Deployment and Upgrade for Joint-Stock Bank Yield Data

The data sources for yield and market data of this category include product yield ledgers from the bank’s own retail business system, and public

What the data for this category looks like

The data sources for yield and market data of this category include product yield ledgers from the bank’s own retail business system, and public market interfaces from the National Interbank Funding Center. Data is aggregated for the full previous trading day at a fixed daily time. Market data for some high-frequency products is updated hourly. Documents use structured table format, including fields such as product ID, product type, income accounting standard, income value, data statistics period, and data release time. The unit of the statistics period is calendar day. Income value is measured in the benchmark pricing unit of the corresponding product, with no additional percentage annotations.

What constraints these characteristics create during deployment and upgrade

Data sources involve the bank’s core business systems and external interbank interfaces. Cross-system access permissions and data format adaptation rules must be configured during deployment to avoid data pull failures. The fixed T+1 update schedule requires scheduled tasks to trigger at a fixed morning time daily. Frequent data pulls should be avoided to prevent excessive resource usage. The structured document format requires enabling structured field extraction in the knowledge base parsing process. Target data cannot be accurately extracted without this setting enabled. This category of data contains business-sensitive information. Data masking and access log retention rules must be configured during deployment to meet compliance requirements. Bulk product data creates significant processing load. Resource configuration and recall thresholds must be adjusted during deployment to avoid system overload.

Configuration Settings

Configuration ItemRecommended SettingRationale
PARSE_STRUCTURED_ENABLEEnabledThis category of data uses structured table format; enabling this allows accurate extraction of specified fields
CRON_EXPRESSION0 8 * * *Matches the T+1 data aggregation update schedule for joint-stock banks, triggers pull tasks at 8:00 daily
RECALL_TOP_KTop 10 entriesJoint-stock banks have a large number of product lines; controlling recall entries prevents result overload
similarity_threshold0.75-0.85Filters low-relevance market data, retains highly matched yield-related information
DATA_MASKING_ENABLEEnabledThis category of data contains business-sensitive information; enabling this meets compliance requirements
PARSE_FILE_TIMEOUT_SECONDS600 secondsBulk structured data parsing requires extended processing time; prevents task interruption due to timeout

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, 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 Mistakes

  • Symptom: Empty results are returned when searching a specified collection in the knowledge base. Cause: The DATA_SOURCE_WHITELIST parameter is not correctly configured, preventing access to the target data source.
  • Symptom: A Connection refused error is returned when starting local offline deployment. Cause: No locally adapted dependency mirror source is configured, preventing retrieval of basic runtime components.
  • Symptom: In version V4.12.3, after a custom plugin runs, the output download address keeps jumping before a result is returned. Cause: No result wait timeout parameter is configured for the plugin, causing the front-end polling logic to fail to terminate correctly.

How to Confirm Proper Configuration

  • Manually trigger a data pull task, and check for records of successful structured field extraction in the system parsing logs.
  • Enter preset test keywords in the knowledge base search box, and verify that yield-related data within the specified collection can be recalled.
  • Check the effectiveness of the data masking configuration, and confirm whether sensitive business fields are hidden in returned results.
  • View the scheduled task execution logs, and confirm that data update and synchronization operations are automatically triggered at the fixed daily time.

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.