I am working on the spark code where I have to save multiple column values as a object format and save the result to mongodb
Given Dataset
|---|-----|------|----------|
|A |A_SRC|Past_A|Past_A_SRC|
|---|-----|------|----------|
|a1 | s1 | a2 | s2 |
What I Have tried
val ds1 = Seq(("1", "2", "3","4")).toDF("a", "src", "p_a","p_src")
val recordCol = functions.to_json(Seq($"a", $"src", $"p_a",$"p_src"),struct("a", "src", "p_a","p_src")) as "A"
ds1.select(recordCol).show(truncate = false)
gives me result like
+-----------------------------------------+
|A |
+-----------------------------------------+
|{"a":"1","src":"2","p_a":"3","p_src":"4"}|
+-----------------------------------------+
I am Expecting something like
+-----------------------------------------+
|A |
+-----------------------------------------+
|{"source":"1","value":"2","p_source":"4","p_value":"3"}|
+-----------------------------------------+
How can I change the keys in the object type other than column names. using maps in java ?
You can pass as in the column struct , so that that will be saved as the name you passed.
Dataset<Row> tstDS = spark.read().format("csv").option("header", "true").load("/home/exa9/Documents/SparkLogs/y.csv");
tstDS.show();
/****
+---+-----+------+----------+
| A|A_SRC|Past_A|Past_A_SRC|
+---+-----+------+----------+
| a1| s1| a2| s2|
+---+-----+------+----------+
****/
tstDS.withColumn("A",
functions.to_json(
functions.struct(
functions.col("A").as("source"),
functions.col("A_SRC").as("value"),
functions.col("Past_A").as("p_source"),
functions.col("Past_A_SRC").as("p_value")
))
)
.select("A")
.show(false);
/****
+-----------------------------------------------------------+
|A |
+-----------------------------------------------------------+
|{"source":"a1","value":"s1","p_source":"a2","p_value":"s2"}|
+-----------------------------------------------------------+
****/
来源：https://stackoverflow.com/questions/57920480/how-to-save-nested-or-json-object-in-spark-dataset-with-converting-to-rdd