gagan taneja created SPARK-18940: ------------------------------------ Summary: Percentile and approximate percentile support for frequency distribution table Key: SPARK-18940 URL: https://issues.apache.org/jira/browse/SPARK-18940 Project: Spark Issue Type: Improvement Components: SQL Affects Versions: 2.0.2 Reporter: gagan taneja
I have a frequency distribution table with following entries Age, No of person 21, 10 22, 15 23, 18 .. .. 30, 14 Moreover it is common to have data in frequency distribution format to further calculate Percentile, Median. With current implementation It would be very difficult and complex to find the percentile. Therefore i am proposing enhancement to current Percentile and Approx Percentile implementation to take frequency distribution column into consideration Current Percentile definition percentile(col, array(percentage1 [, percentage2]...)) case class Percentile( child: Expression, percentageExpression: Expression, mutableAggBufferOffset: Int = 0, inputAggBufferOffset: Int = 0) { def this(child: Expression, percentageExpression: Expression) = { this(child, percentageExpression, 0, 0) } } Proposed changes percentile(col, [frequency], array(percentage1 [, percentage2]...)) case class Percentile( child: Expression, frequency : Expression, percentageExpression: Expression, mutableAggBufferOffset: Int = 0, inputAggBufferOffset: Int = 0) { def this(child: Expression, percentageExpression: Expression) = { this(child, Literal(1L), percentageExpression, 0, 0) } def this(child: Expression, frequency : Expression, percentageExpression: Expression) = { this(child, frequency, percentageExpression, 0, 0) } } Although this definition will differ from hive implementation, it will be useful functionality to many spark user. Moreover the changes are local to only Percentile and ApproxPercentile implementation -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org