Update concepts-data-flow-performance.md

Author: kromerm

articles/data-factory/concepts-data-flow-performance.md

@@ -122,8 +122,8 @@ By using wildcarding, your pipeline will only contain one Data Flow activity. Th
 Setting throughput and batch properties on CosmosDB sinks only take effect during the execution of that data flow from a pipeline data flow activity. The original collection settings will be honored by CosmosDB after your data flow execution.
 
 * Batch size: Calculate the rough row size of your data, and make sure that rowSize * batch size is less than two million. If it is, increase the batch size to get better throughput
-* Througput: Set a higher throughput setting here to allow documents to write faster to CosmosDB. Please keep in mind the higher RU costs based upon a high throughput setting.
-*	Write Throughput Budget: Use a value which is smaller than total RUs per minute. If you have a data flow with a high number of Spark partitiongs, setting a a budget throughput will allow more balance across those partitions.
+* Throughput: Set a higher throughput setting here to allow documents to write faster to CosmosDB. Please keep in mind the higher RU costs based upon a high throughput setting.
+*	Write Throughput Budget: Use a value which is smaller than total RUs per minute. If you have a data flow with a high number of Spark partitions, setting a a budget throughput will allow more balance across those partitions.
 
 ## Next steps