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Which Structured Streaming query correctly transitions data from a Silver to a Gold table in Databricks?

Real Exam

(spark.read.load(rawSalesLocation) .writeStream .option(“checkpointLocation“, checkpointPath) .outputMode(“append“) .table(“uncleanedSales“) )

6.8%

(spark.table(“sales“) .groupBy(“store“) .agg(sum(“sales“)) .writeStream .option(“checkpointLocation“, checkpointPath) .outputMode(“complete“) .table(“aggregatedSales“) )

65.1%

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(spark.table(“sales“) .withColumn(“avgPrice“, col(“sales“) / col(“units“)) .writeStream .option(“checkpointLocation“, checkpointPath) .outputMode(“append“) .table(“cleanedSales“) )

11.6%

(spark.readStream.load(rawSalesLocation) .writeStream .option(“checkpointLocation“, checkpointPath) .outputMode(“append“) .table(“uncleanedSales“) )

9.9%

(spark.table(“sales“) .writeStream .option(“checkpointLocation“, checkpointPath) .outputMode(“complete“) .table(“sales“) )

6.5%