Add indexing for Snowflake parquet files

bin/run.sh

@@ -1,3 +1,3 @@
 #!/bin/sh
 
-java -cp `ls target/*-fatjar.jar` -Xms512M -Xmx192G --add-modules jdk.incubator.vector $@
+java -cp `ls target/*-fatjar.jar` -Xms512M -Xmx512G --add-modules jdk.incubator.vector $@

src/main/java/io/anserini/collection/ParquetDenseVectorCollection.java

@@ -137,24 +137,58 @@
       // Read each record from the Parquet file
       while ((record = reader.read()) != null) {
         // Extract the docid (String) from the record
-        String docid = record.getString("docid", 0);
+        String docid = record.getString("doc_id", 0);
         ids.add(docid);
 
         // Extract the vector (double[]) from the record
-        Group vectorGroup = record.getGroup("vector", 0); // Access the 'vector' field
+        Group vectorGroup = record.getGroup("embedding", 0); // Access the 'vector' field
         int vectorSize = vectorGroup.getFieldRepetitionCount(0); // Get the number of elements in the vector
         double[] vector = new double[vectorSize];
         for (int i = 0; i < vectorSize; i++) {
           Group listGroup = vectorGroup.getGroup(0, i); // Access the 'list' group
-          vector[i] = listGroup.getDouble("element", 0); // Get the double value from the 'element' field
+          vector[i] = listGroup.getFloat("element", 0); // Get the double value from the 'element' field
         }
+        vector = normalizeVector(vector);
         vectors.add(vector);
       }
 
       reader.close();
       currentIndex = 0;
     }
 
+    /**
+     * Computes the L2 norm (Euclidean norm) of a vector.
+     * @param vector the vector to compute the norm of
+     * @return the L2 norm of the vector
+     */
+    private static double computeL2Norm(double[] vector) {
+      double sumOfSquares = 0.0;
+      for (double v : vector) {
+        sumOfSquares += v * v;
+      }
+      return Math.sqrt(sumOfSquares);
+    }
+
+    /**
+     * Normalizes a vector to have a norm of 1.
+     * @param vector the vector to normalize
+     * @return a new vector that is the normalized version of the input vector
+     */
+    private static double[] normalizeVector(double[] vector) {
+      double norm = computeL2Norm(vector);
+      double[] normalizedVector = new double[vector.length];
+
+      if (norm == 0) {
+        throw new IllegalArgumentException("Zero vector cannot be normalized.");
+      }
+
+      for (int i = 0; i < vector.length; i++) {
+        normalizedVector[i] = vector[i] / norm;
+      }
+
+      return normalizedVector;
+    }
+
     /**
      * Reads the next document in the segment.
      *