From 37434f5baf632e839dc14b3c7d8745287cb9368a Mon Sep 17 00:00:00 2001
From: Douglas Rumbaugh <dbr4@psu.edu>
Date: Tue, 25 Jul 2023 11:17:36 -0400
Subject: Benchmarks: mtree and vptree benchmark updates

Note: cosine similarity doesn't seem to work for VPTree--I don't think
that it is actually a metric, upon further research. At the very least I
can't find anyone claiming it is, and I've found several people claiming
it isn't. On testing with the Word2Vec data, Euclidean distance works
insofar as the M-Tree and VPTree return the same KNN results for test
queries, whereas Cosine Similarity does not work.
---
 benchmarks/mtree_knn_bench.cpp | 46 ++++++++++++++++++++++++++++++++++++++----
 1 file changed, 42 insertions(+), 4 deletions(-)

(limited to 'benchmarks/mtree_knn_bench.cpp')

diff --git a/benchmarks/mtree_knn_bench.cpp b/benchmarks/mtree_knn_bench.cpp
index 3c1792a..7ae4e83 100644
--- a/benchmarks/mtree_knn_bench.cpp
+++ b/benchmarks/mtree_knn_bench.cpp
@@ -1,6 +1,44 @@
 #include "include/bench.h"
 #include "mtree.h"
 
+static void mtree_knn_bench(MTree &tree, std::vector<de::KNNQueryParms<Word2VecRec>> queries, size_t trial_cnt=1) 
+{
+    char progbuf[25];
+    sprintf(progbuf, "sampling:");
+
+    size_t batch_size = 100;
+    size_t batches = trial_cnt / batch_size;
+    size_t total_time = 0;
+
+    std::vector<Word2VecRec> result_set;
+
+    for (int i=0; i<trial_cnt; i++) {
+        progress_update((double) (i * batch_size) / (double) trial_cnt, progbuf);
+
+        std::vector<Word2VecRec> results;
+
+        auto start = std::chrono::high_resolution_clock::now();
+        for (size_t j=0; j<queries.size(); j++) {
+            results.clear();
+            auto query_output = tree.get_nearest_by_limit(queries[j].point, queries[j].k);
+            auto itr = query_output.begin();
+            while (itr != query_output.end()) {
+                results.emplace_back(itr->data);
+                itr++;
+            }
+        }
+        auto stop = std::chrono::high_resolution_clock::now();
+
+        total_time += std::chrono::duration_cast<std::chrono::nanoseconds>(stop - start).count();
+    }
+
+    progress_update(1.0, progbuf);
+
+    size_t latency = total_time / (trial_cnt * queries.size());
+
+    fprintf(stdout, "%ld\t", latency);
+}
+
 int main(int argc, char **argv)
 {
     if (argc < 5) {
@@ -20,7 +58,7 @@ int main(int argc, char **argv)
     double insert_batch = 0.1; 
 
     init_bench_env(record_count, true);
-    auto queries = read_knn_queries<de::KNNQueryParms<Word2VecRec>>(qfilename, 50);
+    auto queries = read_knn_queries<de::KNNQueryParms<Word2VecRec>>(qfilename, 10);
 
     auto mtree = MTree();
 
@@ -37,10 +75,10 @@ int main(int argc, char **argv)
     size_t insert_cnt = record_count - warmup_cnt;
 
     insert_tput_bench<MTree, Word2VecRec>(mtree, datafile, insert_cnt, delete_prop, to_delete, true);
-    //fprintf(stdout, "%ld\t", mtree.get_memory_usage());
+   // fprintf(stdout, "%ld\t", mtree.get_memory_usage());
 
-//    query_latency_bench<MTree, Word2VecRec, de::KNNQueryParms<Word2VecRec>>(mtree, queries);
- //   fprintf(stdout, "\n");
+    mtree_knn_bench(mtree, queries);
+    fprintf(stdout, "\n");
 
     delete_bench_env();
     fflush(stdout);
-- 
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