jiayuasu commented on code in PR #609:
URL: https://github.com/apache/incubator-sedona/pull/609#discussion_r855462337
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core/src/main/java/org/apache/sedona/core/spatialOperator/DBScanQuery.java:
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@@ -0,0 +1,31 @@
+package org.apache.sedona.core.spatialOperator;
+
+import org.apache.sedona.core.dbscanJudgement.DBScanJudgement;
+import org.apache.sedona.core.knnJudgement.GeometryDistanceComparator;
+import org.apache.sedona.core.knnJudgement.KnnJudgementUsingIndex;
+import org.apache.sedona.core.spatialRDD.SpatialRDD;
+import org.apache.spark.api.java.JavaRDD;
+import org.locationtech.jts.geom.Geometry;
+
+import java.io.Serializable;
+import java.util.HashSet;
+import java.util.List;
+
+public class DBScanQuery
+ implements Serializable
+{
+ public static <T extends Geometry> List<Integer>
SpatialDBScanQuery(SpatialRDD<T> spatialRDD, double eps, int minPoints, boolean
useIndex)
+ {
+ if (useIndex) {
+ if (spatialRDD.indexedRawRDD == null) {
+ throw new NullPointerException("Need to invoke buildIndex()
first, indexedRDDNoId is null");
+ }
+ JavaRDD<Integer> result =
spatialRDD.getRawSpatialRDD().repartition(1).mapPartitions(new
DBScanJudgement(eps, minPoints, new HashSet<>()), true);
Review Comment:
If your implementation cannot work on multiple partitions, then this PR will
NOT be accepted. We are looking for a distributed DBScan algorithm. For
example, this one: https://github.com/irvingc/dbscan-on-spark
You can incorporate this library into Sedona since this one is also under
Apache 2.0 License
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