nick-bisonai commented 3 months ago

Description

Add condition to prevent overwriting redis database with old local aggregate data.

Type of change

Please delete options that are not relevant.

[ ] Bug fix (non-breaking change which fixes an issue)
[x] New feature (non-breaking change which adds functionality)
[ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
[ ] This change requires a documentation update

Checklist before requesting a review

[x] I have performed a self-review of my code.
[ ] If it is a core feature, I have added thorough tests.

Deployment

[ ] Should publish npm package
[x] Should publish Docker image

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Commits
Files that changed from the base of the PR and between 9d3203402ebe839a8ef2a1bb0e3d0a5e3ec2e108 and 3c301118da82f8d62517d9f74d2e8321285ba64b.

Walkthrough

The recent changes in node/pkg/fetcher/accumulator.go improve the efficiency of the data processing and storage in the accumulatorJob function. The modification involves restructuring the loop to better handle data from the accumulatorChannel, updating localAggregatesDataPgsql, and managing localAggregatesDataRedis based on timestamps to ensure timely and efficient data operations.

Changes

File Path	Change Summary
`node/pkg/fetcher/accumulator.go`	Revamped the loop structure in `accumulatorJob` to enhance data processing and storage efficiency, including managing `localAggregatesDataRedis` and `localAggregatesDataPgsql` based on timestamps.

Sequence Diagram(s)

sequenceDiagram
    participant Accumulator as Accumulator
    participant AccumulatorChannel as accumulatorChannel
    participant PgSQL as localAggregatesDataPgsql
    participant Redis as localAggregatesDataRedis

    loop Process Data
        Accumulator ->> AccumulatorChannel: Read data
        Accumulator ->> PgSQL: Update based on data
        Accumulator ->> Redis: Check timestamps and update
    end

Possibly related issues

Bisonai/orakl#1730: The changes to accumulatorJob function aim to optimize CPU usage and data processing efficiency, potentially addressing the concerns raised in this issue about intensive CPU operations and improving the approach by restructuring the loop.

Poem

In the code's vast realms, where data does flow,
A loop was reborn, both swift and aglow.
With timestamps to guide, and storage to know,
Efficiency sparkles, in the fetcher's tableau.
So sing, little code, in the languages' song,
Your logic reformed, ever swift, ever strong.

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Intizar-T commented 2 months ago

hmm i cannot think of a scenario where this could happen. There is only one goroutine that handles a specific feed data. Data is popped from a channel and written to a db atomically. Is there any race condition that can result in outdated data?

nick-bisonai commented 2 months ago

hmm i cannot think of a scenario where this could happen. There is only one goroutine that handles a specific feed data. Data is popped from a channel and written to a db atomically. Is there any race condition that can result in outdated data?

in redis, only single entry is stored per configuration id as latest local aggregate value to be referenced from aggregator from accumulator, if there's more than two more entries with the same configid, there's a possible scenario where the old local aggregate value overwrites new local aggregate value.

Intizar-T commented 2 months ago

hmm i cannot think of a scenario where this could happen. There is only one goroutine that handles a specific feed data. Data is popped from a channel and written to a db atomically. Is there any race condition that can result in outdated data?

in redis, only single entry is stored per configuration id as latest local aggregate value to be referenced from aggregator from accumulator, if there's more than two more entries with the same configid, there's a possible scenario where the old local aggregate value overwrites new local aggregate value.

hmm but keys in redis are unique so we cannot have multiple entries with the same configid, right?