diff --git a/spark_pipelines/ExamplePipelines.ipynb b/spark_pipelines/ExamplePipelines.ipynb
index f0f9b77..9d286ad 100644
--- a/spark_pipelines/ExamplePipelines.ipynb
+++ b/spark_pipelines/ExamplePipelines.ipynb
@@ -10,7 +10,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 28,
    "id": "752eb795",
    "metadata": {},
    "outputs": [],
@@ -19,7 +19,7 @@
     "import pandas as pd\n",
     "from pathlib import Path\n",
     "from sklearn.pipeline import make_pipeline\n",
-    "\n",
+    "import time\n",
     "from generators import *\n",
     "from clean_data import *\n",
     "from preprocess_data import *\n",
@@ -50,6 +50,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
+   "id": "e915186b",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -71,6 +72,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
+   "id": "e9588a02",
    "metadata": {},
    "outputs": [
     {
@@ -2432,6 +2434,48 @@
     "## 2.1 Generating Features"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "0899db27",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60.85968780517578\n"
+     ]
+    }
+   ],
+   "source": [
+    "start=time.time()\n",
+    "val=getAutoCovariance(df_prepared.reset_index()[:1000], 1, 10,\"volume\")\n",
+    "end=time.time()\n",
+    "print(end-start)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "48a90b44",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "0.1977696418762207\n"
+     ]
+    }
+   ],
+   "source": [
+    "start=time.time()\n",
+    "val=getAutoCovariance2(df_prepared.reset_index()[:1000], 1, 10,\"volume\")\n",
+    "end=time.time()\n",
+    "print(end-start)"
+   ]
+  },
   {
    "attachments": {},
    "cell_type": "markdown",