Status

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

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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 sort out a table containing the correspondence between configuration and metriccorrelate 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.

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.

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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

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REST API.

Frontend Design

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

The previous metrics are moved into 'Advanced' since maybe some users still need them.

Image Added

Detail view

Image AddedImage Removed

REST API Design

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Memory Configuration

The TaskManager's memory configuration will be exposed through {{

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/taskmanagers/:taskmanagerid}}. A proposed REST respond is shown in the code block below:

{
  "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

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TaskExecutorn

1. TaskManagerResourceInfo is introduced as a POJO containing the relevant values proposed in the REST response.
2. 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.
3. The TaskManagerResourceInfo will be added along with HardwareDescription in ResourceManager::requestTaskManagerInfo(ResourceId, Time).

Step 2: Introduce new metric for memory usage of NetworkBufferPoolNetworkBufferPool 

1. add shuffle memory's size metric

   Code Block

   language	java

   public long getTotalMemorySize() { return 1L * getTotalNumberOfMemorySegments() * memorySegmentSize; } public long getUsedMemorySize() { return getTotalMemorySize() - (getNumberOfAvailableMemorySegments() * memorySegmentSize); }

2. update NettyShuffleMetricFactory#registerShuffleMetrics

   Code Block

   language	java

   private static final String METRIC_TOTAL_MEMORY_IN_BYTES = "TotalMemory"; private static final String METRIC_USED_MEMORY_IN_BYTES = "UsedMemory"; // ... private static void registerShuffleMetrics( String groupName, MetricGroup metricGroup, NetworkBufferPool networkBufferPool) { MetricGroup networkGroup = metricGroup.addGroup(groupName); networkGroup.<Integer, Gauge<Integer>>gauge(METRIC_TOTAL_MEMORY_SEGMENT, networkBufferPool::getTotalNumberOfMemorySegments); networkGroup.<Integer, Gauge<Integer>>gauge(METRIC_AVAILABLE_MEMORY_SEGMENT, networkBufferPool::getNumberOfAvailableMemorySegments); // === new === networkGroup.<Long, Gauge<Long>>gauge(METRIC_TOTAL_MEMORY_IN_BYTES, networkBufferPool::getTotalMemorySize); networkGroup.<Long, Gauge<Long>>gauge(METRIC_USED_MEMORY_IN_BYTES, networkBufferPool::getUsedMemorySize); }

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

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.

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add default memory type in MemoryManager

public static final MemoryType DEFAULT_MEMORY_TYPE = MemoryType.OFF_HEAP;

add register ManagedMemoryUsage in TaskExecutor#requestSlot:

public long getManagedMemoryUsed() {
	return this.taskSlotTable.getAllocatedSlots().stream().mapToLong(
		slot ->
			slot.getMemoryManager().getMemorySizeByType(MemoryManager.DEFAULT_MEMORY_TYPE) - 
				slot.getMemoryManager().availableMemory(MemoryManager.DEFAULT_MEMORY_TYPE)
	).sum();

}

add instantiateMemoryManagerMetrics in MetricUtils

public static void instantiateMemoryManagerMetrics(
	
	MetricGroup statusMetricGroup, 
		TaskExecutor taskExecutor) {
	checkNotNull(statusMetricGroup);

	MetricGroup memoryManagerGroup = statusMetricGroup.addGroup("Managed").addGroup("Memory");
	memoryManagerGroup.<Long, Gauge<Long>>gauge("TotalCapacity",  taskExecutor::getManagedMemoryTotal);
	memoryManagerGroup.<Long, Gauge<Long>>gauge("MemoryUsed", taskExecutor::getManagedMemoryUsed);
}

Step 4: Add Metaspace metrics 

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 

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 .

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Step 4: Expose new metrics to REST interface

TaskManagerDetailsHandler#handleRequest  can be extended to cover also the newly added metrics:

1. TaskManagerMetricsInfo  needs to be extended adding members for the newly added fields:

2. TaskManagerDetailsHandler::createTaskManagerMetricsInfo(MetricsStore.TaskManagerMetricStore) can be used to initialize the fields.
   

Follow-Ups

• The /metrics endpoint of each TaskManager could be split up into multiple endpoints:
• /configuration containing the static values like configuration and hardware description
/metrics containing the volatile values like the metrics and slot information

Test Plan

Existing tests are updated to verify feature.