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Update service-level-indicators/spark-retrieval-success-rate.md to describe how Spark v1.5 ingests DDO deals #238 #13

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@Goddhi Goddhi commented Feb 17, 2025

This implementation introduces the spark-deal-observer pipeline for real-time ingestion of Direct Data Onboarding (DDO) deals in Spark v1.5. Key changes include:

  1. New Section: Added "Spark v1.5 DDO Deal Ingestion" under "Deal Ingestion" to describe the new process.
  2. Real-Time Updates: The spark-deal-observer monitors the Filecoin network for new DDO deals, extracting relevant data and updating the Spark Eligible Deal database immediately.

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Thank you @Goddhi for the pull request. It goes in the right direction.

The patch is difficult to review because it contains a lot of unrelated changes, most notably changing and to ' and ". Please revert those changes.


The `spark-deal-observer` works by monitoring the Filecoin network for new DDO deals and automatically adding them to the Spark Eligible Deal database. This process involves the following steps:

1. **Event Listening**: The `spark-deal-observer` listens for events related to DDO deals on the Filecoin blockchain.
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Let's be more specific here and explain: what event we listen for (claim) and how we calculate deal expiration time.

The `spark-deal-observer` works by monitoring the Filecoin network for new DDO deals and automatically adding them to the Spark Eligible Deal database. This process involves the following steps:

1. **Event Listening**: The `spark-deal-observer` listens for events related to DDO deals on the Filecoin blockchain.
2. **Data Extraction**: When a new DDO deal is detected, the observer extracts relevant information, including the payload CID and the associated storage provider.
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We need to be more specific here and explain how we leverage IPNI Advertisement metadata to discover payload CIDs advertised for a given PieceCID. The documentation should also explain how we convert a multihash found in advertised entries to a CID we can retrieve. (Answer: we assume Raw (0x55) codec and create a CID in v1 format.)

Comment on lines +116 to +117
3. **Database Update**: The extracted data is then formatted and inserted into the Spark Eligible Deal database, marking the deal as eligible for retrieval testing.
4. **Real-Time Updates**: This process allows for immediate updates to the Spark system, meaning that new storage providers can be evaluated for their Spark scores without the previous delays associated with nightly batch processes.
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The updates are not real-time:

  • We are processing only events older than 8 hours to get high confidence in chain finality.
  • The code updating the database of eligible deals picks only deals older than 48 hours (IIRC).

It's important to explain that in this document.

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