What the data for this category looks like
Data related to film theater revenue yield is sourced from theater operation management systems and third-party film data service providers. Updates follow a fixed daily schedule, pushing full operational data from the previous day. Documentation uses a structured table format. Each record corresponds to the daily operational status of one film in one theater. Fields include theater unique identifier, film name, daily showings, cumulative visitor count, daily revenue amount, average ticket price per customer, and more. Corresponding units are showings, visitors, yuan, yuan per visitor. No semi-structured or unstructured additional content is included, only standardized operational metrics.
What constraints do these characteristics impose on deployment and upgrade
The fixed daily full data update requirement means scheduled sync task cycles must align with the data update rhythm. This avoids duplicate sync or missed data. The structured multi-field association feature requires vector database field mapping rules to strictly match core fields such as theater, film and revenue. This prevents cross-dimensional association query failures. The single-day batch import feature requires batch processing timeout and concurrency configurations to adapt to single-batch data volume. This avoids import interruptions or resource overload. During the upgrade process, retain original field mapping rules. This prevents old version sync scripts from failing due to field structure changes.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Film theater daily reports are batch structured tables. Single-batch import takes a long time. 600 seconds covers standard batch processing durations |
UPLOAD_BATCH_SIZE | 500 records/batch | The number of records in a single theater daily report typically ranges from hundreds to thousands. 500 records/batch balances import efficiency and resource usage |
SYNC_CRON_EXPRESSION | 0 2 * * * | Film theater data typically completes previous day settlement at 1 AM daily. Syncing at 2 AM ensures complete data is obtained |
RECALL_TOP_K | Top 10 entries | Film theater revenue yield analysis requires multi-dimensional data association across theater, film and revenue. Recalling 10 entries covers core associated dimension information |
VECTOR_DIMENSION | 1536 | Mainstream text embedding models output 1536 dimensions. This adapts to vector storage requirements for structured fields |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three common errors
- Phenomenon: A
404 no bodyerror is returned when calling the model for local deployment testing. Cause: The model interface proxy address is not configured correctly, preventing requests from forwarding to the target model service. - Phenomenon: SQL queries cannot be executed after accessing the pgvector image inside Docker. Cause: Database connection port mapping and access permissions are not configured correctly, preventing external requests from accessing the database service inside the container.
- Phenomenon: Duplicate records appear during scheduled synchronization of theater daily report data. Cause: The sync task cron expression is configured incorrectly, causing repeated task triggers and duplicate imports of the same data.
How to confirm configurations are properly set
- Perform a manual data import once. Check if the import log displays a normal completion mark, and verify that the number of imported records matches the number of records in the source data file.
- Access the vector database management interface. Check if stored fields include core fields such as theater unique identifier, film name and revenue amount, and that field types match the source data.
- Configure the scheduled sync task. Wait for the next execution cycle, then check if the sync task execution log has no timeout or failure markers.
- Initiate a revenue yield association query request. Check if returned results include associated theater, film and revenue data, and that the number of results matches the configured recall rules.
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.