add throughput and hit ratio metrics

app/config.yaml

@@ -1,4 +1,4 @@
-cache_strategy: "Baseline"  # Change this to "Prefetch" or "Tiered" or "Seive"
+cache_strategy: "Tiered"  # Change this to "Prefetch" or "Tiered" or "Seive"
 cache_limit: 10
 l2_cache_limit: 100
 db_file: "llmData_sns.json" # Change this to the name of any json file within the "database/datastore" folder

tests/basic_latency_hitrate.py

@@ -1,36 +0,0 @@
-# Tests latency and hit rate of endpoints. Can be configured with weighted averages for various endpoints.
-
-import requests
-import random
-import json
-
-baseurl = "http://localhost:8000"
-
-endpoints = {
-    "/user/{user_id}": 1
-}
-
-user_ids = json.loads(requests.get(baseurl + "/users").content)["ids"]
-
-random.seed(0)
-
-def generate_random():
-    x = random.choices(list(endpoints.keys()), list(endpoints.values()))[0] # select randomly from endpoint (keys) with weight (values)
-
-    random_user = str(random.choice(user_ids))
-    x = x.replace("{user_id}", random_user)
-
-    return baseurl + x
-
-times = []
-hits = []
-
-for i in range(10000):
-    url = generate_random()
-    response = requests.get(url)
-    content = json.loads(response.content)
-    times.append(content["time_ms"])
-    hits.append(content["source"] == "cache")
-
-print(f"average response time (ms): {sum(times) / len(times)}")
-print(f"hits: {sum(hits)} misses: {len(hits) - sum(hits)}")

tests/random_readonly.py

@@ -0,0 +1,56 @@
+# Tests latency and hit rate of endpoints. Can be configured with weighted averages for various endpoints.
+
+import requests
+import random
+import json
+from tqdm import tqdm
+import time
+
+baseurl = "http://localhost:8000"
+
+endpoints = {
+    "/user/{user_id}": 1
+}
+
+user_ids = json.loads(requests.get(baseurl + "/users").content)["ids"]
+
+random.seed(0)
+
+def generate_random():
+    x = random.choices(list(endpoints.keys()), list(endpoints.values()))[0] # select randomly from endpoint (keys) with weight (values)
+
+    random_user = str(random.choice(user_ids))
+    x = x.replace("{user_id}", random_user)
+
+    return baseurl + x
+
+times = []
+hits = []
+
+start = time.time()
+for i in tqdm(range(10000)):
+    url = generate_random()
+    response = requests.get(url)
+    content = json.loads(response.content)
+    times.append(content["time_ms"])
+    hits.append(content["source"] == "cache")
+end = time.time()
+
+hits_count = sum(hits)
+miss_count = len(hits) - hits_count
+
+hits_time = 0
+miss_time = 0
+for i in range(len(times)):
+    if hits[i]:
+        hits_time += times[i]
+    else:
+        miss_time += times[i]
+total_time = hits_time + miss_time
+
+print(f"hits: {hits_count} misses: {miss_count} ratio: { hits_count / (hits_count + miss_count)}")
+print(f"average response time (ms)           : {total_time / len(times)}")
+print(f"average cache hit response time (ms) : {hits_time / hits_count}")
+print(f"average cache miss response time (ms): {miss_time / miss_count}")
+print(f"cache throughput (requests / ms)     : { len(times) / total_time}")
+print(f"real throughput  (requests / ms)     : { len(times) / (end - start) / 1000}")