rank() function usage in Spark SQL

Question

Need some pointers in using rank()

I have extracted a column from a dataset..need to do the ranking.

Dataset<Row> inputCol= inputDataset.apply("Colname");    
Dataset<Row>  DSColAwithIndex=inputDSAAcolonly.withColumn("df1Rank", rank());

DSColAwithIndex.show();

I can sort the column and then append an index column too to get rank...but curious to known syntax and usage of rank()

Solution

Window spec need to be specified for rank()

val w = org.apache.spark.sql.expressions.Window.orderBy("date") //some spec    

val leadDf = inputDSAAcolonly.withColumn("df1Rank", rank().over(w))

Edit: Java version of answer, as OP using Java

import org.apache.spark.sql.expressions.WindowSpec; 
WindowSpec w = org.apache.spark.sql.expressions.Window.orderBy(colName);
Dataset<Row> leadDf = inputDSAAcolonly.withColumn("df1Rank", rank().over(w));

Comments

[Binu]

Thanks ...tried the below in java....worked fine... import org.apache.spark.sql.expressions.WindowSpec; WindowSpec w = org.apache.spark.sql.expressions.Window.orderBy(colName); Dataset<Row> leadDf = inputDSAAcolonly.withColumn("df1Rank", rank().over(w));