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@@ -12,13 +12,15 @@ import static org.apache.spark.sql.functions.sum;
 public class AvgAdvTime {
 
     public static void main(String[] args) throws Exception {
-
+        
+        // Start Spark Session
         SparkSession spark = SparkSession
                 .builder()
                 .master("local")
                 .appName("Java Spark SQL basic example")
                 .getOrCreate();
         
+        // Read SCV to DataSet
         Dataset<Row> df = spark.read().format("csv")
                 .option("inferSchema", "true")
                 .option("header", "true")
@@ -29,13 +31,17 @@ public class AvgAdvTime {
         newdf = newdf.withColumn("utc_attributed_time", df.col("attributed_time").cast("long"));
         newdf = newdf.drop("click_time").drop("attributed_time");
 
+        // set Window partition by 'ip' and 'app' order by 'utc_click_time' select rows between 1st row to current row
         WindowSpec w = Window.partitionBy("ip", "app")
                 .orderBy("utc_click_time")
                 .rowsBetween(Window.unboundedPreceding(), Window.currentRow());
         
+        // aggregation
         newdf = newdf.withColumn("cum_count_click", count("utc_click_time").over(w));
         newdf = newdf.withColumn("cum_sum_attributed", sum("is_attributed").over(w));        
         newdf = newdf.withColumn("avg_efficient", col("cum_sum_attributed").divide(col("cum_count_click")));
+        
+        // print example
         newdf.where("ip == '5348' and app == '19'").show();
         newdf.printSchema();