[GitHub] [pinot] chiquelo commented on a diff in pull request #10643: Add PercentileKLL aggregation function

["chiquelo (via GitHub)" <gi...@apache.org>]

chiquelo commented on code in PR #10643:
URL: https://github.com/apache/pinot/pull/10643#discussion_r1182958934


##########
pinot-core/src/main/java/org/apache/pinot/core/query/aggregation/function/PercentileKLLAggregationFunction.java:
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@@ -0,0 +1,248 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements.  See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership.  The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License.  You may obtain a copy of the License at
+ *
+ *   http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+package org.apache.pinot.core.query.aggregation.function;
+
+import com.google.common.base.Preconditions;
+import java.util.List;
+import java.util.Map;
+import org.apache.datasketches.kll.KllDoublesSketch;
+import org.apache.datasketches.memory.Memory;
+import org.apache.pinot.common.request.context.ExpressionContext;
+import org.apache.pinot.common.utils.DataSchema.ColumnDataType;
+import org.apache.pinot.core.common.BlockValSet;
+import org.apache.pinot.core.query.aggregation.AggregationResultHolder;
+import org.apache.pinot.core.query.aggregation.ObjectAggregationResultHolder;
+import org.apache.pinot.core.query.aggregation.groupby.GroupByResultHolder;
+import org.apache.pinot.core.query.aggregation.groupby.ObjectGroupByResultHolder;
+import org.apache.pinot.segment.spi.AggregationFunctionType;
+import org.apache.pinot.spi.data.FieldSpec.DataType;
+
+/**
+ * <p>
+ *  {@code PercentileKLLAggregationFunction} provides an approximate percentile calculator using the KLL algorithm
+ *  from <a href="https://datasketches.apache.org/docs/KLL/KLLSketch.html">Apache DataSketches library</a>.
+ * </p>
+ * <p>
+ *  The interface is similar to plain 'Percentile' function except for the optional K value which determines
+ *  the size, hence the accuracy of the sketch.
+ * </p>
+ * <p><b>PERCENTILE_KLL(col, percentile, kValue)</b></p>
+ * <p>E.g.:</p>
+ * <ul>
+ *   <li><b>PERCENTILE_KLL(col, 90)</b></li>
+ *   <li><b>PERCENTILE_KLL(col, 99.9, 800)</b></li>
+ * </ul>
+ *
+ * <p>
+ *   There is a variation of the function (<b>PERCENTILE_RAW_KLL</b>) that returns the Base64 encoded
+ *   sketch object to be used externally.
+ * </p>
+ */
+public class PercentileKLLAggregationFunction
+    extends BaseSingleInputAggregationFunction<KllDoublesSketch, Comparable> {
+
+  protected final double _percentile;
+  protected int _kValue = 200; // size of the sketch. This is the default size used by DataSketches lib as well
+
+  public PercentileKLLAggregationFunction(List<ExpressionContext> arguments) {
+    super(arguments.get(0));
+
+    // Check that there are correct number of arguments
+    int numArguments = arguments.size();
+    Preconditions.checkArgument(numArguments == 2 || numArguments == 3,
+        "Expecting 2 or 3 arguments for PercentileKLL function: "
+            + "PERCENTILE_KLL(column, percentile, k=200");
+
+    _percentile = arguments.get(1).getLiteral().getDoubleValue();
+    if (numArguments == 3) {
+      _kValue = arguments.get(2).getLiteral().getIntValue();

Review Comment:
   Makes sense. Did not know about SketchesArgumentException. That should be good enough if bubbled up properly



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