命名空间
Namespace = QCE/TSTREAM
监控指标
指标英文名 | 指标中文名 | 说明 | 单位 | 维度 | 统计规则
[period, statType] |
Binlogpos | 位点信息 | 数据源日志位点信息 | None | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
Currentemiteventtimelag | source消息处理时间 | CDC Source 处理发送下游的时间与消息本身时间差 | ms | tjob_id | [ 60s, last ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
Currentfetcheventtimelag | 数据流入耗时 | Source Fetch消息的延迟时间(EmitTime-messageTimestamp) | ms | tjob_id | [ 60s, last ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
Dbflushdelay | Sink刷新延迟 | Sink 刷新延迟 | ms | tjob_id | [ 60s, last ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobBytesInPerSecond | 作业每秒输入的数据量 | 作业所有数据源（Source）每秒输入的数据总量（仅对 Kafka Source 有效） | Bytes/s | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobBytesOutPerSecond | 作业每秒输出的数据量 | 作业所有数据目的（Sink）每秒输出的数据总量（仅对 Kafka Sink 有效） | Bytes/s | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobCpuLoad | TaskManagerCPU使用率 | 作业中所有 TaskManager 的平均 CPU 使用率 | % | tjob_id | [ 60s, avg ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobLastcheckpointduration | 最近一次的Checkpoint耗时 | 当前作业最近一次的 Checkpoint 耗时 | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobLastcheckpointsize | 最近一次的Checkpoint大小 | 当前作业最近一次的 Checkpoint 大小 | Bytes | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobLatency | 算子计算总耗时 | 数据流经各个算子时的耗时总和。可能存在采样误差，数值仅供参考 | ms | tjob_id | [ 60s, sum ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerCpuLoad | JobManagerCPU的使用率 | 当前作业 JobManager 的 CPU 使用率 | % | tjob_id | [ 60s, avg ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerCpuTime | JobManager使用CPU的时长 | 当前作业 JobManager CPU 使用时长（毫秒） | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerDowntime | 作业中断运行时间 | 对于失败或恢复等非运行状态的作业，表示本次中断运行的时长。对于正在运行中的作业，值为 0. | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerJobNumrestarts | 当前运行实例的重启次数 | 当前实例 JobManager 记录的任务崩溃重启次数（不含 JobManager 退出后作业重新拉起的场景） | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerJvmOldGcCount | JobManager老年代GC次数 | 当前作业 JobManager 老年代 GC 次数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerJvmOldGcTime | JobManager老年代GC时间 | 当前作业 JobManager 老年代 GC 时间 | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerJvmYoungGcCount | JobManager年轻代GC次数 | 当前作业 JobManager 年轻代 GC 次数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerJvmYoungGcTime | JobManager年轻代GC时间 | 当前作业 JobManager 年轻代 GC 时间 | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerLastcheckpointrestoretimestamp | 作业上次从快照恢复的时间戳 | 作业最近一次从快照恢复的 Unix 时间戳（以毫秒为单位，如果未恢复过则是 -1） | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerMemoryDirectCount | JobManager直接内存中的缓存数 | JobManager 堆外直接内存（Direct Buffer Pool）中的缓存（Buffer）个数 | Count | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryDirectMemoryused | JobManager堆外直接内存用量 | JobManager 堆外直接内存（Direct Buffer Pool）的用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryDirectTotalcapacity | JobManager直接内存总容量 | JobManager 堆外直接内存（Direct Buffer Pool）的最大用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryHeapCommitted | JobManager已提交的堆内存容量 | 当前作业 JobManager 已提交（committed）的堆内存容量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryHeapMax | JobManager堆内存最大容量 | 当前作业 JobManager 堆内存最大容量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryMappedCount | JobManager映射内存的缓存数 | JobManager 堆外映射内存（Mapped Buffer Pool）中的缓存（Buffer）个数之和 | Count | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryMappedMemoryused | JobManager映射内存的使用量 | JobManager 堆外映射内存（Mapped Buffer Pool）的用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryMappedTotalcapacity | JobManager映射内存的总容量 | JobManager 堆外映射内存（Mapped Buffer Pool）的最大用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerMemoryNonheapCommitted | JobManager已提交的非堆内存容量 | 当前作业已提交（committed）的 JobManager 非堆内存（JVM 元空间、代码缓存等）容量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerNumberofinprogresscheckpoints | 进行中的Checkpoint数量 | 当前作业进行中（未完成）的 Checkpoint 个数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerNumregisteredtaskmanagers | 作业中TaskManager的数量 | 当前作业已注册的 TaskManager 数，通常等于所有算子并行度的最大值。如果 TaskManager 个数减少，说明存在 TaskManager 失联，作业可能崩溃并尝试恢复。 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerNumrunningjobs | 运行中的作业数量 | 正在运行中作业数。如果作业正常运行，则值为 1. 如果作业崩溃则值为 0 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerStatusJvmMemoryHeapUsed | JobManager堆内存的用量 | 当前作业 JobManager 堆内存的用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerStatusJvmMemoryHeapUsedPercentage | JobManager堆内存使用率 | 当前作业 JobManager 堆内存使用率 | % | tjob_id | [ 60s, expr ]
[ 300s, expr ] |
JobmanagerStatusJvmMemoryNonheapMax | JobManager内存最大容量 | 当前作业 JobManager 非堆内存（JVM 元空间、代码缓存等）的最大容量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerStatusJvmMemoryNonheapUsed | JobManager非堆内存用量 | 当前作业 JobManager 非堆内存（JVM 元空间、代码缓存等）用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerStatusJvmMemoryProcessMemoryused | JobManager所在的JVM的物理内存用量 | JobManager 所在的 JVM 的物理内存用量 | Bytes | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobmanagerTaskslotsavailable | JobManager可用任务槽数量 | 如果作业正常运行，则可用的任务槽（Task Slot）数为 0. 如果不为 0 则说明作业可能出现短时间的非运行状态 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerTaskslotstotal | JobManager任务槽总数 | Oceanus 中一个 TaskManager 只有一个任务槽，因此任务槽总数等于注册的 TaskManager 数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobmanagerThreadsCount | JobManager活动线程数 | 当前作业 JobManager 中活动的线程数，含 Daemon 和非 Daemon 线程。 | Count | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobMemoryDirectUsed | TaskManager堆外直接内存用量 | 作业中所有 TaskManager 堆外直接内存（Direct Buffer Pool）的用量之和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobMemoryHeapMax | TaskManager堆内存最大容量 | 作业中所有 TaskManager 的堆内存最大（max）容量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobMemoryHeapUsed | TaskManager堆内存用量 | 作业中所有 TaskManager 的当前堆内存用量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobMemoryMappedUsed | TaskManager堆外映射内存用量 | 作业中所有 TaskManager 堆外映射内存（Mapped Buffer Pool）的用量之和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobMemoryNonheapUsed | TaskManager非堆内存用量 | 作业中所有 TaskManager 非堆内存（JVM 元空间、代码缓存等）用量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobNumberofcompletedcheckpoints | Checkpoint成功完成次数 | 当前作业 Checkpoint 成功完成的次数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobNumberoffailedcheckpoints | Checkpoint失败次数 | 当前作业 Checkpoint 失败（例如超时、遇到异常等）的次数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobNumrecordsinbutfailed | 严重异常数据个数 | 算子中发生严重异常（例如抛出各种 Exception）的数据个数，如果大于 1 则会影响 Exactly-Once 语义（试验参数，仅供参考） | Count | tjob_id | [ 60s, sum ]
[ 300s, sum ]
[ 3600s, sum ]
[ 86400s, sum ] |
JobRecordsInPerSecond | 作业每秒输入的记录条数 | 作业所有数据源（Source）每秒输入的数据总条数 | Count/s | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobRecordsOutPerSecond | 作业每秒输出的记录条数 | 作业所有数据目的（Sink）每秒输出的数据总条数 | Count/s | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
JobRestartingtime | 作业重启耗时 | 作业最近一次重启耗时 | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobServiceDelay | 目的端Watermark延时 | 当前时间戳与数据目的（Sink）InputWatermark 之间的差值（多个 Sink 则取最大值） | ms | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
JobTotalnumberofcheckpoints | Checkpoint总次数 | Checkpoint 总次数（进行中、已完成和失败的总和） | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
JobUptime | 作业无中断持续执行的时间 | 对于运行中的作业，表示当次作业持续处于运行中的时长 | ms | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
RecordsLagMax | Taskmanger上报的kafka最大lag指标 | TaskManger 上报的 Kafka 最大 lag 指标 | None | tjob_id | [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
RecordsLagMaxAvg | Taskmanger上报的kafka最大lag指标的均值 | TaskManger 上报的 Kafka 最大 lag 指标的均值 | None | tjob_id | [ 60s, avg ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
RecordsLagMaxMin | Taskmanger上报的kafka最大lag指标最小值 | TaskManger 上报的 Kafka 最大 lag 指标最小值 | None | tjob_id | [ 60s, min ]
[ 300s, min ]
[ 3600s, min ]
[ 86400s, min ] |
RecordsLagMaxSum | Taskmanger上报的kafka最大lag指标的求和值 | TaskManger 上报的 Kafka 最大 lag 指标的求和值 | None | tjob_id | [ 60s, sum ]
[ 300s, sum ]
[ 3600s, sum ]
[ 86400s, sum ] |
Sourceidletime | 批间隔时间 | Source 处理的空闲时间 | ms | tjob_id | [ 60s, last ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
Syndelay | 数据源同步百分比 | 数据源同步百分比 | % | tjob_id | [ 60s, last ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerCpuTime | TaskManager使用CPU的时长 | 作业中所有 TaskManager CPU 使用时长总和（毫秒） | ms | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerJobTaskBackpressuredtimemspersecond | 反压指标 | 当前作业所有 task 每秒内反压时长的最大值 | % | tjob_id | [ 60s, max ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerJobTaskBuffersInpoolusage | task输入缓冲区使用率 | task输入缓冲区使用率 | % | tjob_id
task_id
subtask_index | [ 60s, max ]
[ 300s, max ] |
TaskmanagerJobTaskBuffersInputqueuelength | task输入缓冲区的数量 | task输入缓冲区的数量 | None | tjob_id
task_id
subtask_index | [ 60s, max ]
[ 300s, max ] |
TaskmanagerJobTaskBuffersOutpoolusage | task输出缓冲区使用率 | task输出缓冲区使用率 | % | tjob_id
task_id
subtask_index | [ 60s, max ]
[ 300s, max ] |
TaskmanagerJobTaskBuffersOutputqueuelength | task输出缓冲区的数量 | task输出缓冲区的数量 | None | tjob_id
task_id
subtask_index | [ 60s, max ]
[ 300s, max ] |
TaskmanagerJobTaskCurrentlowwatermark | task当前收到的watermark | task当前收到的watermark | None | tjob_id
task_id
subtask_index | [ 60s, max ]
[ 300s, max ] |
TaskmanagerJobTaskDataskewcoefficient | 数据倾斜程度 | 当前作业所有 task 的 subtask 的数据输入量的离散系数（=标准差/均值），在[0,1]的范围内 | None | tjob_id | [ 60s, max ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerJobTaskOperatorKafkaSwitch | 开关指标_kafka | 是否包含 Kafka connector | None | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerJobTaskOperatorSchemachange | CDC_Schema_变更次数 | CDC Schema 变更次数 | Count | tjob_id | [ 60s, last ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerJvmOldGcCount | TaskManager老年代GC次数 | 作业中所有 TaskManager 老年代 GC 次数之和 | Count | tjob_id | [ 60s, sum ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerJvmOldGcTime | TaskManager老年代GC时间 | 作业中所有 TaskManager 老年代 GC 时间之和 | ms | tjob_id | [ 60s, sum ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerJvmThreadsCount | TaskManager活动线程数 | 作业中所有 TaskManager 中活动的线程数之和，含 Daemon 和非 Daemon 线程。 | Count | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerJvmYoungGcCount | TaskManager年轻代GC次数 | 作业中所有 TaskManager 年轻代 GC 次数之和 | Count | tjob_id | [ 60s, sum ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerJvmYoungGcTime | TaskManager年轻代GC时间 | 作业中所有 TaskManager 年轻代 GC 时间之和 | ms | tjob_id | [ 60s, sum ]
[ 300s, last ]
[ 3600s, last ]
[ 86400s, last ] |
TaskmanagerMemoryDirectCount | TaskManager直接内存缓存数 | 作业中所有 TaskManager 堆外直接内存（Direct Buffer Pool）中的缓存（Buffer）个数之和 | Count | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerMemoryDirectTotalcapacity | TaskManager直接内存总容量 | 作业中所有 TaskManager 堆外直接内存（Direct Buffer Pool）的最大容量之和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerMemoryHeapCommitted | TaskManager已提交的堆内存容量 | 作业中所有 TaskManager 已提交（committed）的堆内存容量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerMemoryMappedCount | TaskManager堆外映射内存缓存数 | 作业中所有 TaskManager 堆外映射内存（Mapped Buffer Pool）中的缓存（Buffer）个数之和 | Count | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerMemoryMappedTotalcapacity | TaskManager堆外映射内存总容量 | 作业中所有 TaskManager 堆外映射内存（Mapped Buffer Pool）的最大容量之和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerMemoryNonheapCommitted | TaskManager已提交的非堆内存容量 | 作业中所有 TaskManager 已提交（committed）的非堆内存（JVM 元空间、代码缓存等）用量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerNetworkAvailablememorysegments | 当前可用的MemorySegment个数 | 作业中所有 TaskManager 的可用 MemorySegment 个数之和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerNetworkTotalmemorysegments | 已分配的MemorySegment总数 | 作业中所有 TaskManager 已分配的 MemorySegment 个数总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerStatusJvmCpuLoad | 单个taskmanager的jvm的 CPU 负载 | 单个 taskmanager 的 jvm CPU 负载 | % | tjob_id
tm_id | [ 60s, avg ]
[ 300s, avg ] |
TaskmanagerStatusJvmGarbagecollectorOldGenerationCount | 单个taskmanager老年代GC次数 | 单个taskmanager老年代GC次数 | None | tm_id
tjob_id | [ 60s, max ]
[ 300s, max ] |
TaskmanagerStatusJvmGarbagecollectorOldGenerationTime | 单个taskmanager老年代GC时间 | 单个taskmanager老年代GC时间 | ms | tm_id
tjob_id | [ 60s, max ]
[ 300s, max ] |
TaskmanagerStatusJvmMemoryHeapUsed | 单个taskmanager堆内存使用量 | 单个taskmanager堆内存使用量 | Bytes | tjob_id
tm_id | [ 60s, max ]
[ 300s, max ] |
TaskmanagerStatusJvmMemoryHeapUsedPercentage | TaskManager堆内存使用率 | 作业中所有 TaskManager 的平均堆内存使用率 | % | tjob_id | [ 60s, expr ]
[ 300s, expr ] |
TaskmanagerStatusJvmMemoryNonheapMax | TaskManager非堆内存最大容量 | 作业中所有 TaskManager 非堆内存（JVM 元空间、代码缓存等）最大容量总和 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ] |
TaskmanagerStatusJvmMemoryProcessMemoryused | 所有TaskManager所在JVM的物理内存的用量的最大值 | 所有 TaskManager JVM 的物理内存用量的最大值 | Bytes | tjob_id | [ 60s, sum ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ] |
各维度对应参数总览
参数名称 | 维度名称 | 维度解释 | 格式 |
Instances.N.Dimensions.0.Name | tjob_id | 作业 ID 的维度名称 | 输入 String 类型维度名称：tjob_id |
Instances.N.Dimensions.0.Value | tjob_id | 具体作业 ID | |
Instances.N.Dimensions.0.Name | task_id | Flink 任务的算子ID | 输入 String 类型维度名称：task_id |
Instances.N.Dimensions.0.Value | task_id | 具体算子ID | 输入具体算子ID，可以从 DescribeJobRuntimeInfo 接口中获取 JobRuntimeInfo.[N].Key 为 SubTasks 的 Value, 使用 base64 解码 |
Instances.N.Dimensions.0.Name | subtask_index | Flink 中用于标识并行任务中每个子任务的索引 | 输入 String 类型维度名称：subtask_index |
Instances.N.Dimensions.0.Value | subtask_index | 具体子任务的索引 | 输入子任务的索引，可以从 DescribeJobRuntimeInfo 接口中获取 JobRuntimeInfo.[N].Key 为 SubTasks 的 Value, 使用 base64 解码 |
Instances.N.Dimensions.0.Name | tm_id | Flink 中的taskmanager pod 唯一的名称 | 输入 String 类型维度名称：tm_id |
Instances.N.Dimensions.0.Value | tm_id | 具体pod名称 | 输入具体pod名称，可以从 DescribeJobRuntimeInfo 接口中获取 JobRuntimeInfo.[N].Key 为 TaskManagers 的 Value, 使用 base64 解码 |
入参说明
查询云服务器监控数据，入参取值如下：
&Namespace=QCE/TSTREAM
&Instances.N.Dimensions.0.Name=tjob_id
&Instances.N.Dimensions.0.Value=具体作业 ID
&Instances.N.Dimensions.0.Name=task_id
&Instances.N.Dimensions.0.Value=具体算子ID
&Instances.N.Dimensions.0.Name=subtask_index
&Instances.N.Dimensions.0.Value=具体子任务的索引
&Instances.N.Dimensions.0.Name=tm_id
&Instances.N.Dimensions.0.Value=具体pod名称
