DP420 Designing and Implementing CloudNative Applications Using Microsoft Azure Cosmos DB Free Practice Test — 30 Questions

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For a global e-commerce platform that processes millions of transactions per minute, generating extensive time-series order data, which partitioning strategy for Azure Cosmos DB would be most effective in preventing hot partitions and ensuring low-latency access to recent order history, while adhering to data locality principles for efficient querying?

Partitioning by a composite key combining `CustomerID` and the date of the transaction (e.g., `CustomerID#YYYY-MM-DD`)
Partitioning by `OrderID`, assuming `OrderID` is a globally unique, sequential identifier
Partitioning solely by `TransactionTimestamp`, granular to the day of the transaction
Partitioning by `CustomerID` to distribute data across individual customer profiles

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