HTTP Interfaces and External Systems for Aquaculture Intelligent Due Diligence Reports

Data for aquaculture intelligent due diligence reports comes from online monitoring sensors at aquaculture ponds, daily feeding logs, third-party

What Data Looks Like for This Category

Data for aquaculture intelligent due diligence reports comes from online monitoring sensors at aquaculture ponds, daily feeding logs, third-party water quality test reports, fry purchase and delivery vouchers, and slaughter quarantine records.

Data update rhythms fall into three categories:

  • Real-time pond monitoring data syncs every hour
  • Log data such as feeding and quarantine records updates daily
  • Bulk batch slaughter data syncs per breeding cycle

The document structure uses breeding batches as the core unit. It includes fields including pond ID, breeding cycle, water temperature, dissolved oxygen, ammonia nitrogen content, total feeding amount, fry stocking amount, and average slaughter weight. All fields include standard industry measurement units.

What Constraints These Characteristics Impose on HTTP Interfaces and External Systems

The hour-level update requirement for real-time monitoring data means HTTP interfaces must support queries within minute-level time ranges, and return fields with standard industry measurement units.

Structured log data from multiple sources requires interfaces to support bulk pulling of different types of business data, to avoid returning an unreasonably large data volume in a single call.

The periodic sync requirement for breeding batches means interfaces must provide query capabilities that accurately match by batch ID, and support incremental pulling via timestamp parameters, to prevent repeated pulling of historical data.

Some authorized test data requires interfaces to include permission verification parameters, to ensure callers have compliant data access permissions.

How to Configure Settings

Configuration ItemRecommended SettingRationale
external_api_timeout300 secondsBulk data pulling for aquaculture requires processing historical data from multiple ponds. 300 seconds covers response needs for most scenarios
batch_query_max_size50 entriesThe number of aquaculture ponds per batch is typically controlled under 50. Pulling too much data at once can trigger interface timeouts
field_mapping_strategyStrict unit matchingAquaculture data fields all include standard measurement units. Strict matching prevents data parsing errors
incremental_sync_interval3600 secondsReal-time monitoring data updates once per hour. Matching the sync interval to the update rhythm reduces invalid calls
api_auth_typeAPI_KEY authenticationExternal aquaculture data interfaces commonly use API keys for permission verification, which aligns with industry data access standards

The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

  • Phenomenon: Calling a bound external aquaculture data interface returns 500 Internal Server Error. Cause: api_auth_type is not configured as API_KEY authentication, and the caller does not carry valid permission credentials.
  • Phenomenon: Pond monitoring data fields returned when generating due diligence reports are empty. Cause: The batch_query_max_size parameter is not set. The single pull data volume exceeds interface limits, resulting in empty returned data.
  • Phenomenon: Calling the clear_history_cache interface in version v4.8.10 does not clear historical session cache. Cause: The interface in this version does not fully adapt to external system cache cleanup logic, and has a functional defect.

How to Verify Proper Configuration

  • Call a test external data interface, check that returned fields include core business fields with correct measurement units, and confirm that the field mapping configuration takes effect.
  • Initiate a bulk pull request, confirm that the number of returned data entries matches the preset bulk query limit, and verify that the interface timeout configuration takes effect.
  • Call the clear_history_cache interface, check whether the session cache is cleared, and confirm that the current version supports the full functionality of this interface.
  • View interface call logs, confirm that valid permission credentials are carried with each call, and verify that the authentication configuration is correct.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.