What Data for This Category Looks Like
Data sources include internal ERP systems of power grid enterprises, provincial power grid reporting platforms, and official financial report disclosure channels. There are two update cadences: full financial reports disclosed in bulk quarterly, and incremental updates of operation and revenue data on a monthly basis. The document structure has four fixed modules: balance sheet, revenue and cost, equipment operation and maintenance, and depreciation and amortization. Most fields use exclusive naming conventions for the power grid industry, such as "grid-connected power revenue", "original value of transmission equipment", and "substation operation and maintenance cost". Corresponding units include ten thousand yuan, kilowatt-hour, unit, and others.
What Constraints These Characteristics Impose on Workflow Orchestration
Dispersed multiple data sources require configuring cross-system connection nodes, and need to handle data alignment logic for different update cadences. Specialized industry fields require establishing standardized mapping rules to avoid field identification deviations during financial report analysis. The difference in volume between quarterly bulk data and monthly incremental data requires the workflow to support dynamic adjustment of bulk processing thresholds. The articulation relationship between equipment asset data and operation and maintenance data in financial reports requires embedding verification nodes to ensure data accuracy and prevent logical errors in subsequent analysis.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
DB_CONNECTION_TIMEOUT | 300 seconds | Multi-data sources (ERP, power grid reporting systems) associated with power grid equipment financial reports have long connection latency; 300 seconds covers cross-system handshake and data pulling processes |
WORKFLOW_BATCH_SIZE | 5000 rows | The row count of quarterly power grid equipment-related data tables is moderate; 5000-row batch processing avoids single-node memory overflow |
PARSE_TABLE_MAX_ROWS | 20000 rows | Maximum row limit for annual financial report equipment asset details; automatically split parsing when exceeding this value to ensure stable node execution |
DATA_FIELD_MAPPING | Map according to power grid industry financial report standards | Power grid equipment financial reports include exclusive fields such as "transmission line depreciation amount", which need to match the field rules of general financial report analysis |
ERROR_RETRY_TIMES | 3 times | Cross-system data pulling may experience temporary network fluctuations; 3 retries covers most temporary failures and reduces invalid executions |
NOTIFICATION_TRIGGER_CONDITION | Node failure or data verification failure | High accuracy requirements for financial report analysis; timely anomaly awareness is needed to trigger corresponding alarm notifications |
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 specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Errors
- The symptom is a database connection error
Failed to connect to jyfkk:1433 - 38BBDDC3AF7F0000. The cause is that the dedicated database access whitelist for power grid equipment financial reports is not configured. The database IP segment of the power grid reporting system differs from that of general business databases, and permissions for the corresponding network segment are not added. - The symptom is that
console.loglogs from the code running module cannot be viewed in the console. The cause is that theDEBUG_LOG_ENABLEconfiguration item is not enabled for the workflow. By default, only core node status is recorded, and custom debug logs are not output. - The symptom is workflow execution timeout and interruption. The cause is that a reasonable
DB_CONNECTION_TIMEOUTparameter is not set, and the 60-second timeout of general business is directly used, which cannot cover the data pulling latency of multiple power grid data sources.
How to Confirm Proper Configuration
- Execute a test node to pull the test data table of power grid equipment financial reports, check whether the timeout warning corresponding to
DB_CONNECTION_TIMEOUTis triggered, and confirm that the connection latency meets expectations. - Manually trigger the data field mapping node, check whether "transmission line depreciation amount" is correctly mapped to "fixed asset depreciation" for financial report analysis, and confirm that the mapping rule takes effect.
- Run the batch processing node, check whether data is split according to the value set by
WORKFLOW_BATCH_SIZE, and there is no single-node data overload error. - Trigger a simulated node failure scenario, check whether the alarm corresponding to
NOTIFICATION_TRIGGER_CONDITIONis triggered, and confirm that the abnormal notification process is working properly.
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.