Deployment and Upgrade for Construction Machinery Yield

What the data for this category looks like

Data related to construction machinery yield is primarily sourced from shift pricing guidelines on industry rental platforms, daily quotes from diesel wholesale platforms, operation and maintenance records from equipment manufacturers’ operation systems, and shift demand data from construction bidding. Update frequencies vary across data sources: diesel prices are updated each morning, shift pricing guidelines are updated daily, equipment operation data is synced daily, and monthly depreciation allocation data is updated monthly. Each data entry includes fields such as equipment model, factory serial number, statistical date, daily valid shift hours, shift rental unit price, daily fuel consumption cost, daily maintenance and consumable cost, monthly cumulative depreciation allocation amount, and daily net revenue amount. The unit for duration is hours, and the units for unit price and cost are yuan.

What Constraints These Characteristics Impose on Deployment and Upgrade

Multi-source data access requires configuring multiple data synchronization plugins during deployment. Failing to pre-plan plugin registration paths will cause subsequent data pull failures. Differences in update frequencies across data sources require adjusting scheduled task scheduling parameters during upgrades. Using a single uniform interval will lead to delayed real-time data updates or repeated pulls of daily-updated data. A large number of fields with varying formats across source systems requires configuring field mapping rules during deployment. Compatibility with older field formats is required during upgrades to avoid data parsing errors. Each device generates one data entry per day, leading to significant database load over long-term accumulation. Database read-write separation parameters must be configured during deployment. Historical data must be migrated in batches during upgrades to prevent service freezes.

Configuration Recommendations

Configuration Item	Recommended Setting	Rationale
`PLUGIN_REGISTER_PATH`	`/app/fastgpt/packages/plugins/register`	Adapts to the registration path of multi-source data plugins, avoids missing plugin entry points during deployment
`SYNC_DATA_INTERVAL`	`300 seconds`	Adapts to the multi-frequency update requirements of construction machinery data, balances real-time diesel data and daily shift pricing data
`DATABASE_READ_REPLICA_COUNT`	`2–3`	Addresses daily data accumulation per device, improves read performance during multi-source data synchronization
`PARSE_FIELD_MAPPING`	`Calibrated via actual testing`	Adapts to field differences across source data, must match core fields such as equipment model and statistical date
`DOCKER_PULL_TIMEOUT`	`600 seconds`	Addresses large image pull requirements, prevents timeout failures during upgrades due to oversized images
`MAX_CONTEXT_LENGTH`	`1000–1200 characters`	Adapts to the text length of a single yield report, avoids truncation of core data during processing

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

Three Common Configuration Errors

Executing docker compose pull for upgrades results in image pull failure errors. The cause is that the DOCKER_PULL_TIMEOUT parameter is not configured, and the default timeout period is insufficient due to the large image size.
Input lag occurs in the local deployment workflow configuration interface when there are too many nodes. The cause is that the MAX_CONTEXT_LENGTH parameter is not adjusted, and excessively long context configured for a single node leads to excessive front-end rendering load.
The packages/plugins/register file cannot be found when configuring system plugins. The cause is that the PLUGIN_REGISTER_PATH parameter was not correctly specified during deployment, resulting in the plugin registration path not being generated.

How to Verify Successful Configuration

Execute the ls ${PLUGIN_REGISTER_PATH} command to confirm that the plugin registration directory exists and contains necessary configuration files.
Review scheduled task logs to confirm that multi-source data synchronization tasks execute normally at the interval set by SYNC_DATA_INTERVAL.
Import a single test data entry and verify that parsed fields match the preset PARSE_FIELD_MAPPING rules.
After executing docker compose up -d for upgrades, check container status to confirm all services are running and no error logs are present.

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.