deleting information revealing the address of the machine

examples/03_features_preprocessing_and_lightFM.ipynb

@@ -131,7 +131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {
     "ExecuteTime": {
      "end_time": "2020-02-10T15:59:09.227179Z",
@@ -151,57 +151,7 @@
      "is_executing": false
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "WARNING: An illegal reflective access operation has occurred\n",
-      "WARNING: Illegal reflective access by org.apache.spark.unsafe.Platform (file:/opt/conda/lib/python3.10/site-packages/pyspark/jars/spark-unsafe_2.12-3.2.4.jar) to constructor java.nio.DirectByteBuffer(long,int)\n",
-      "WARNING: Please consider reporting this to the maintainers of org.apache.spark.unsafe.Platform\n",
-      "WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations\n",
-      "WARNING: All illegal access operations will be denied in a future release\n",
-      "Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties\n",
-      "Setting default log level to \"WARN\".\n",
-      "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n",
-      "24/02/29 10:19:19 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable\n",
-      "24/02/29 10:19:19 WARN SparkConf: Note that spark.local.dir will be overridden by the value set by the cluster manager (via SPARK_LOCAL_DIRS in mesos/standalone/kubernetes and LOCAL_DIRS in YARN).\n"
-     ]
-    },
-    {
-     "data": {
-      "text/html": [
-       "\n",
-       "            <div>\n",
-       "                <p><b>SparkSession - hive</b></p>\n",
-       "                \n",
-       "        <div>\n",
-       "            <p><b>SparkContext</b></p>\n",
-       "\n",
-       "            <p><a href=\"http://localhost:4040\">Spark UI</a></p>\n",
-       "\n",
-       "            <dl>\n",
-       "              <dt>Version</dt>\n",
-       "                <dd><code>v3.2.4</code></dd>\n",
-       "              <dt>Master</dt>\n",
-       "                <dd><code>local[*]</code></dd>\n",
-       "              <dt>AppName</dt>\n",
-       "                <dd><code>pyspark-shell</code></dd>\n",
-       "            </dl>\n",
-       "        </div>\n",
-       "        \n",
-       "            </div>\n",
-       "        "
-      ],
-      "text/plain": [
-       "<pyspark.sql.session.SparkSession at 0x7e439103afb0>"
-      ]
-     },
-     "execution_count": 15,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
+   "outputs": [],
    "source": [
     "spark = State().session\n",
     "spark"
@@ -528,7 +478,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2024-02-29T10:21:42.887962Z",
@@ -538,26 +488,7 @@
      "shell.execute_reply.started": "2024-02-29T10:21:42.887929Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "29-Feb-24 10:21:42, replay, INFO: Columns with ids of users or items are present in mapping. The dataframe will be treated as an interactions log.\n",
-      "/opt/conda/lib/python3.10/site-packages/pyspark/sql/pandas/conversion.py:471: FutureWarning: iteritems is deprecated and will be removed in a future version. Use .items instead.\n",
-      "  arrow_data = [[(c, t) for (_, c), t in zip(pdf_slice.iteritems(), arrow_types)]\n",
-      "29-Feb-24 10:21:54, replay, INFO: Column with ids of users or items is absent in mapping. The dataframe will be treated as a users'/items' features dataframe.\n"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "CPU times: user 140 ms, sys: 400 ms, total: 540 ms\n",
-      "Wall time: 12.2 s\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "%%time\n",
     "log = preparator.transform(columns_mapping={'user_id': 'user_id',\n",
@@ -1440,7 +1371,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.9.18"
   }
  },
  "nbformat": 4,