Data Platform/Data Lake/Data Issues
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From Wikitech
All Subpages of Data Platform/Data Lake/Data Issues
- 2021年02月09日 Unique Devices By Family Overcount
- 2021年06月04日 Traffic Data Loss
- 2023年01月08日 Webrequest Data Loss
- 2023-11 eventgate-analytics-external Data Loss
- 2024年09月20日 Unique Devices by Family Inflated Due to Miscategorized Traffic
- 2024年10月10日 Webrequest Data Loss - Clobbered Hadoop Temporary Dir
- 2025年04月11日 Mediawiki History duplicate revisions and excess reverts
- 2025年06月03日 May 2025 spike in bot traffic
- 2025年06月30日 Haproxykafka silently stopped sending request data to Kafka
- 2026年06月10日 Nov 2025 spike in bot traffic
Annotating Superset Dashboards
We recommend the following approaches for excluding or annotating data that contains known data quality issues:
- Use date filters to exclude data from analysis for the affected time period
- For time series visualizations:
- Visually block out the period of the data loss and add annotation with the problem summary and from and to dates. For example:
Wikistats pageviews time series graph with data loss period visually blocked Between June 2021 and January 2022, pageview data was underreported due to caching nodes in the US data centers that had stopped collecting traffic data. For more details see the /2021-06-04 Traffic Data Loss report on Wikitech. Time series graph from Wikistats. - Use overlays to annotate the data. For users of Superset an annotation layer can be created and reused. For example, for the /2021-06-04 Traffic Data Loss, an annotation layer is available called "Pageview Data Loss June 2021-January 2022":
Time series graph of pageviews from Superset, with data loss period annotated using Superset annotation layers. Between June 2021 and January 2022, pageview data was underreported due to caching nodes in the US data centers that had stopped collecting traffic data. For more details see the /2021-06-04 Traffic Data Loss report on Wikitech. Time series graph from Superset, showing annotation layer with mouseover. - For point in time issues, use a data point annotation.
- Visually block out the period of the data loss and add annotation with the problem summary and from and to dates. For example:
- When it is not feasible to remove data from an existing report or dashboard, add an annotation or footnote describing the impact of the data issue.