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Step 3

Write the answers to these questions in the README.md doc of your GitHub repo:

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

Parameters like maxOffsetsPerTrigger, that limits the maximum number of offsets processed per trigger interval, specified total number of offsets will be proportionally split across topicPartitions of different volume. And maxRatePerPartition, which is the maximum rate (in messages per second) at which each Kafka partition will be read by this direct API.

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?

I achieved the best performance with the following configuration:

  • master(local(*)). This will use all available cores in CPU.
  • config("spark.sql.shuffle.partitions", 4). This parameter impromeved my processedRowsPerSecond.
  • option("maxOffsetsPerTrigger", 8000). This parameter impromeved my processedRowsPerSecond.