A smart home energy platform collects high-frequency telemetry data from millions of IoT smart meters. Each meter writes power consumption readings every 10 seconds. Each telemetry document contains `deviceId`, `timestamp`, `deviceType` (e.g., Thermostat, SmartPlug), and `powerUsage`.
The solution must meet the following requirements:
- Support a high volume of write ingestions without encountering hot partitions.
- Ensure that all telemetry readings and device state updates for a specific meter on a given day can be executed atomically as a single transaction.
- Prevent individual logical partitions from exceeding the 20 GB size limit as data accumulates over years of operation.
- Optimize queries that retrieve daily consumption metrics for a specific meter.
Which two partition key strategies or configurations should you implement to satisfy these requirements? (Select two.)
- Create a synthetic partition key by concatenating the device ID and the current date (for example, deviceId_YYYY-MM-DD) for telemetry ingestion.Cevap
- Group the telemetry writes and state updates for a meter on a specific day into a single transactional batch using the synthetic partition key.Cevap
- CConfigure deviceType as the partition key to optimize reporting queries that aggregate consumption across device categories.
- DRely on the default session consistency level of the container to guarantee read-your-writes consistency across separate user web sessions without sharing session tokens.