MRS MapReduce

Functions

The MRS MapReduce node is used to execute a predefined MapReduce program on MRS.

MapReduce is a programming model used for parallel computation of large-scale data sets (larger than 1 TB). Data computed by MapReduce comes from multiple data sources, mostly HDFS. MapReduce uses the high throughput performance of HDFS to read a large amount of data for computing and stores the processed data in HDFS.

Parameters

Table 1 and Table 2 describe the parameters of the MRS MapReduce node.

**Table 1** Parameters of MRS MapReduce nodes
Parameter	Mandatory	Description
Node Name	Yes	Name of a node. The name must contain 1 to 128 characters, including only letters, numbers, underscores (_), hyphens (-), slashes (/), less-than signs (<), and greater-than signs (>).
MRS Cluster Name	Yes	Name of the MRS cluster. To create an MRS cluster, use either of the following methods: Click . On the Clusters page, create an MRS cluster. Go to the MRS console to create an MRS cluster.
MapReduce Job Name	Yes	MRS job name. It can contain a maximum of 64 characters. Only letters, digits, hyphens (-), and underscores (_) are allowed. NOTE: The job name cannot contain Chinese characters or more than 64 characters. If the job name does not meet requirements, the MRS job will fail to be submitted.
JAR Package	Yes	Select a JAR package. Before selecting a JAR package, upload the JAR package to the OBS bucket, create a resource on the Manage Resource page, and add the JAR package to the resource management list. For details, see Creating a Resource. NOTE: If you configured an MRS tenant plane connection and selected keytab for MRS Authentication Type in Management Center, you cannot select an OBS JAR package. DataArts Studio and MRS are not connected to the same OBS. MRS cannot identify the OBS domain name transferred by DataArts Studio. As a result, an error message is displayed, indicating that the domain name cannot be accessed.
JAR File Parameters	No	Parameters of the JAR package. You can set JAR package parameters as required.
Input Data Path	No	Path where the input data is stored
Output Data Path	No	Path where the output data is to be stored

**Table 2** Advanced parameters
Parameter	Mandatory	Description
Node Status Polling Interval (s)	Yes	How often the system check completeness of the node. The value ranges from 1 to 60 seconds.
Max. Node Execution Duration	Yes	Execution timeout interval for the node. If retry is configured and the execution is not complete within the timeout interval, the node will be executed again.
Retry upon Failure	Yes	Whether to re-execute a node if it fails to be executed. Possible values: Yes: The node will be re-executed, and the following parameters must be configured: Retry upon Timeout Maximum Retries Retry Interval (seconds) No: The node will not be re-executed. This is the default setting. NOTE: If retry is configured for a job node and the timeout duration is configured, the system allows you to retry a node when the node execution times out. If a node is not re-executed when it fails upon timeout, you can go to the Default Configuration page to modify this policy. Retry upon Timeout is displayed only when Retry upon Failure is set to Yes.
Policy for Handling Subsequent Nodes If the Current Node Fails	Yes	Operation that will be performed if the node fails to be executed. Possible values: Suspend execution plans of the subsequent nodes: stops running subsequent nodes. The job instance status is Failed. End the current job execution plan: stops running the current job. The job instance status is Failed. Go to the next node: ignores the execution failure of the current node. The job instance status is Failure ignored. Suspend the current job execution plan: If the current job instance is in abnormal state, the subsequent nodes of this node and the subsequent job instances that depend on the current job are in waiting state.
Enable Dry Run	No	If you select this option, the node will not be executed, and a success message will be returned.
Task Groups	No	Select a task group. If you select a task group, you can control the maximum number of concurrent nodes in the task group in a fine-grained manner in scenarios where a job contains multiple nodes, a data patching task is ongoing, or a job is rerunning.