append two dataframes and update data - scala

Question

Hello guys I want to update an old dataframe based on pos_id and article_id field.
If the tuple (pos_id,article_id) exist , I will add each column to the old one, if it doesn't exist I will add the new one. It worked fine. But I don't know how to deal with the case , when the dataframe is intially empty , in this case , I will add the new rows in the second dataframe to the old one. Here it is what I did
val histocaisse = spark.read
.format("csv")
.option("header", "true") //reading the headers
.load("C:/Users/MHT/Desktop/histocaisse_dte1.csv")
val hist = histocaisse
.withColumn("pos_id", 'pos_id.cast(LongType))
.withColumn("article_id", 'pos_id.cast(LongType))
.withColumn("date", 'date.cast(DateType))
.withColumn("qte", 'qte.cast(DoubleType))
.withColumn("ca", 'ca.cast(DoubleType))
val histocaisse2 = spark.read
.format("csv")
.option("header", "true") //reading the headers
.load("C:/Users/MHT/Desktop/histocaisse_dte2.csv")
val hist2 = histocaisse2.withColumn("pos_id", 'pos_id.cast(LongType))
.withColumn("article_id", 'pos_id.cast(LongType))
.withColumn("date", 'date.cast(DateType))
.withColumn("qte", 'qte.cast(DoubleType))
.withColumn("ca", 'ca.cast(DoubleType))
hist2.show(false)
+------+----------+----------+----+----+
|pos_id|article_id|date |qte |ca |
+------+----------+----------+----+----+
|1 |1 |2000-01-07|2.5 |3.5 |
|2 |2 |2000-01-07|14.7|12.0|
|3 |3 |2000-01-07|3.5 |1.2 |
+------+----------+----------+----+----+
+------+----------+----------+----+----+
|pos_id|article_id|date |qte |ca |
+------+----------+----------+----+----+
|1 |1 |2000-01-08|2.5 |3.5 |
|2 |2 |2000-01-08|14.7|12.0|
|3 |3 |2000-01-08|3.5 |1.2 |
|4 |4 |2000-01-08|3.5 |1.2 |
|5 |5 |2000-01-08|14.5|1.2 |
|6 |6 |2000-01-08|2.0 |1.25|
+------+----------+----------+----+----+
+------+----------+----------+----+----+
|pos_id|article_id|date |qte |ca |
+------+----------+----------+----+----+
|1 |1 |2000-01-08|5.0 |7.0 |
|2 |2 |2000-01-08|39.4|24.0|
|3 |3 |2000-01-08|7.0 |2.4 |
|4 |4 |2000-01-08|3.5 |1.2 |
|5 |5 |2000-01-08|14.5|1.2 |
|6 |6 |2000-01-08|2.0 |1.25|
+------+----------+----------+----+----+
Here is the solution , i found
val df = hist2.join(hist1, Seq("article_id", "pos_id"), "left")
.select($"pos_id", $"article_id",
coalesce(hist2("date"), hist1("date")).alias("date"),
(coalesce(hist2("qte"), lit(0)) + coalesce(hist1("qte"), lit(0))).alias("qte"),
(coalesce(hist2("ca"), lit(0)) + coalesce(hist1("ca"), lit(0))).alias("ca"))
.orderBy("pos_id", "article_id")
This case doesn't work when hist1 is empty .Any help please ?
Thanks a lot

Answer 1

Not sure if I understood correctly, but if the problem is sometimes the second dataframe is empty, and that makes the join crash, something you can try is this:
val checkHist1Empty = Try(hist1.first)
val df = checkHist1Empty match {
case Success(df) => {
hist2.join(hist1, Seq("article_id", "pos_id"), "left")
.select($"pos_id", $"article_id",
coalesce(hist2("date"), hist1("date")).alias("date"),
(coalesce(hist2("qte"), lit(0)) + coalesce(hist1("qte"), lit(0))).alias("qte"),
(coalesce(hist2("ca"), lit(0)) + coalesce(hist1("ca"), lit(0))).alias("ca"))
.orderBy("pos_id", "article_id")
}
case Failure(e) => {
hist2.select($"pos_id", $"article_id",
coalesce(hist2("date")).alias("date"),
coalesce(hist2("qte"), lit(0)).alias("qte"),
coalesce(hist2("ca"), lit(0)).alias("ca"))
.orderBy("pos_id", "article_id")
}
}
This basically checks if the hist1 is empty before performing the join. In case it is empty it generates the df based on the same logic but applied only to the hist2 dataframe. In case it contains information it applies the logic you had, which you said that works.

Answer 2

instead of doing a join, why don't you do a union of the two dataframes and then groupBy (pos_id,article_id) and apply udf to each column sum for qte and ca.
val df3 = df1.unionAll(df2)
val df4 = df3.groupBy("pos_id", "article_id").agg($"pos_id", $"article_id", max("date"), sum("qte"), sum("ca"))