What Data for This Category Looks Like
Data sources for this category include raw datasets, ETL run logs, annotation platform output results, and sampling quality inspection results. Updates run daily or per individual batch. Daily generated documents include cleaning rule configuration files, quality inspection sampling statistics tables, abnormal data lists, and delivery reports. Document fields include data identifiers, processing timestamps, exception types, compliance tags, and similar items. There are no standardized fixed units; values must be adjusted based on data type. The three most time-consuming processing steps are duplicate data identification, outlier correction, and sampling quality inspection. Data exceptions will directly render delivery results unusable and lead to customer rejection.
Constraints for the Database and Operations Link
Irregular updates from multiple data sources require databases to support parallel writes and on-demand reads, to avoid processing delays caused by single-table pressure overload. Different types of daily documents require dedicated storage table structures, to prevent field mixing that reduces query efficiency. Abnormal data lists and delivery reports need long-term retention, requiring databases to have reliable persistence and archiving mechanisms. Duplicate data identification and outlier processing generate large amounts of temporary computational data. Temporary storage resources must be configured for regular cleanup, to prevent excessive storage space occupation. Additionally, data exceptions will trigger delivery failures. The operations link must be configured with real-time monitoring alerts to promptly detect database connection or write exceptions.
How to Configure Settings
This document applies to FastGPT v4.17.0.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@[host address]:[port]/[database name]?authSource=admin | Adapts to the unstructured storage needs of raw datasets and ETL logs for this category |
PG_URL | postgresql://[username]:[password]@[host address]:[port]/[database name]?sslmode=require | Used to store structured documents such as quality inspection sampling tables and abnormal data lists, supports multi-field filtering |
DB_MAX_LINK | 50–80 connections | Balances concurrent connection requirements for multi-batch data processing, avoids exhausting database resources |
REDIS_URL | redis://[host address]:[port]/0 | Used to cache cleaning rules and temporary calculation results, improves outlier processing efficiency |
| Data backup cycle | 1 time per day | Adapts to the daily or batch update rhythm of this category's data, ensures data security |
| Single write batch size | 1000–2000 entries | Matches the single write scale of daily documents for this category, balances write efficiency and stability |
Three Common Misconfigurations
- Symptom: Database connection errors with prompts "connection timed out" or "authentication failed". Cause: Username, password, or port parameters in
MONGODB_URIorPG_URLare not filled correctly, preventing establishment of a valid connection. - Symptom: Duplicate data writes or data loss during concurrent processing. Cause: No reasonable value set for
DB_MAX_LINK, leading multiple tasks to compete for database connections simultaneously, triggering data write conflicts. - Symptom: Unable to connect to the database in a containerized deployment environment. Cause: Database ports are not mapped to host ports, preventing
REDIS_URLor database connection addresses from penetrating the container network.
How to Verify Successful Configuration
- Run a single batch data cleaning task, check database write logs, confirm there are no connection errors or write failure records related to
MONGODB_URIorPG_URL. - View the cache storage corresponding to
REDIS_URL, confirm that cleaning rules and temporary calculation data can be read and updated normally. - Check the execution records of database backup tasks, confirm that the data backup cycle runs according to the set schedule.
- Simulate a high-concurrency data processing scenario, check database connection number monitoring, confirm that the value does not exceed the range set by
DB_MAX_LINK.
The values given are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.