gparai commented on a change in pull request #1715: DRILL-7117: Support 
creation of equi-depth histogram for selected dat…
URL: https://github.com/apache/drill/pull/1715#discussion_r269756979
 
 

 ##########
 File path: 
exec/java-exec/src/main/java/org/apache/drill/exec/planner/common/NumericEquiDepthHistogram.java
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 @@ -0,0 +1,106 @@
+/*
+ * 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.drill.exec.planner.common;
+
+
+import com.fasterxml.jackson.annotation.JsonProperty;
+import com.fasterxml.jackson.annotation.JsonTypeName;
+
+import org.apache.calcite.rex.RexNode;
+import com.clearspring.analytics.stream.quantile.TDigest;
+
+/**
+ * A column specific equi-depth histogram which is meant for numeric data types
+ */
+@JsonTypeName("numeric-equi-depth")
+public class NumericEquiDepthHistogram implements Histogram {
+
+  // For equi-depth, all buckets will have same (approx) number of rows
+  @JsonProperty("numRowsPerBucket")
+  private long numRowsPerBucket;
+
+  // An array of buckets arranged in increasing order of their start boundaries
+  // Note that the buckets only maintain the start point of the bucket range.
+  // End point is assumed to be the same as the start point of next bucket.
+  @JsonProperty("buckets")
+  private Double[] buckets;
+
+  // Default constructor for deserializer
+  public NumericEquiDepthHistogram() {}
+
+  public NumericEquiDepthHistogram(int numBuckets) {
+    // If numBuckets = N, we are keeping N + 1 entries since the (N+1)th 
bucket's
+    // starting value is the MAX value for the column and it becomes the end 
point of the
+    // Nth bucket.
+    buckets = new Double[numBuckets + 1];
+    for (int i = 0; i < buckets.length; i++) {
+      buckets[i] = new Double(0.0);
+    }
+    numRowsPerBucket = -1;
+  }
+
+  public long getNumRowsPerBucket() {
+    return numRowsPerBucket;
+  }
+
+  public void setNumRowsPerBucket(long numRows) {
+    this.numRowsPerBucket = numRows;
+  }
+
+  public Double[] getBuckets() {
+    return buckets;
+  }
+
+  @Override
+  public Double estimatedSelectivity(RexNode filter) {
+    if (numRowsPerBucket >= 0) {
+      return 1.0;
+    } else {
+      return null;
+    }
+  }
+
+  /**
+   * Utility method to build a Numeric Equi-Depth Histogram from a t-digest 
byte array
+   * @param tdigest_array
+   * @return An instance of NumericEquiDepthHistogram
+   */
+  public static NumericEquiDepthHistogram buildFromTDigest(byte[] 
tdigest_array,
+                                                           int numBuckets) {
+    TDigest tdigest = 
TDigest.fromBytes(java.nio.ByteBuffer.wrap(tdigest_array));
+
+    NumericEquiDepthHistogram histogram = new 
NumericEquiDepthHistogram(numBuckets);
+
+    double q = 1.0/numBuckets;
+    int i = 0;
+    for (; i < numBuckets; i++) {
+      // get the starting point of the i-th quantile
+      double start = tdigest.quantile(q * i);
+      histogram.buckets[i] = start;
+    }
+    // for the N-th bucket, the end point corresponds to the 1.0 quantile but 
we don't keep the end
+    // points; only the start point, so this is stored as the start point of 
the (N+1)th bucket
+    histogram.buckets[i] = tdigest.quantile(1.0);
+
+    // each bucket stores approx equal number of rows
+    histogram.setNumRowsPerBucket(tdigest.size()/numBuckets);
 
 Review comment:
   `tdigest.size()` would be equal to the sampled rows? In that case we should 
use the rowcount (which would have done the scaling to account for sampling).

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