Verification

• Verifying data

  The database comparison methods include database content comparison, object comparison, and row comparison. The file comparison methods include file quantity comparison, size comparison, and content comparison. For details about data comparison methods, see Data Verification.

• Verifying tasks

  Following the migration of big data tasks, it is imperative to ensure that these workloads execute successfully, produce accurate outcomes, and meet defined performance benchmarks. Task verification generally involves verifying the following key aspects:

• Verifying the task execution success rate

  After the task migration is complete, a thorough verification of the migrated big data tasks is required. This includes executing tasks and meticulously assessing their execution success rate. During this verification process, close attention should be paid to task statuses, logs, and any encountered errors or exceptions. Tasks that fail to execute correctly necessitate detailed investigation and debugging to identify and rectify the underlying faults.

• Verifying the consistency of task execution results

  Verify the consistency of execution results generated by the big data tasks by comparing the output data of tasks running on both the new and legacy big data platforms. Consistency verification can be performed using specialized comparison tools, custom data verification scripts, or manual inspection. Data inconsistencies found may necessitate a review of data conversion processes, data formats, or data processing logic implemented during the migration, followed by appropriate rectification and adjustments.

• Verifying the task execution performance

  Following the migration, evaluate the task execution performance, including metrics such as runtime, resource utilization, and concurrency. By monitoring key execution and performance metrics, you can determine whether the post-migration task performance meets the established expectations. Identified performance anomalies may require adjustments to task configuration parameters, optimization of the task code, or reconsideration of resource allocation strategies.

During the job verification process, leveraging monitoring tools, log analysis techniques, and data verification utilities is crucial to ensure the overall reliability and stability of the big data tasks after migration.