What the data for this category looks like
Port and shipping ledger data primarily originates from port scheduling systems, vessel AIS signal systems, container operation management systems, and berth operation log systems. Data update frequencies fall into two categories: real-time and scheduled. Vessel dynamics and berth operation status are updated in real time. Container volume ledgers are synchronized on a daily scheduled basis. Historical archived ledgers are imported in batches weekly. Individual ledger documents use a structured format, including fields such as vessel IMO number, berth number, operation duration, container TEU volume, cargo type handled, and operation start and end times. Units include hours, standard containers, tons, and other standard metrics.
What constraints these characteristics impose on database and operations maintenance
Multi-source real-time data creates high-concurrency read and write demands, so the carrying capacity of database connection pools must be secured. Multiple structured fields and high-frequency query dimensions require targeted index creation to avoid full table scans. Data with differing update frequencies must be stored across separate databases and tables to prevent excessive single-table data volume from impacting query efficiency. Some ledgers contain long-text operation descriptions, so reasonable cache policy configuration is needed to reduce database load.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
MONGODB_URI | Configure as the replica set connection address for the port ledger database, enable read-write separation | Adapt to high-concurrency read and write scenarios for port data, separate query and write performance |
PG_URL | Configure as a PostgreSQL connection string with SSL encryption, specify the connected database as the ledger archive database | Ensure transmission encryption for sensitive operation data, comply with data security specifications |
DB_MAX_LINK | Set to 20–30 | Match concurrent connection requirements for port ledgers, avoid service interruptions caused by exhausted connections |
REDIS_URL | Configure as cluster mode, set maximum memory to 1000 MB | Cache ledger metadata and intermediate results from high-frequency queries, reduce database access pressure |
Three Common Misconfigurations
- Symptom: The exported dataset.csv only contains the index field, with no content field. Cause: Database field mapping was not configured correctly, and the ledger's operation description field was not associated with the content parameter.
- Symptom: Slow operation logs are continuously reported during knowledge base upload parsing, with delayed MongoDB responses. Cause: Indexes were not created for high-frequency query fields such as vessel IMO number and container number, leading to excessively long full table scan times.
- Symptom: The rerank model maintains high video memory occupancy during operation, eventually triggering an out-of-memory error. Cause: The number of ledger documents processed per batch was not limited. Port ledger data volume per batch is large, and no paging splitting was implemented.
How to Verify Successful Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
- Access the database monitoring panel, review the current active connection count, and confirm it does not exceed the
DB_MAX_LINKconfiguration value. - Execute a high-frequency query statement, such as querying ledger data by vessel IMO number, check whether response time meets business expectations, and verify index configuration is effective.
- Trigger a full ledger data synchronization task, check whether all eligible data is fully captured without truncation or missing entries.
- Export a test data set, confirm the csv file includes both index and content fields, and that field formats match ledger definitions.
The configuration values provided are common starting points, and should be evaluated against the reader's own specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.