A document collaboration platform stores real-time edit logs in an Azure Cosmos DB Core (SQL) API container. Each log document contains a `logId` (GUID), `documentId` (String), `userId` (String), `timestamp` (DateTime, formatted as `YYYY-MM-DDTHH:mm:ssZ`), and `editType` (String).
The workload exhibits the following characteristics:
- Write profile: High-frequency write operations occur as more than users concurrently edit documents during peak business hours.
- Read profile: The platform frequently retrieves edit history for a specific document on a specific day to show revisions.
- Transactional profile: The application executes transactional batches to group and commit multiple edits for the same document on the same calendar day.
You must design a partitioning strategy that avoids hot partitions, supports the transactional consistency requirements, and optimizes query performance.
Which two actions should you perform? (Select two.)
- Create a synthetic partition key by concatenating the `documentId` and the date portion of the `timestamp` in the application code.Cevap
- Configure the container partition key path to point to the new custom property that holds the concatenated value.Cevap
- CConfigure the container partition key path to point to `/timestamp` to distribute writes evenly across time-based partitions.
- DSet `/logId` as the partition key path and execute transactional batches to update multiple documents across different logical partitions.