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腾讯云可观测平台 流计算 Oceanus 监控指标

• 腾讯云产品

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。

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一、命名空间

Namespace = QCE/TSTREAM

二、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 Taskmanager 上报的 kafka 最大 lag 指标 TaskManager 上报的 Kafka 最大 lag 指标 None tjob_id [ 60s, max ]
[ 300s, max ]
[ 3600s, max ]
[ 86400s, max ]
RecordsLagMaxAvg TaskManager 上报的 kafka 最大 lag 指标的均值 TaskManager 上报的 Kafka 最大 lag 指标的均值 None tjob_id [ 60s, avg ]
[ 300s, avg ]
[ 3600s, avg ]
[ 86400s, avg ]
RecordsLagMaxMin TaskManager 上报的 kafka 最大 lag 指标最小值 TaskManager 上报的 Kafka 最大 lag 指标最小值 None tjob_id [ 60s, min ]
[ 300s, min ]
[ 3600s, min ]
[ 86400s, min ]
RecordsLagMaxSum TaskManager 上报的 kafka 最大 lag 指标的求和值 TaskManager 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 ]
ClusterTotalSnapshotCount Snapshot 总次数 集群 Snapshot 总次数 Count cluster_id [ 60s, last ][ 300s, last ]
ClusterTotalCommitCount 集群 Commit 总次数 集群 Commit 总次数 Count cluster_id [ 60s, last ][ 300s, last ]
ClusterTotalCommitSuccessCount 集群 Commit 成功总次数 集群 Commit 成功总次数 Count cluster_id [ 60s, last ][ 300s, last ]
ClusterTotalCommitFailedCount 集群 Commit 失败总次数 集群 Commit 失败总次数 Count cluster_id [ 60s, last ][ 300s, last ]
ClusterTotalRestartCount 集群异常重启总次数 集群 Worker 重启总次数 Count cluster_id [ 60s, last ][ 300s, last ]
ClusterCurActivePodNum 当前健康 Pod 数量 集群当前活跃 Pod 数量 None cluster_id [ 60s, last ][ 300s, last ]
ClusterStorageTotalUsed 集群当前已使用存储总量 集群当前已使用存储总量 Bytes cluster_id [ 60s, last ][ 300s, last ]
ClusterStorageTotalUsedPercent 集群当前已使用存储率 集群当前已使用存储率 % cluster_id [ 60s, last ][ 300s, last ]
TableCommitSuccessCount 表 Commit 成功次数 表的提交成功次数 Count cluster_iddatabase_nametable_name [ 60s, last ][ 300s, last ]
TableCommitFailedCount 表 Commit 失败次数 表的提交失败次数 Count cluster_iddatabase_nametable_name [ 60s, last ][ 300s, last ]
TableSizeBytes 表大小 表所占存储大小 Bytes cluster_iddatabase_nametable_name [ 60s, last ][ 300s, last ]
TableMetaSizeBytes 表元数据大小 表所占元数据大小 Bytes cluster_iddatabase_nametable_name [ 60s, last ][ 300s, last ]
TableTotalOpenedBucketCount 表打开的 bucket 数量 表当前所有已打开的 bucket 数量 None cluster_iddatabase_nametable_name [ 60s, last ][ 300s, last ]

三、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 输入具体作业 ID ，可从 DescribeJobs 中获取 JobId 字段
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
Instances.N.Dimensions.0.Name cluster_id 集群 ID 的维度名称 输入 String 类型维度名称：cluster_id
Instances.N.Dimensions.0.Value cluster_id 具体集群 ID 输入具体集群 ID，可从 DescribeClusters 中的 OwnerClusterGroupSerialId 获取的值就是 ClusterId 字段
Instances.N.Dimensions.0.Name database_name database_name 的维度名称 输入 String 类型维度名称：database_name
Instances.N.Dimensions.0.Value database_name 具体的数据库名称 Setats 数据库名称，例如：default
Instances.N.Dimensions.0.Name table_name table_name 的维度名称 输入 String 类型维度名称：table_name
Instances.N.Dimensions.0.Value table_name 具体的数据表名称 Setats 表名称，例如：test_table

四、入参说明

&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

&Instances.N.Dimensions.0.Name=cluster_id

&Instances.N.Dimensions.0.Value=具体 ClusterId 字段

&Instances.N.Dimensions.0.Name=database_name

&Instances.N.Dimensions.0.Value=Setats 数据库名称

&Instances.N.Dimensions.0.Name=table_name

&Instances.N.Dimensions.0.Value=Setats 表名称

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