HTTP Interfaces and External Systems for Game Revenue Yield

What the Data for This Category Looks Like

Game revenue yield data primarily comes from revenue reporting interfaces of in-house game operation backends, and event tracking interfaces from in-game payment modules. Most updates refresh full data from the previous day at daily midnight. Some real-time monitoring scenarios support hourly incremental updates.

Data is mostly formatted as JSON. Each record includes these fields: game_id (string, unique game identifier), server_id (string, server group identifier), stat_date (ISO format date string), total_revenue (numeric, unit: Chinese Yuan RMB), operating_cost (numeric, unit: Chinese Yuan RMB), daily_yield (numeric, ratio of daily revenue to cost).

The data structure is flat, with no nested levels or extra redundant fields.

Constraints Imposed on HTTP Interfaces and External Systems

The characteristics of game revenue yield data impose multiple constraints on HTTP interfaces and external systems.

First, revenue data counts as business-sensitive information. Interfaces must enforce HTTPS transmission, and configure authentication rules such as API signature verification and IP whitelists.

Second, the data supports both full and incremental update modes. Interfaces must support start_date and end_date parameters for incremental pulls. This avoids bandwidth waste from repeated transfers of full data sets.

Third, single-batch data volume grows with the number of game servers. Interfaces must support page_size and page_num pagination parameters. This prevents single responses from exceeding FastGPT's processing limits.

Fourth, field format requirements are strict. stat_date must comply with ISO 8601 standards. Field names cannot be changed arbitrarily, or data parsing will fail.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT`	`30 seconds`	Game revenue interface response latency typically ranges from 10 to 20 seconds. Adding reasonable buffer time avoids interrupting the pull process due to timeouts
`BATCH_IMPORT_SIZE`	`500 records per batch`	Daily game report data volume usually ranges from hundreds to thousands of records. Importing too many records at once triggers platform memory limits, while importing too few increases the number of pull operations
`DATA_PARSE_STRATEGY`	`Map directly by field name`	Game revenue yield data fields are fixed and flat. No complex regular expression extraction is needed, and parsing can be completed by directly matching field names
`HTTPS_VERIFY`	`Enabled`	Game revenue data is sensitive business data. SSL certificate verification must be enabled to prevent data leaks
`DATE_FIELD_FORMAT`	`YYYY-MM-DD`	Game statistical dates typically use this format, which is compatible with FastGPT's built-in date parsing rules
`API_AUTH_TYPE`	`API_KEY signature verification`	Internal game data sources usually use API key plus signature for authentication, ensuring interface access security

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by data format, volume and business rules. Specific issues require individual analysis. Testing against local samples is recommended before finalizing settings.

Three Common Configuration Mistakes

Symptom: Returns 413 Request Entity Too Large status code when pulling data, or prompts request body size exceed limit during import. Cause: Single-batch data volume exceeds the request body limit of the external interface or FastGPT, and pagination parameters were not configured, leading to bulk full-data pulls.
Symptom: Triggers a maxLength error during data parsing, preventing data import from completing. Cause: Numeric values in the total_revenue or operating_cost field of a single game data record exceed FastGPT's text length limit, and no truncation parameters were configured, causing parsing failure.
Symptom: Data fields are empty after import, or daily_yield calculation results are abnormal. Cause: Incorrect configuration of the DATE_FIELD_FORMAT parameter leads to failed statistical date parsing, subsequent errors in yield calculation logic, or incorrect core field names used during field mapping.

How to Verify Successful Configuration

Call the configured HTTP interface, manually pull a single test data set, and confirm that returned JSON fields match the configured mapping rules.
Import a small batch of test data, check FastGPT's data source synchronization logs to confirm no errors such as timeouts or parsing failures.
Compare original external data with field values stored in FastGPT, confirm core fields such as stat_date and daily_yield match.
Temporarily remove the IP whitelist configuration, verify access to the external interface is blocked, then restore the whitelist and confirm normal access, to validate that authentication configuration works.

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.