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This topic created in 1399 days ago, the information mentioned may be changed or developed.
Q1: Someone handed you this dataset (~1GB), and you discovered that it’s over 1,000 tiny files. var df = spark.read.format("orc").load(clean_tracker_cstt_path) ○ Using Spark, please show how you can improve storage efficiency, and explain why this is important. ○ After improving storage efficiency, please explain impact on loading and using dataset in Spark.
Q2: Given the schema below, use Spark 2.x Dataframe API to give count of events per day for the last 7 days.
root |-- action_id: integer (nullable = true) |-- receive_time: timestamp (nullable = true) |-- uuid: string (nullable = true)
Q3: You have calculated the Daily Event Count above using Spark API. Now please find the Min, Max, Mean, and Standard Deviation of Daily Count by using Scala. Only built-in Scala functions may be used. Please format the answer with 2 decimal places, e.g. “The Average Daily Count from Last 7 Days is x.xx”.
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