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Zorluk: KolayConfigure Partition Keys and Partitioning Strategies in Azure Cosmos DB

A company is developing a centralized logging service that stores application log messages in Azure Cosmos DB.

The workload has the following characteristics:
- Throughput Profile: High-volume write ingestion of up to 20,00020,000 writes per second, with occasional read queries by administrators.
- Transactional Boundaries: There are no transactional requirements across different log entries; each log document is written independently.
- Read/Write Trade-off: The partitioning strategy must be optimized to maximize write throughput and avoid bottlenecks, even if it requires read queries for a specific day to span multiple partitions.

The log documents contain a `logDate` property (formatted as `YYYY-MM-DD`) and a `serviceName` property. Using `logDate` directly as the partition key would direct all writes for the current day to a single partition, causing a hot partition.

You need to select a partitioning strategy that distributes the write throughput evenly.

Which strategy should you use?

  1. Create a synthetic partition key by appending a random integer suffix to the `logDate` value.Cevap
  2. B
    Use the `serviceName` property as the partition key.
  3. C
    Use the unmodified `logDate` property as the partition key.
  4. D
    Set the partition key to the client's Cosmos DB session consistency token.

Cevap

Create a synthetic partition key by appending a random integer suffix to the `logDate` value.
Appending a random integer suffix to the `logDate` creates a synthetic partition key with higher cardinality. This distributes the write operations of a single day across multiple logical partitions (e.g., from suffix 11 to 1010), preventing any single partition from being overwhelmed by the high write rate of 20,00020,000 operations per second.

Adım Adım Çözüm

1
Analyze the workload characteristics and requirements.
High-volume write throughput (20,00020,000 writes/sec) with no transactional boundaries between separate logs.
Understanding boundaries and throughput patterns guides partition key selection.
2
Identify potential hot partitions.
Using `logDate` causes a hot partition because all logs on a given day target the same key. Using `serviceName` creates a hot partition if a few services dominate logs.
A partition key must distribute write traffic evenly across logical partitions.
3
Determine the optimal partitioning strategy.
Append a random suffix to the `logDate` to create a synthetic key, distributing write traffic across multiple logical partitions.
A synthetic partition key with random suffixes distributes high write traffic evenly, satisfying the write-optimized requirement.

Anahtar Kavram

Avoiding hot partitions in high-write Azure Cosmos DB containers using synthetic partition keys.

Alternatif Yöntem

Instead of appending a random suffix, a pre-calculated hash of another property (like a transaction ID) could be appended to the date to create a deterministic synthetic partition key, which helps when reading specific records if the suffix can be calculated.
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Configure Partition Keys and Partitioning Strategies in Azure Cosmos DB

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