[GitHub] [carbondata] manishnalla1994 commented on a change in pull request #3182: [CARBONDATA-3343] Compaction for Range Sort

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manishnalla1994 commented on a change in pull request #3182: [CARBONDATA-3343] Compaction for Range Sort
URL: https://github.com/apache/carbondata/pull/3182#discussion_r280737189
 
 

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 File path: integration/spark-common/src/main/scala/org/apache/carbondata/spark/rdd/CarbonMergerRDD.scala
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 @@ -589,9 +601,91 @@ class CarbonMergerRDD[K, V](
     // Change string type to support all types
     val sampleRdd = scanRdd
       .map(row => (row.get(0, sparkDataType), null))
+    val sortedRdd = sampleRdd.sortBy(_._1, true)(objectOrdering, classTag[AnyRef])
     val value = new DataSkewRangePartitioner(
-      defaultParallelism, sampleRdd, true)(objectOrdering, classTag[Object])
-    CarbonCompactionUtil.getRangesFromVals(value.rangeBounds, value.minMaxVals)
+      defaultParallelism, sortedRdd, true)(objectOrdering, classTag[Object])
+    if(minVal == null && maxVal == null) {
+      CarbonCompactionUtil
+        .getRangesFromVals(value.rangeBounds, value.rangeBounds(0), value.rangeBounds(1))
+    } else {
+      CarbonCompactionUtil.getRangesFromVals(value.rangeBounds, minVal, maxVal)
+    }
+  }
+
+  def getOverallMinMax(carbonInputSplits: mutable.Seq[CarbonInputSplit],
 
 Review comment:
   It is not giving exact values for min/max in case of big data. For example, in case for 1-10000, RangePartitioner was storing only a few intermediate values in its ordered set in which the last value is not necessarily the max value. So I had to take the overall min/max for the column.

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