Purpose
Please provide as much context as possible as well as what the produced insights or services will be used for.
Data SREs have provided a regular output of logs from dumps.wikimedia.org on stat1011 that can be found in srv/log/webrequest/archive/dumps.wikimedia.org. This information has various uses for WMF and WMDE teams on how the dump data for the projects that they work on is being accessed. This task suggests moving these log files to HDFS and creating DAGs to import the data into the data lake and generate monthly request metrics across all dumps.
Current related task: T399808: [Analytics] Baseline metrics for data dumps
Prior related task: T383175: Analyze Dumps Usage Through Apache Logs
Prior related work: GitLab:data-engineering/dumps-log-analysis
Desired Outputs
The desired outputs of this task are listed and confirmed as being finished below.
Please note: WMDE would be happy to do any of the work that is within our capacities for this task. The initial idea is that the DAGs suggested below are shared infrastructure, so with Data Engineering approval the merge request would go to GitLab:data-engineering/airflow-dags/main.
- The dump logs are moved to a location in HDFS where they can be accessed by Airflow processes
- Support from Data SREs needed
- A daily DAG is written to import the log data from HDFS into a table in the data lake
- Code based on GitLab:data-engineering/dumps-log-analysis is operationalized via a SparkOperator in the DAG
- A monthly DAG is written to calculate usage metrics across all dumps and write them to a table in the data lake
- Input table is the above HDFS import table via an ExternalTaskSensor and daily_execution_dates_of_month
- We need this to run on the second day of the month as the log file for the first day has requests from the one for the last day of the month (0 0 2 * * )
Deadline
Please make the time sensitivity of this request clear with a date that it should be completed by. If there is no specific date, then the task will be triaged based on its priority.
DD.MM.YYYY