Comments (2)
@kushagraThapar could you help route @fabrideci's issue
from azure-sdk-for-java.
After restarting the cluster a few times and cleaning up the tmp
folders, it's now working as expected with the settings provided above! 🥳
I'd then advise to update the README.md to keep consistency with the information available at Azure Cosmos DB Spark Connector - throughput control, that is:
- Use
spark.cosmos.throughputControl.targetThroughput
rather thanspark.cosmos.throughputControl.targetThroughputThreshold
in case the ThroughputControl collection is created on a serverless account, providing an absolute value for target throughput/RU instead of a percentage, e.g. 500 - Set
spark.cosmos.read.partitioning.strategy
toRestrictive
as any other partitioning strategy will result in indexing not being used to count - so latency and RU would spike up - as outlined here - Delete
autoScaleMaxThroughput = '4000'
from thecreateThroughputControl
var if the ThroughputControl collection is created on a serverless account - throughput is automatically handled by the serverless account - Change
autoScaleMaxThroughput
in thecreateTargetResources
var according to the destination account/database, i.e. eitherautoScaleMaxThroughput
,manualThroughput
,sharedDBmanualThroughput
, orsharedDBautoScaleMaxThroughput
from azure-sdk-for-java.
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