将数据推送到 Cosmos DB 时 Azure 流分析作业降级

Question

I Have data getting pushed from Azure IoT Hub -> Stream Analytics -> CosmosDB

I had 1 simulated device and my cosmos DB collection was of 1000 RU/s working fine . now i have made it 10 simulated devices and my Cosmos DB collection scaled to 15000 RU/s still my stream analytics getting degraded .

Is there i need to increase number of parallel connections to collection ?

can we make it more optimal As Azure pricing of Cosmos DB , Depend on throughput and RU

Answer 1

Can we make it more optimal as Azure pricing of Cosmos DB, depend on throughput and RUs?

I just want to share some thoughts with you about improving write performance of Cosmos db here.

1.Consistency Level

Based on the document :

Depending on what levels of read consistency your scenario needs against read and write latency, you can choose a consistency level on your database account.

You could try to set Consistency Level as Eventually . Details please refer to here .

2.Indexing:

Based on the document:

by default, Azure Cosmos DB enables synchronous indexing on each CRUD operation to your collection. This is another useful option to control the write/read performance in Azure Cosmos DB.

Please try to set index lazy. Also, remove useless index.

3.Partition:

Based on the document :

Azure Cosmos DB unlimited are the recommended approach for partitioning your data, as Azure Cosmos DB automatically scales partitions based on your workload. When writing to unlimited containers, Stream Analytics uses as many parallel writers as previous query step or input partitioning scheme.

Please partition your collection and pass the partition key in output to improve write performance.