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...posals/data_normalization/20240227-implementation_plan_catalog_data_cleaning.md
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# 2024-02-27 Implementation Plan: Catalog Data Cleaning | ||
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**Author**: @krysal | ||
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## Reviewers | ||
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- [ ] TBD | ||
- [ ] TBD | ||
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## Project links | ||
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<!-- Enumerate any references to other documents/pages, including milestones and other plans --> | ||
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- [Project Thread](https://github.com/WordPress/openverse/issues/430) | ||
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This project does not have a project proposal because the scope and rationale of | ||
the project are clear, as defined in the project thread. In doubt, check the | ||
[Expected Outcomes](#expected-outcomes) section below. | ||
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## Overview | ||
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One of the steps of the [data refresh process for images][img-data-refresh] is | ||
cleaning the data that is not fit for production. This process is triggered | ||
weekly by an Airflow DAG, and then runs in the Ingestion Server, taking | ||
approximately just over **20 hours** to complete, according to a inspection of | ||
latest executions. The cleaned data is only saved to the API database, which is | ||
replaced each time during the same data refresh, causing it to have to be | ||
repeated each time to make the _same_ corrections. | ||
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This cleaning process was designed this way to speed the rows update up since | ||
the relevant part was to provide the correct data to users via the API. Most of | ||
the rows affected were added previous to the creation of the `MediaStore` class | ||
in the Catalog (possibly by the discontinued CommonCrawl ingestion) which is | ||
nowadays responsible for validating the provider data. However, it entails a | ||
problem of wasting resources both in time, which continues to increase, and in | ||
the machines (CPU) it uses, which could easily be avoided making the changes | ||
permanent by saving them in the upstream database. | ||
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This implementation plan (IP) describe a path to save these resources and | ||
finally normalise the catalog DB data, pushing cleaning steps to the media | ||
storage class and/or providers API DAGs. | ||
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[img-data-refresh]: | ||
https://github.com/WordPress/openverse-catalog/blob/main/DAGs.md#image_data_refresh | ||
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## Expected Outcomes | ||
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<!-- List any succinct expected products from this implementation plan. --> | ||
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- The catalog database (upstream) preserves the cleaned data results of the | ||
current Ingestion Server's cleaning steps | ||
- The image Data Refresh process is simplified by reducing the cleaning steps | ||
time to nearly zero (and optionally removing them). | ||
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## Step-by-step plan | ||
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The cleaning functions that the Ingestion Server applies are already ported to | ||
the Catalog in the `MediaStore` class: see its `_tag_blacklisted` method (which | ||
should probably be renamed) and the [url utilities][url_utils] file. The only | ||
part that it's not there and can't be ported is the filtering of low-confidence | ||
tags, since provider scripts don't save an "accuracy" by tag. | ||
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With this the plan then starts in the Ingestion Server with the following steps: | ||
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1. [Save TSV files of cleaned data to AWS S3](#save-tsv-files-of-cleaned-data-to-aws-s3) | ||
1. [Make and run a batched update DAG for one-time cleanup](#make-and-run-a-batched-update-dag-for-one-time-cleanup) | ||
1. [Run an image Data Refresh to confirm cleaning time is reduced](#run-an-image-data-refresh-to-confirm-cleaning-time-is-reduced) | ||
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[url_utils]: | ||
https://github.com/WordPress/openverse/blob/a930ee0f1f116bac77cf56d1fb0923989613df6d/catalog/dags/common/urls.py | ||
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## Step details | ||
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### Save TSV files of cleaned data to AWS S3 | ||
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In a previous exploration, it was set to store TSV files of the cleaned data in | ||
the form of `<identifier> <cleaned_field>`, which can be used later to perform | ||
the updates efficiently in the catalog DB, which only had indexes for the | ||
`identifier` field. These files are saved to the disk of the Ingestion Server | ||
EC2 instances, and worked fine for files with URL corrections since this type of | ||
fields is relatively short, but became a problem when trying to save tags, as | ||
the file turned too large and filled up the disk, causing problems to the data | ||
refresh execution. | ||
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The alternative is to upload TSV files to the Amazon Simple Storage Service | ||
(S3), creating a new bucket or using `openverse-catalog` with a subfolder. The | ||
benefit of using S3 buckets is that they have streaming capabilities and will | ||
allow us to read the files in chunks later if necessary for performance. The | ||
downside is that objects in S3 don't allow appending, so it may require to | ||
upload files with different part numbers or evaluate if the [multipart upload | ||
process][aws_mpu] will serve us here. | ||
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[aws_mpu]: | ||
https://docs.aws.amazon.com/AmazonS3/latest/userguide/mpuoverview.html | ||
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| timestamp (UTC) | 'url' | 'creator_url' | 'foreign_landing_url' | 'tags' | | ||
| ------------------- | :---: | :-----------: | :-------------------: | :----: | | ||
| 2024-02-27 04:05:26 | 22156 | 9035458 | 8809213 | 0 | | ||
| 2024-02-20 04:06:56 | 22157 | 9035456 | 8809209 | 0 | | ||
| 2024-02-13 04:41:22 | 22155 | 9035451 | 8809204 | 0 | | ||
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The previous table shows the number of records cleaned by field for last runs at | ||
the moment of writing this IP, except for tags, which we don't have accurate | ||
registries since file saving was disabled. | ||
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### Make and run a batched update DAG for one-time cleanup | ||
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A batched catalog cleaner DAG (or potentially a `batched_update_from_files`) | ||
should take the files of the previous step to perform an arbitrary batched | ||
update on a Catalog media table, while handling deadlocking and timeout | ||
concerns, similar to the [batched_update][batched_update]. A | ||
[proof of concept PR](https://github.com/WordPress/openverse/pull/3601) proved | ||
to work locally for URL fields, so it will just need to be adapted to the tags. | ||
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[batched_update]: ./../../../catalog/reference/DAGs.md#batched_update | ||
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### Run an image Data Refresh to confirm cleaning time is reduced | ||
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Finally, after the previous steps are done, running a data refresh will confirm | ||
there are no more updates applied at ingestion. If time isn't significantly | ||
reduced then it will be necessary to check what was missing in the previous | ||
steps. | ||
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## Dependencies | ||
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### Infrastructure | ||
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<!-- Describe any infrastructure that will need to be provisioned or modified. In particular, identify associated potential cost changes. --> | ||
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No changes needed. The Ingestion Server already has the credentials required to | ||
[connect with AWS](https://github.com/WordPress/openverse/blob/a930ee0f1f116bac77cf56d1fb0923989613df6d/ingestion_server/ingestion_server/indexer_worker.py#L23-L28). | ||
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<!-- | ||
### Tools & packages | ||
Describe any tools or packages which this work might be dependent on. If multiple options are available, try to list as many as are reasonable with your own recommendation. --> | ||
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### Other projects or work | ||
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Once the steps have been completed and proved the method works we could make | ||
additional similar corrections following the same procedure. Some potentially | ||
related issues are: | ||
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- [Some images have duplicate incorrectly decoded unicode tags #1303](https://github.com/WordPress/openverse/issues/1303) | ||
- [Provider scripts may include html tags in record titles #1441](https://github.com/WordPress/openverse/issues/1441) | ||
- [Fix Wikimedia image titles #1728](https://github.com/WordPress/openverse/issues/1728) | ||
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This will also open up space for more structural changes to the Openverse DB | ||
schemas in a [second phase](https://github.com/WordPress/openverse/issues/244) | ||
of the Data Normalization endeavor. | ||
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## Alternatives | ||
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<!-- Describe any alternatives considered and why they were not chosen or recommended. --> | ||
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## Rollback | ||
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<!-- How do we roll back this solution in the event of failure? Are there any steps that can not easily be rolled back? --> | ||
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In the rare case we need the old data back, we can resort to DB backups, which | ||
are performed [weekly][db_snapshots]. | ||
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[db_snapshots]: ./../../../catalog/reference/DAGs.md#rotate_db_snapshots | ||
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<!-- | ||
## Risks | ||
What risks are we taking with this solution? Are there risks that once taken can’t be undone?--> | ||
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## Prior art | ||
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- Previous attempt from cc-archive: | ||
[Clean preexisting data using ImageStore #517](mathemancer_pr) | ||
- @obulat's PR to | ||
[add logging and save cleaned up data in the Ingestion Server](https://github.com/WordPress/openverse/pull/904) | ||
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[mathemancer_pr]: https://github.com/cc-archive/cccatalog/pull/517 |
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# Data Normalization | ||
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```{toctree} | ||
:titlesonly: | ||
:glob: | ||
* | ||
``` |