Updated on 2022-02-22 GMT+08:00

Overview

You can quickly view the status of all clusters and jobs by viewing the dashboard information, and obtain relevant MRS documents from Help in the left navigation pane on the MRS console.

MRS is used to manage and analyze massive data. It is easy to use. You can create a cluster and add MapReduce, Spark, and Hive jobs to the cluster to analyze and process user data. After being processed, you can transmit the data in SSL encryption mode to OBS to ensure data integrity and confidentiality.

Cluster Status

Table 1 lists the statuses of all MRS clusters after you log in to the MRS management console.
Table 1 Cluster status

Status

Description

Starting

If a cluster is being created, the cluster is in the Starting state.

Running

If a cluster is created successfully and all components in the cluster are normal, the cluster is in the Running state.

Scaling out

If the Core or Task node in a cluster is being added, the cluster is in the Scaling out state.

NOTE:

If the cluster scale-out fails, you can add node to the cluster again.

Scaling in

If you stop, delete, change or reinstall the OSs of cluster nodes, and modify the specifications of the cluster node, the cluster nodes are being terminated. Then, the cluster is in the Scaling in state.

Abnormal

If some components in a cluster are abnormal, the cluster is Abnormal.

Terminating

If a cluster node is being terminated, the cluster is in the Terminating state.

Terminated

The cluster has been terminated. This parameter is displayed only in Cluster History.

Job Status

Table 2 describes the status of jobs that you execute after logging in to the MRS management console.

Table 2 Job status

Status

Description

Accepted

Initial status of a job after it is successfully submitted.

Running

A job is being executed.

Completed

A job has been executed and completed successfully.

Terminated

A job is stopped during execution.

Abnormal

An error occurs during job execution or job execution fails.