From: gmungoc <g.m.carstairs@dundee.ac.uk>
Date: Sun, 8 Sep 2019 19:00:14 +0000 (+0100)
Subject: JAL-3397 timing comparisons for (add then query) IntervalStore
X-Git-Url: http://source.jalview.org/gitweb/?a=commitdiff_plain;h=9c463e09ba8d77823fd8dd47d00d068c223a4c50;p=jalview.git

JAL-3397 timing comparisons for (add then query) IntervalStore
---

diff --git a/test/intervalstore/nonc/IntervalStoreTest.java b/test/intervalstore/nonc/IntervalStoreTest.java
index 7b96e39..7c1a921 100644
--- a/test/intervalstore/nonc/IntervalStoreTest.java
+++ b/test/intervalstore/nonc/IntervalStoreTest.java
@@ -38,9 +38,12 @@ import static org.testng.Assert.assertTrue;
 
 import java.util.ArrayList;
 import java.util.List;
+import java.util.Random;
 
 import org.testng.annotations.Test;
 
+import intervalstore.api.IntervalStoreI;
+
 public class IntervalStoreTest
 {
   @Test(groups = "Functional")
@@ -580,4 +583,87 @@ public class IntervalStoreTest
     assertTrue(store.findOverlaps(36, 100, overlaps).isEmpty());
     assertTrue(store.findOverlaps(1, 9, overlaps).isEmpty());
   }
-}
+
+  /**
+   * Compares alternative IntervalStoreI implementations for time to add an
+   * interval then query, at a range of different scales of N (the number of
+   * stored features).
+   */
+  @Test(groups = "Timing")
+  public void testAddAndQueryTiming()
+  {
+    IntervalStoreI<SimpleFeature> store = new intervalstore.impl.IntervalStore<>();
+    System.out.println("IntervalStoreJ");
+    testAddAndQueryTiming(store);
+
+    System.out.println("\nnonc.IntervalStore");
+    store = new intervalstore.nonc.IntervalStore<>();
+    testAddAndQueryTiming(store);
+  }
+
+  /**
+   * Populates the store with intervals, then logs the time taken to add an
+   * interval then query, at a range of different scales of N (the number of
+   * stored features).
+   * 
+   * @param store
+   */
+  private void testAddAndQueryTiming(IntervalStoreI<SimpleFeature> store)
+  {
+    final int seqlen = 100000; // e.g. length of gene sequence
+    final int repeats = 20;
+    final int K = 1000;
+    final int warmups = 5;
+    final int[] scales = new int[] { 10 * K, 100 * K, K * K };
+
+    Random r = new Random(732); // fixed seed = repeatable test
+    int counter = 0; // to ensure a distinct description for each feature
+
+    System.out.println("Scale\titeration\tmicrosecs");
+    
+    for (int scale : scales)
+    {
+      /*
+       * add 'scale' features to the store
+       */
+      for (int i = 0; i < scale; i++)
+      {
+        SimpleFeature sf = makeFeature(seqlen, r, counter);
+        counter++;
+        store.add(sf);
+      }
+
+      /*
+       * do "add then query" and log the time taken for the query
+       * we ignore the first 5 repetitions as 'warmups'
+       */
+      long total = 0L;
+      for (int i = 0; i < repeats + warmups; i++)
+      {
+        SimpleFeature sf = makeFeature(seqlen, r, counter);
+        store.add(sf);
+        long t1 = System.nanoTime();
+        store.findOverlaps(10, 20);
+        long elapsed = System.nanoTime() - t1;
+        if (i >= warmups)
+        {
+          total += elapsed;
+          System.out.println(
+                  String.format("%d\t%d\t%d", scale, i - warmups,
+                          elapsed / K));
+        }
+      }
+      System.out.println("average " + (total / (K * repeats)));
+    }
+  }
+
+  SimpleFeature makeFeature(final int seqlen, Random r, int counter)
+  {
+    int i1 = r.nextInt(seqlen);
+    int i2 = r.nextInt(seqlen);
+    int from = Math.min(i1, i2);
+    int to = Math.max(i1, i2);
+    SimpleFeature sf = new SimpleFeature(from, to, "desc" + counter);
+    return sf;
+  }
+}
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