What is the execution process of Debian Hadoop

The Hadoop task execution process mainly includes the following steps:

1. Submit job : The user uses the command line tools or API provided by Hadoop on the client machine to build the task execution environment and submit the task to YARN (Hadoop's resource manager).

2. Resource application : After YARN receives the task submission request, it will apply for resources from the nodes in the cluster based on the resources required by the task (such as memory, CPU, etc.).

3. Task Start : Once the resource allocation is completed, YARN will send the task's startup command to the corresponding node. On the node, NodeManager is responsible for starting the task container and monitoring the execution status of the task.

4. Execute Map Tasks : After the task container is started, the application in it will load the code and data required by the task and start performing the calculations in the Map stage. The Map task is responsible for converting the input data into intermediate key-value pairs.

5. Execute Reduce Task : After the Map task is completed, the Reduce Task begins to be executed. The Reduce task is responsible for merging and aggregating the output of the Map task to generate the final result.

6. Output result : After the Reduce task is completed, the result of the task will be written into the specified output path for subsequent use and analysis.

7. Follow-up processing : After the task is completed, some follow-up processing work needs to be carried out, such as output data checking, resource release, logging and monitoring, etc., to ensure the integrity of the task and the availability of data.

The above is the basic execution process of Debian Hadoop tasks. It should be noted that the specific execution process and configuration of Hadoop may be different if the version of Hadoop is different.

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