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1. How did changing values on the SparkSession property parameters affect the throughput and latency of the data?

We can see the impact of these values encreasing or decreasing processedRowsPerSecond and inputRowsPerSecond

2. What were the 2-3 most efficient SparkSession property key/value pairs? Through testing multiple variations on values, how can you tell these were the most optimal?

To ensure the values I was playing around were the most optimal I used the value of processedRowsPerSecond obtaining 341.8551515158866

The params I found more relevant:

spark.sql.shuffle.partitions                
spark.streaming.kafka.maxRatePerPartition

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