Beta feature
This functionality is in beta and is subject to change. The design and code is less mature than official generally available features and is being provided as-is with no warranties. Beta features are not subject to the support service level agreement of official generally available features.
What is an Elastic integration?

This integration is powered by Elastic Agent. Elastic Agent is a single, unified agent that you can deploy to hosts or containers to collect data and send it to the Elastic Stack. Behind the scenes, Elastic Agent runs the Beats shippers or Elastic Endpoint required for your configuration. Please refer to our documentation for a detailed comparison between Beats and Elastic Agent.

Prefer to use Beats for this use case? See Filebeat modules for logs or Metricbeat modules for metrics.

Overview

This integration is used to collect Hadoop metrics as follows:

  • Application Metrics
  • Cluster Metrics
  • DataNode Metrics
  • NameNode Metrics
  • NodeManager Metrics

This integration uses Resource Manager API and JMX API to collect above metrics.

application

This data stream collects Application metrics.

An example event for application looks as following:

{
    "@timestamp": "2022-04-04T16:42:03.866Z",
    "agent": {
        "ephemeral_id": "7ebc1f0a-1beb-4519-81b4-60bdcf7449a3",
        "id": "9944acc9-e39f-40e0-a02a-7529cf504db1",
        "name": "docker-fleet-agent",
        "type": "filebeat",
        "version": "8.1.0"
    },
    "data_stream": {
        "dataset": "hadoop.application",
        "namespace": "ep",
        "type": "logs"
    },
    "ecs": {
        "version": "8.1.0"
    },
    "elastic_agent": {
        "id": "9944acc9-e39f-40e0-a02a-7529cf504db1",
        "snapshot": false,
        "version": "8.1.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": "database",
        "created": "2022-04-04T16:42:03.866Z",
        "dataset": "hadoop.application",
        "ingested": "2022-04-04T16:42:07Z",
        "kind": "metric",
        "module": "httpjson",
        "type": "info"
    },
    "hadoop": {
        "application": {
            "allocated": {
                "mb": 2048,
                "v_cores": 1
            },
            "id": "application_1649090491744_0001",
            "memory_seconds": 24502,
            "progress": 0,
            "running_containers": 1,
            "time": {
                "elapsed": 15947,
                "finished": "2022-01-01T00:00:00.000Z",
                "started": "2022-01-01T00:00:00.906Z"
            },
            "vcore_seconds": 11
        }
    },
    "input": {
        "type": "httpjson"
    },
    "tags": [
        "forwarded"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
hadoop.application.allocated.mb
Total memory allocated to the application's running containers (Mb)
long
hadoop.application.allocated.v_cores
The total number of virtual cores allocated to the application's running containers
long
hadoop.application.id
Application ID
keyword
hadoop.application.memory_seconds
The amount of memory the application has allocated
long
hadoop.application.progress
Application progress (%)
long
hadoop.application.running_containers
Number of containers currently running for the application
long
hadoop.application.time.elapsed
The elapsed time since application started (ms)
long
hadoop.application.time.finished
Application finished time
date
hadoop.application.time.started
Application start time
date
hadoop.application.vcore_seconds
The amount of CPU resources the application has allocated
long
input.type
Type of Filebeat input.
keyword
tags
User defined tags
keyword

cluster

This data stream collects Cluster metrics.

An example event for cluster looks as following:

{
    "@timestamp": "2022-04-04T17:22:22.255Z",
    "agent": {
        "ephemeral_id": "a8157f06-f6b6-4eae-b67f-4ad08fa7c170",
        "id": "abf8f8c1-f293-4e16-a8f8-8cf48014d040",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.1.0"
    },
    "data_stream": {
        "dataset": "hadoop.cluster",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.1.0"
    },
    "elastic_agent": {
        "id": "abf8f8c1-f293-4e16-a8f8-8cf48014d040",
        "snapshot": false,
        "version": "8.1.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": "database",
        "dataset": "hadoop.cluster",
        "duration": 50350559,
        "ingested": "2022-04-04T17:22:25Z",
        "kind": "metric",
        "module": "http",
        "type": "info"
    },
    "hadoop": {
        "cluster": {
            "application_main": {
                "launch_delay_avg_time": 2115,
                "launch_delay_num_ops": 1,
                "register_delay_avg_time": 0,
                "register_delay_num_ops": 0
            },
            "node_managers": {
                "num_active": 1,
                "num_decommissioned": 0,
                "num_lost": 0,
                "num_rebooted": 0,
                "num_unhealthy": 0
            }
        }
    },
    "host": {
        "architecture": "x86_64",
        "containerized": true,
        "hostname": "docker-fleet-agent",
        "ip": [
            "172.27.0.7"
        ],
        "mac": [
            "02:42:ac:1b:00:07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "3.10.0-1160.53.1.el7.x86_64",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.3 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "json",
        "period": 60000
    },
    "service": {
        "address": "http://elastic-package-service_hadoop_1:8088/jmx?qry=Hadoop%3Aservice%3DResourceManager%2Cname%3DClusterMetrics",
        "type": "http"
    },
    "tags": [
        "forwarded"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
hadoop.cluster.application_main.launch_delay_avg_time
Application Main Launch Delay Average Time (Milliseconds)
long
hadoop.cluster.application_main.launch_delay_num_ops
Application Main Launch Delay Operations (Number of Operations)
long
hadoop.cluster.application_main.register_delay_avg_time
Application Main Register Delay Average Time (Milliseconds)
long
hadoop.cluster.application_main.register_delay_num_ops
Application Main Register Delay Operations (Number of Operations)
long
hadoop.cluster.applications.completed
The number of applications completed
long
hadoop.cluster.applications.failed
The number of applications failed
long
hadoop.cluster.applications.killed
The number of applications killed
long
hadoop.cluster.applications.pending
The number of applications pending
long
hadoop.cluster.applications.running
The number of applications running
long
hadoop.cluster.applications.submitted
The number of applications submitted
long
hadoop.cluster.containers.allocated
The number of containers allocated
long
hadoop.cluster.containers.pending
The number of containers pending
long
hadoop.cluster.containers.reserved
The number of containers reserved
long
hadoop.cluster.memory.allocated
The amount of memory allocated in MB
long
hadoop.cluster.memory.available
The amount of memory available in MB
long
hadoop.cluster.memory.reserved
The amount of memory reserved in MB
long
hadoop.cluster.memory.total
The amount of total memory in MB
long
hadoop.cluster.node_managers.num_active
Number of Node Managers Active
long
hadoop.cluster.node_managers.num_decommissioned
Number of Node Managers Decommissioned
long
hadoop.cluster.node_managers.num_lost
Number of Node Managers Lost
long
hadoop.cluster.node_managers.num_rebooted
Number of Node Managers Rebooted
long
hadoop.cluster.node_managers.num_unhealthy
Number of Node Managers Unhealthy
long
hadoop.cluster.nodes.active
The number of active nodes
long
hadoop.cluster.nodes.decommissioned
The number of nodes decommissioned
long
hadoop.cluster.nodes.decommissioning
The number of nodes being decommissioned
long
hadoop.cluster.nodes.lost
The number of lost nodes
long
hadoop.cluster.nodes.rebooted
The number of nodes rebooted
long
hadoop.cluster.nodes.shutdown
The number of nodes shut down
long
hadoop.cluster.nodes.total
The total number of nodes
long
hadoop.cluster.nodes.unhealthy
The number of unhealthy nodes
long
hadoop.cluster.virtual_cores.allocated
The number of allocated virtual cores
long
hadoop.cluster.virtual_cores.available
The number of available virtual cores
long
hadoop.cluster.virtual_cores.reserved
The number of reserved virtual cores
long
hadoop.cluster.virtual_cores.total
The total number of virtual cores
long
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

datanode

This data stream collects Datanode metrics.

An example event for datanode looks as following:

{
    "@timestamp": "2022-04-04T18:05:39.491Z",
    "agent": {
        "ephemeral_id": "d35434eb-fdea-41eb-94ed-124bc7e4afe7",
        "id": "b712f448-71fa-4826-999f-6266019438db",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.1.0"
    },
    "data_stream": {
        "dataset": "hadoop.datanode",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.1.0"
    },
    "elastic_agent": {
        "id": "b712f448-71fa-4826-999f-6266019438db",
        "snapshot": false,
        "version": "8.1.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": "database",
        "dataset": "hadoop.datanode",
        "duration": 148436877,
        "ingested": "2022-04-04T18:05:42Z",
        "kind": "metric",
        "module": "http",
        "type": "info"
    },
    "hadoop": {
        "datanode": {
            "bytes": {
                "read": 238743,
                "written": 237315
            }
        }
    },
    "host": {
        "architecture": "x86_64",
        "containerized": true,
        "hostname": "docker-fleet-agent",
        "ip": [
            "172.29.0.4"
        ],
        "mac": [
            "02:42:ac:1d:00:04"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "3.10.0-1160.53.1.el7.x86_64",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.3 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "json",
        "period": 60000
    },
    "service": {
        "address": "http://elastic-package-service_hadoop_1:9864/jmx?qry=Hadoop%3Aname%3DDataNodeActivity%2A%2Cservice%3DDataNode",
        "type": "http"
    },
    "tags": [
        "forwarded"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
hadoop.datanode.blocks.cached
The number of blocks cached
long
hadoop.datanode.blocks.failed.to_cache
The number of blocks that failed to cache
long
hadoop.datanode.blocks.failed.to_uncache
The number of failed blocks to remove from cache
long
hadoop.datanode.bytes.read
Data read
long
hadoop.datanode.bytes.written
Data written
long
hadoop.datanode.cache.capacity
Cache capacity in bytes
long
hadoop.datanode.cache.used
Cache used in bytes
long
hadoop.datanode.dfs_used
Distributed File System Used
long
hadoop.datanode.disk_space.capacity
Disk capacity in bytes
long
hadoop.datanode.disk_space.remaining
The remaining disk space left in bytes
long
hadoop.datanode.estimated_capacity_lost_total
The estimated capacity lost in bytes
long
hadoop.datanode.last_volume_failure_date
The date/time of the last volume failure in milliseconds since epoch
date
hadoop.datanode.volumes.failed
Number of failed volumes
long
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

namenode

This data stream collects Namenode metrics.

An example event for namenode looks as following:

{
    "@timestamp": "2022-03-28T11:36:07.166Z",
    "agent": {
        "ephemeral_id": "1304d85b-b3ba-45a5-ad59-c9ec7df3a49f",
        "id": "adf6847a-3726-4fe6-a202-147021ff3cbc",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.1.0"
    },
    "data_stream": {
        "dataset": "hadoop.namenode",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.1.0"
    },
    "elastic_agent": {
        "id": "adf6847a-3726-4fe6-a202-147021ff3cbc",
        "snapshot": false,
        "version": "8.1.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": "database",
        "dataset": "hadoop.namenode",
        "duration": 341259289,
        "ingested": "2022-03-28T11:36:09Z",
        "kind": "metric",
        "module": "http",
        "type": "info"
    },
    "hadoop": {
        "namenode": {
            "blocks": {
                "corrupt": 0,
                "missing_repl_one": 0,
                "pending_deletion": 0,
                "pending_replication": 0,
                "scheduled_replication": 0,
                "total": 0,
                "under_replicated": 0
            },
            "capacity": {
                "remaining": 11986817024,
                "total": 48420556800,
                "used": 4096
            },
            "estimated_capacity_lost_total": 0,
            "files_total": 9,
            "lock_queue_length": 0,
            "nodes": {
                "num_dead_data": 0,
                "num_decom_dead_data": 0,
                "num_decom_live_data": 0,
                "num_decommissioning_data": 0,
                "num_live_data": 1
            },
            "num_stale_storages": 0,
            "stale_data_nodes": 0,
            "total_load": 0,
            "volume_failures_total": 0
        }
    },
    "host": {
        "architecture": "x86_64",
        "containerized": true,
        "hostname": "docker-fleet-agent",
        "ip": [
            "192.168.160.7"
        ],
        "mac": [
            "02:42:c0:a8:a0:07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "3.10.0-1160.45.1.el7.x86_64",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.3 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "json",
        "period": 60000
    },
    "service": {
        "address": "http://elastic-package-service_hadoop_1:9870/jmx?qry=Hadoop%3Aname%3DFSNamesystem%2Cservice%3DNameNode",
        "type": "http"
    },
    "tags": [
        "forwarded"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
hadoop.namenode.blocks.corrupt
Current number of blocks with corrupt replicas.
long
hadoop.namenode.blocks.missing_repl_one
Current number of missing blocks with replication factor 1
long
hadoop.namenode.blocks.pending_deletion
Current number of blocks pending deletion
long
hadoop.namenode.blocks.pending_replication
Current number of blocks pending to be replicated
long
hadoop.namenode.blocks.scheduled_replication
Current number of blocks scheduled for replications
long
hadoop.namenode.blocks.total
Current number of allocated blocks in the system
long
hadoop.namenode.blocks.under_replicated
Current number of blocks under replicated
long
hadoop.namenode.capacity.remaining
Current remaining capacity in bytes
long
hadoop.namenode.capacity.total
Current raw capacity of DataNodes in bytes
long
hadoop.namenode.capacity.used
Current used capacity across all DataNodes in bytes
long
hadoop.namenode.estimated_capacity_lost_total
An estimate of the total capacity lost due to volume failures
long
hadoop.namenode.files_total
Current number of files and directories
long
hadoop.namenode.lock_queue_length
Number of threads waiting to acquire FSNameSystem lock
long
hadoop.namenode.nodes.num_dead_data
Number of datanodes which are currently dead
long
hadoop.namenode.nodes.num_decom_dead_data
Number of datanodes which have been decommissioned and are now dead
long
hadoop.namenode.nodes.num_decom_live_data
Number of datanodes which have been decommissioned and are now live
long
hadoop.namenode.nodes.num_decommissioning_data
Number of datanodes in decommissioning state
long
hadoop.namenode.nodes.num_live_data
Number of datanodes which are currently live
long
hadoop.namenode.num_stale_storages
Number of storages marked as content stale
long
hadoop.namenode.stale_data_nodes
Current number of DataNodes marked stale due to delayed heartbeat
long
hadoop.namenode.total_load
Current number of connections
long
hadoop.namenode.volume_failures_total
Total number of volume failures across all Datanodes
long
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

node_manager

This data stream collects Node Manager metrics.

An example event for node_manager looks as following:

{
    "@timestamp": "2022-03-28T11:54:32.506Z",
    "agent": {
        "ephemeral_id": "9948a37a-5732-4d7d-9218-0e9cf30c035a",
        "id": "adf6847a-3726-4fe6-a202-147021ff3cbc",
        "name": "docker-fleet-agent",
        "type": "metricbeat",
        "version": "8.1.0"
    },
    "data_stream": {
        "dataset": "hadoop.node_manager",
        "namespace": "ep",
        "type": "metrics"
    },
    "ecs": {
        "version": "8.1.0"
    },
    "elastic_agent": {
        "id": "adf6847a-3726-4fe6-a202-147021ff3cbc",
        "snapshot": false,
        "version": "8.1.0"
    },
    "event": {
        "agent_id_status": "verified",
        "category": "database",
        "dataset": "hadoop.node_manager",
        "duration": 12930711,
        "ingested": "2022-03-28T11:54:35Z",
        "kind": "metric",
        "module": "http",
        "type": "info"
    },
    "hadoop": {
        "node_manager": {
            "allocated_containers": 0,
            "container_launch_duration_avg_time": 169,
            "container_launch_duration_num_ops": 2,
            "containers": {
                "completed": 0,
                "failed": 2,
                "initing": 0,
                "killed": 0,
                "launched": 2,
                "running": 0
            }
        }
    },
    "host": {
        "architecture": "x86_64",
        "containerized": true,
        "hostname": "docker-fleet-agent",
        "ip": [
            "192.168.160.7"
        ],
        "mac": [
            "02:42:c0:a8:a0:07"
        ],
        "name": "docker-fleet-agent",
        "os": {
            "codename": "focal",
            "family": "debian",
            "kernel": "3.10.0-1160.45.1.el7.x86_64",
            "name": "Ubuntu",
            "platform": "ubuntu",
            "type": "linux",
            "version": "20.04.3 LTS (Focal Fossa)"
        }
    },
    "metricset": {
        "name": "json",
        "period": 60000
    },
    "service": {
        "address": "http://elastic-package-service_hadoop_1:8042/jmx?qry=Hadoop%3Aservice%3DNodeManager%2Cname%3DNodeManagerMetrics",
        "type": "http"
    },
    "tags": [
        "forwarded"
    ]
}

Exported fields

FieldDescriptionType
@timestamp
Event timestamp.
date
data_stream.dataset
Data stream dataset.
constant_keyword
data_stream.namespace
Data stream namespace.
constant_keyword
data_stream.type
Data stream type.
constant_keyword
ecs.version
ECS version this event conforms to. ecs.version is a required field and must exist in all events. When querying across multiple indices -- which may conform to slightly different ECS versions -- this field lets integrations adjust to the schema version of the events.
keyword
event.category
This is one of four ECS Categorization Fields, and indicates the second level in the ECS category hierarchy. event.category represents the "big buckets" of ECS categories. For example, filtering on event.category:process yields all events relating to process activity. This field is closely related to event.type, which is used as a subcategory. This field is an array. This will allow proper categorization of some events that fall in multiple categories.
keyword
event.dataset
Name of the dataset. If an event source publishes more than one type of log or events (e.g. access log, error log), the dataset is used to specify which one the event comes from. It's recommended but not required to start the dataset name with the module name, followed by a dot, then the dataset name.
keyword
event.kind
This is one of four ECS Categorization Fields, and indicates the highest level in the ECS category hierarchy. event.kind gives high-level information about what type of information the event contains, without being specific to the contents of the event. For example, values of this field distinguish alert events from metric events. The value of this field can be used to inform how these kinds of events should be handled. They may warrant different retention, different access control, it may also help understand whether the data coming in at a regular interval or not.
keyword
event.module
Name of the module this data is coming from. If your monitoring agent supports the concept of modules or plugins to process events of a given source (e.g. Apache logs), event.module should contain the name of this module.
keyword
event.type
This is one of four ECS Categorization Fields, and indicates the third level in the ECS category hierarchy. event.type represents a categorization "sub-bucket" that, when used along with the event.category field values, enables filtering events down to a level appropriate for single visualization. This field is an array. This will allow proper categorization of some events that fall in multiple event types.
keyword
hadoop.node_manager.allocated_containers
Containers Allocated
long
hadoop.node_manager.container_launch_duration_avg_time
Container Launch Duration Average Time (Seconds)
long
hadoop.node_manager.container_launch_duration_num_ops
Container Launch Duration Operations (Operations)
long
hadoop.node_manager.containers.completed
Containers Completed
long
hadoop.node_manager.containers.failed
Containers Failed
long
hadoop.node_manager.containers.initing
Containers Initializing
long
hadoop.node_manager.containers.killed
Containers Killed
long
hadoop.node_manager.containers.launched
Containers Launched
long
hadoop.node_manager.containers.running
Containers Running
long
service.address
Address where data about this service was collected from. This should be a URI, network address (ipv4:port or [ipv6]:port) or a resource path (sockets).
keyword
service.type
The type of the service data is collected from. The type can be used to group and correlate logs and metrics from one service type. Example: If logs or metrics are collected from Elasticsearch, service.type would be elasticsearch.
keyword
tags
List of keywords used to tag each event.
keyword

Changelog

VersionDetails
0.2.0
Enhancement View pull request
Add dashboard and visualizations for Hadoop.
0.1.1
Enhancement View pull request
Update SSL and proxy configuration for application data stream.
0.1.0
Enhancement View pull request
Add namenode data stream for Hadoop.

Enhancement View pull request
Add node_manager data stream, visualizations and Dashboards for Hadoop.

Enhancement View pull request
Add datanode data stream for Hadoop.

Enhancement View pull request
Add cluster metrics data stream for Hadoop.

Enhancement View pull request
Add Hadoop integration with application data stream.
Last updated: Jun 3rd, 2022