OpenSearch integration improvements

[filipecosta90]

The bellow changes aim to:

• Ease the OpenSearch integration, while also reusing as much as possible the connection creation steps.
• Add support for anonymous auth on opensearch client
• Add support for HTTPS traffic and detect ssl configs from connection details
• Ensure that the cluster is at least at yellow state before querying
• Enables inner product distance (supported for Lucene in OpenSearch version 2.13 and later)
• Enables vector dimensions up to 16K (Source: https://opensearch.org/docs/latest/search-plugins/knn/approximate-knn/)
• Uses a backoff stragegy on search_one method when required (due to 429 errors). Fixes https://github.com/qdrant/vector-db-benchmark/issues/142

[LukasWestholt]

No real performace difference between old and new implementation.

--- ../results/opensearch-old/output.json       2024-10-02 15:05:57.197185400 +0200
+++ ../results/opensearch-new/output.json       2024-10-02 15:52:09.001055200 +0200
@@ -1,59 +1,59 @@
 [
   {
     "engine_name": "opensearch",
     "setup_name": "opensearch-m-16-ef-128",
     "dataset_name": "glove-100-angular",
-    "upload_time": 505.1072022999997,
-    "total_upload_time": 506.65230710000014,
+    "upload_time": 571.6861197999997,
+    "total_upload_time": 571.9920295000002,
     "parallel": 1,
     "engine_params": {
       "knn.algo_param.ef_search": 128
     },
-    "mean_time": 0.08039978975999684,
-    "mean_precisions": 0.819351,
-    "std_time": 0.07328582483094778,
-    "min_time": 0.021495099999810918,
-    "max_time": 4.868069999999534,
-    "rps": 12.39949293721894,
-    "p95_time": 0.10517231999988325,
-    "p99_time": 0.18999490199986213
+    "mean_time": 0.07982564825000299,
+    "mean_precisions": 0.8167789999999999,
+    "std_time": 0.07186505068791486,
+    "min_time": 0.008940600000642007,
+    "max_time": 6.208381400001599,
+    "rps": 12.489320049897197,
+    "p95_time": 0.10064215000093098,
+    "p99_time": 0.21390265599933658
   },
   {
     "engine_name": "opensearch",
     "setup_name": "opensearch-m-16-ef-128",
     "dataset_name": "glove-100-angular",
-    "upload_time": 505.1072022999997,
-    "total_upload_time": 506.65230710000014,
+    "upload_time": 571.6861197999997,
+    "total_upload_time": 571.9920295000002,
     "parallel": 1,
     "engine_params": {
       "knn.algo_param.ef_search": 256
     },
-    "mean_time": 0.08500446872999737,
-    "mean_precisions": 0.816762,
-    "std_time": 0.07344455333790761,
-    "min_time": 0.026552799999990384,
-    "max_time": 4.793960500000139,
-    "rps": 11.71986972688328,
-    "p95_time": 0.1365703799996481,
-    "p99_time": 0.28884295299986684
+    "mean_time": 0.08107645404999203,
+    "mean_precisions": 0.814407,
+    "std_time": 0.020966374585830613,
+    "min_time": 0.028347600000415696,
+    "max_time": 1.7499939999997878,
+    "rps": 12.30329778171997,
+    "p95_time": 0.09037325000108466,
+    "p99_time": 0.09874180600041654
   },
   {
     "engine_name": "opensearch",
     "setup_name": "opensearch-m-16-ef-128",
     "dataset_name": "glove-100-angular",
-    "upload_time": 505.1072022999997,
-    "total_upload_time": 506.65230710000014,
+    "upload_time": 571.6861197999997,
+    "total_upload_time": 571.9920295000002,
     "parallel": 1,
     "engine_params": {
       "knn.algo_param.ef_search": 512
     },
-    "mean_time": 0.07950227081000166,
-    "mean_precisions": 0.816762,
-    "std_time": 0.027110040761532377,
-    "min_time": 0.027317600000060338,
-    "max_time": 1.4170608000003995,
-    "rps": 12.539646869542393,
-    "p95_time": 0.09963219500077684,
-    "p99_time": 0.14407165300047384
+    "mean_time": 0.07992414966999531,
+    "mean_precisions": 0.814407,
+    "std_time": 0.010356757441751704,
+    "min_time": 0.025327800000013667,
+    "max_time": 0.42032800000015413,
+    "rps": 12.479517153224734,
+    "p95_time": 0.08913765000097555,
+    "p99_time": 0.09884917200071869
   }
 ]
\ No newline at end of file