Status

Current state: [Under Discussion]

Discussion threads:

FLIP-75 discussion about the initial design
FLIP-102 discussion after splitting up FLIP-75 into sub-flips

JIRA: Unable to render Jira issues macro, execution error.

Released: <Flink Version>

Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

Motivation

FLIP-49 has been accepted and merged in Flink 1.10, the metric in current task manager detail page could not correspond well to the design of FLIP-49.

The memory model which is exposed through the configuration parameters should be visualized in the same way in the TaskManager's details.

Proposed Changes

According to FLIP-49, we can correlate the configuration parameters and the metrics partially.

JVM Metrics

These JVM metrics are exposed and can be used through the TaskManager's metrics REST API.

JVM	Metric	Used key	Total key
Heap	Status.JVM.Memory.Heap	Used	Max
Direct	Status.JVM.Memory.Direct	Used	Max
Metaspace	Status.JVM.Memory.Metaspace Unable to render Jira issues macro, execution error.	Used	Max
Mapped	Status.JVM.Memory.Mapped	MemoryUsed	TotalCapacity
NonHeap	Status.JVM.Memory.NonHeap	MemoryUsed	TotalCapacity

Memory Configuration

Flink's memory model (as described in org.apache.flink.runtime.clusterframework.TaskExecutorProcessSpec) can be mapped to the following Flink configuration parameters. There are a few that have a correlating Flink metric.

Flink Memory Model	Flink configuration¹	Effective Configuration REST API²	Metric³	Used key	Total key
Framework Heap	`taskmanager.memory.framework.heap.size`	memoryConfiguration.frameworkHeap	Status.JVM.Memory.Heap	Used	Max
Task Heap	`taskmanager.memory.task.heap.size`	memoryConfiguration.taskHeap	Status.JVM.Memory.Heap	Used	Max
Framework OffHeap	`taskmanager.memory.framework.off-heap.size`	memoryConfiguration.frameworkOffHeap	-	-	-
Task OffHeap	`taskmanager.memory.task.off-heap.size`	memoryConfiguration.taskOffHeap	-	-	-
Network Memory	`taskmanager.memory.network.min` `taskmanager.memory.network.max`	memoryConfiguration.networkMemory	Status.Shuffle.Netty Unable to render Jira issues macro, execution error.	UsedMemory	TotalMemory
Managed Memory	`taskmanager.memory.managed.size`	memoryConfiguration.managedMemory	Status.Flink.Memory.Managed Unable to render Jira issues macro, execution error.	Used	Total
JVM Metaspace	`taskmanager.memory.jvm-metaspace.size`	memoryConfiguration.jvmMetaspace	Status.JVM.Memory.Metaspace	Used	Max
JVM Overhead	`taskmanager.memory.jvm-overhead.min` `taskmanager.memory.jvm-overhead.max`	memoryConfiguration.jvmOverhead	-	-	-

¹ These are the configuration parameters used in the Flink configuration.
² These are the Json paths to address the properties in the HTTP REST API response. Additionally, memoryConfiguration.totalFlinkMemory and totalProcessMemory are exposed through the REST API.
³ The metrics which are exposed through the TaskManager's metrics REST API.

Frontend Design (out-dated)

Redesign the task manager metric page, this would allow users to more clearly understand the relationship between these metrics.

REST API Design

Memory Configuration

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The TaskManager's memory configuration will be exposed through {{/taskmanagers/:taskmanagerid}}. A proposed REST respond is shown in the code block below:

JSON Schema of response

{
  "type" : "object",
  "id" : "urn:jsonschema:org:apache:flink:runtime:rest:messages:taskmanager:TaskManagerDetailsInfo",
  "properties" : {
    "id" : {
      "type" : "any"
    },
    "path" : {
      "type" : "string"
    },
    "dataPort" : {
      "type" : "integer"
    },
    "timeSinceLastHeartbeat" : {
      "type" : "integer"
    },
    "slotsNumber" : {
      "type" : "integer"
    },
    "freeSlots" : {
      "type" : "integer"
    },
    "hardware" : {
      "type" : "object",
      "id" : "urn:jsonschema:org:apache:flink:runtime:instance:HardwareDescription",
      "properties" : {
        "cpuCores" : {
          "type" : "integer"
        },
        "physicalMemory" : {
          "type" : "integer"
        },
        "freeMemory" : {
          "type" : "integer"
        },
        "managedMemory" : {
          "type" : "integer"
        }
      }
    },
    "memoryConfiguration" : {
      "type" : "object",
      "id" : "urn:jsonschema:org:apache:flink:runtime:rest:messages:taskmanager:TaskExecutorMemoryConfiguration",
      "properties" : {
        "frameworkHeap" : {
          "type" : "long"
        },
        "frameworkOffHeap" : {
          "type" : "long"
        },
        "taskHeap" : {
          "type" : "long"
        },
        "taskOffHeap" : {
          "type" : "long"
        },
        "networkMemory" : {
          "type" : "long"
        },
        "managedMemory" : {
          "type" : "long"
        },
        "jvmMetaspace" : {
          "type" : "long"
        },
        "jvmOverhead" : {
          "type" : "long"
        },
        "totalFlinkMemory" : {
          "type" : "long"
        }
        "totalProcessMemory" : {
          "type" : "long"
        }
      }
    },
    "metrics" : {
      "type" : "object",
      "id" : "urn:jsonschema:org:apache:flink:runtime:rest:messages:taskmanager:TaskManagerMetricsInfo",
      "properties" : {
        "heapUsed" : {
          "type" : "integer"
        },
        "heapCommitted" : {
          "type" : "integer"
        },
        "heapMax" : {
          "type" : "integer"
        },
        "metaspaceUsed" : {
          "type" : "integer"
        },
        "metaspaceCommitted" : {
          "type" : "integer"
        },
        "metaspaceMax" : {
          "type" : "integer"
        },      
        "nonHeapUsed" : {
          "type" : "integer"
        },
        "nonHeapCommitted" : {
          "type" : "integer"
        },
        "nonHeapMax" : {
          "type" : "integer"
        },
        "directCount" : {
          "type" : "integer"
        },
        "directUsed" : {
          "type" : "integer"
        },
        "directMax" : {
          "type" : "integer"
        },
        "mappedCount" : {
          "type" : "integer"
        },
        "mappedUsed" : {
          "type" : "integer"
        },
        "mappedMax" : {
          "type" : "integer"
        },
        "memorySegmentsAvailable" : {
          "type" : "integer"
        },
        "memorySegmentsTotal" : {
          "type" : "integer"
        },
        "managedMemoryUsed" : {
          "type" : "long"
        },
        "managedMemoryTotal" : {
          "type" : "long"
        },
        "networkMemoryUsed" : {
          "type" : "long"
        },
        "networkMemoryTotal" : {
          "type" : "long"
        },
        "garbageCollectors" : {
          "type" : "array",
          "items" : {
            "type" : "object",
            "id" : "urn:jsonschema:org:apache:flink:runtime:rest:messages:taskmanager:TaskManagerMetricsInfo:GarbageCollectorInfo",
            "properties" : {
              "name" : {
                "type" : "string"
              },
              "count" : {
                "type" : "integer"
              },
              "time" : {
                "type" : "integer"
              }
            }
          }
        }
      }
    }
  }
}

Metrics exposure

The newly introduced metrics can be accessed through the metrics REST endpoint.

Implementation Proposal

Step 1: Expose effective configuration parameters of TaskExecutorn

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TaskManagerResourceInfo is introduced as a POJO containing the relevant values proposed in the REST response.
The TaskManagerResourceInfo is initialized when initializing the TaskExecutor in the same way as we do it with the HardwareDescription. It will be handed over in the same way through TaskExecutorRegistry → WorkerRegistration.
The TaskManagerResourceInfo will be added along with HardwareDescription in ResourceManager::requestTaskManagerInfo(ResourceId, Time).

Step 2: Introduce new metric for memory usage of NetworkBufferPool

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add shuffle memory's size metric
update NettyShuffleMetricFactory#registerShuffleMetrics

Step 3: Introduce new metrics for Task's managed memory usage

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We still have to discuss how to implement that in the right way. A brief proposal is the following one:

We would have to introduce a new metric that represents the aggregated memory usage of each TaskSlot . The aggregation can be maintained in the TaskExecutor.

Step 4: Add Metaspace metrics

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There are no metrics present, yet, monitoring the JVM's Metaspace pool. The newly introduced metrics are going to be exposed through the /taskmanagers/metrics REST API.

Step 5: Update TaskManager's details page

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The web UI has to be updated as proposed above.

Follow-Ups

Create a separate independent endpoint for the effective memory configuration.
Deprecate the metrics sub-record returned by /taskmanagers/:taskmanagerid . The metrics endpoint can be used instead. This would simplify the TaskManagerDetailsHandler .

Test Plan

Existing tests are updated to verify feature.

Page tree

FLIP-102: Add More Metrics to TaskManager

Status

Motivation

Proposed Changes

JVM Metrics

Memory Configuration

Frontend Design (out-dated)

REST API Design

Memory Configuration

Metrics exposure

Implementation Proposal

Step 1: Expose effective configuration parameters of TaskExecutorn

Step 2: Introduce new metric for memory usage of NetworkBufferPool

Step 3: Introduce new metrics for Task's managed memory usage

Step 4: Add Metaspace metrics

Step 5: Update TaskManager's details page

Follow-Ups

Test Plan