: true,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}}
}
15、检索 service为service::tendata-contact-service的事件列表 {from: 0,size: 20,query: {bool: {must: [{term: {metric_table: {value: events,boost: 1.0}}},{term: {service: {value: service::tendata-contact-service,boost: 1.0}}},{range: {start_time: {from: 1732245120000,to: null,include_lower: false,include_upper: true,boost: 1.0}}},{range: {end_time: {from: null,to: 1732246980000,include_lower: true,include_upper: false,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{start_time: {order: desc}}]
}
16、分页获取特定时间段内特定服务指标数据并按时间戳排序 {from: 0,size: 15,query: {bool: {must: [{range: {time_bucket: {from: 20241122111200,to: 20241122114259,include_lower: true,include_upper: true,boost: 1.0}}},{term: {service_id: {value: c2VydmljZTo6dGVuZGF0YS1tZXNzYWdlLXNlcnZpY2U.1,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{timestamp: {order: desc}}]
}
17、根据传递的id查询端点信息 {size: 156,query: {ids: {values: [endpoint_traffic_c2VydmljZTo6dGVuZGF0YS1nYXRld2F5LXNlcnZpY2U.1_L2luc2lnaHQtc2VhcmNoL3YxL3Byb2dyYW1tZXMvMjkyNTcvbWFya2V0LWNvdW50ZXJwYXJ0eS1hcmVh,endpoint_traffic_c2VydmljZTo6dGVuZGF0YS1nYXRld2F5LXNlcnZpY2U.1_L2NvcnAvdjIvY29tcGFuaWVzLzEwYzdkMWVjYTY4NTE0NDQ1NzQ5OWVkZTJkZTQxY2I1L3JlZnJlc2gvcmVzdWx0],boost: 1.0}}
}
18、查询某个服务的每分钟请求次数最多的10个接口 {query: {bool: {must: [{term: {metric_table: {value: endpoint_cpm,boost: 1.0}}},{terms: {service_id: [c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1],boost: 1.0}},{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 10,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{value: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
19、查询某个服务的响应时间最大的10个接口 {query: {bool: {must: [{term: {metric_table: {value: endpoint_resp_time,boost: 1.0}}},{terms: {service_id: [c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1],boost: 1.0}},{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 10,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{value: desc},{_key: asc}],collect_mode: breadth_first},aggregations: {value: {avg: {field: value}}}}}
}
20、查询某个服务的指定时间范围内成功率最小的10个接口 {query: {bool: {must: [{term: {metric_table: {value: endpoint_sla,boost: 1.0}}},{terms: {service_id: [c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1],boost: 1.0}},{range: {time_bucket: {from: 202411221112,to: 202411221142,include_lower: true,include_upper: true,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},aggregations: {entity_id: {terms: {field: entity_id,size: 10,min_doc_count: 1,shard_min_doc_count: 0,show_term_doc_count_error: false,execution_hint: map,order: [{percentage: asc},{_key: asc}],collect_mode: breadth_first},aggregations: {percentage: {avg: {field: percentage}}}}}
}
21、查询标签信息 {size: 12,query: {ids: {values: [tag_autocomplete_20241122_TRACE_db.instance_[im_moldova-2024, im_moldova-2022, im_moldova-2023, im_moldova-2021],tag_autocomplete_20241122_TRACE_db.instance_[a04b2a53a6d946ad9fe525cd1ab2646a_alias],tag_autocomplete_20241122_TRACE_db.instance_[im_maritime_silk_bol-2022, im_maritime_silk_bol-2023, im_maritime_silk_bol-2021, im_maritime_silk_bol-2024]],boost: 1.0}}
} 查询sw_records-all索引
1、查询优化任务列表 {size: 200,query: {bool: {must: [{term: {record_table: {value: profile_task,boost: 1.0}}},{range: {time_bucket: {from: 202411221137,to: null,include_lower: true,include_upper: true,boost: 1.0}}},{range: {time_bucket: {from: null,to: 202411221147,include_lower: true,include_upper: true,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{start_time: {order: desc}}]
}
2、查询sw_records-all与特定跨度Span关联的事件记录 {size: 100,query: {bool: {must: [{term: {record_table: {value: span_attached_event_record,boost: 1.0}}},{terms: {related_trace_id: [ab80cf2b85fa4f3e9baabd114f3b909e.98.17322469467401053],boost: 1.0}},{terms: {trace_ref_type: [0],boost: 1.0}}],adjust_pure_negative: true,boost: 1.0}},sort: [{start_time_second: {order: asc}},{start_time_nanos: {order: asc}}]
}
3、检索ebpf优化任务 {size: 200,query: {bool: {must: [{term: {record_table: {value: ebpf_profiling_task,boost: 1.0}}},{term: {service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}},{terms: {target_type: [1,2],boost: 1.0}},{term: {trigger_type: {value: 1,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{create_time: {order: desc}}]
}
4、查询性能任务日志 {size: 10000,query: {bool: {must: [{term: {record_table: {value: profile_task_log,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{operation_time: {order: desc}}]
}
查询sw_segment索引
1、查询某个服务的流量 {size: 1,query: {ids: {values: [service_traffic_MTkyLjE2OC4xMS4xMDo1Njcy.15],boost: 1.0}}
}
2、查询某个调用链信息 {size: 200,query: {term: {trace_id: {value: ab80cf2b85fa4f3e9baabd114f3b909e.98.17322469467401053,boost: 1.0}}}
}
3、分页获取特定时间段内特定服务调用数据并按开始时间排序 {from: 0,size: 20,query: {bool: {must: [{range: {time_bucket: {from: 20241122111200,to: 20241122114259,include_lower: true,include_upper: true,boost: 1.0}}},{term: {service_id: {value: c2VydmljZTo6dGVuZGF0YS1jb250YWN0LXNlcnZpY2U.1,boost: 1.0}}}],adjust_pure_negative: true,boost: 1.0}},sort: [{start_time: {order: desc}}]
}
