diff options
Diffstat (limited to 'opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb')
| -rw-r--r-- | opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb | 2089 |
1 files changed, 287 insertions, 1802 deletions
diff --git a/opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb b/opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb index 0100f79d..61ae6322 100644 --- a/opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb +++ b/opendc-experiments/opendc-experiments-greenifier/src/main/Python_scripts/OpenDCdemo.ipynb @@ -165,7 +165,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 140, "id": "fd17d88a", "metadata": {}, "outputs": [ @@ -238,89 +238,32 @@ " <td>1</td>\n", " <td>0.000000</td>\n", " </tr>\n", - " <tr>\n", - " <th>...</th>\n", - " <td>...</td>\n", - " <td>...</td>\n", - " <td>...</td>\n", - " <td>...</td>\n", - " <td>...</td>\n", - " </tr>\n", - " <tr>\n", - " <th>6143</th>\n", - " <td>1019</td>\n", - " <td>2013-09-11 13:14:58+00:00</td>\n", - " <td>600000</td>\n", - " <td>1</td>\n", - " <td>0.000000</td>\n", - " </tr>\n", - " <tr>\n", - " <th>6144</th>\n", - " <td>1019</td>\n", - " <td>2013-09-11 13:19:58+00:00</td>\n", - " <td>300000</td>\n", - " <td>1</td>\n", - " <td>11.704000</td>\n", - " </tr>\n", - " <tr>\n", - " <th>6145</th>\n", - " <td>1019</td>\n", - " <td>2013-09-11 13:29:58+00:00</td>\n", - " <td>600000</td>\n", - " <td>1</td>\n", - " <td>0.000000</td>\n", - " </tr>\n", - " <tr>\n", - " <th>6146</th>\n", - " <td>1019</td>\n", - " <td>2013-09-11 13:34:58+00:00</td>\n", - " <td>300000</td>\n", - " <td>1</td>\n", - " <td>11.704000</td>\n", - " </tr>\n", - " <tr>\n", - " <th>6147</th>\n", - " <td>1019</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>300000</td>\n", - " <td>1</td>\n", - " <td>0.000000</td>\n", - " </tr>\n", " </tbody>\n", "</table>\n", - "<p>6148 rows × 5 columns</p>\n", "</div>" ], "text/plain": [ - " id timestamp duration cpu_count cpu_usage\n", - "0 1019 2013-08-12 13:40:46+00:00 300000 1 0.000000\n", - "1 1019 2013-08-12 13:45:46+00:00 300000 1 11.703998\n", - "2 1019 2013-08-12 13:55:46+00:00 600000 1 0.000000\n", - "3 1019 2013-08-12 14:00:46+00:00 300000 1 11.703998\n", - "4 1019 2013-08-12 14:15:46+00:00 900000 1 0.000000\n", - "... ... ... ... ... ...\n", - "6143 1019 2013-09-11 13:14:58+00:00 600000 1 0.000000\n", - "6144 1019 2013-09-11 13:19:58+00:00 300000 1 11.704000\n", - "6145 1019 2013-09-11 13:29:58+00:00 600000 1 0.000000\n", - "6146 1019 2013-09-11 13:34:58+00:00 300000 1 11.704000\n", - "6147 1019 2013-09-11 13:39:58+00:00 300000 1 0.000000\n", - "\n", - "[6148 rows x 5 columns]" + " id timestamp duration cpu_count cpu_usage\n", + "0 1019 2013-08-12 13:40:46+00:00 300000 1 0.000000\n", + "1 1019 2013-08-12 13:45:46+00:00 300000 1 11.703998\n", + "2 1019 2013-08-12 13:55:46+00:00 600000 1 0.000000\n", + "3 1019 2013-08-12 14:00:46+00:00 300000 1 11.703998\n", + "4 1019 2013-08-12 14:15:46+00:00 900000 1 0.000000" ] }, - "execution_count": 4, + "execution_count": 140, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_trace = pd.read_parquet(f\"{base_folder}/resources/bitbrains-small/trace/trace.parquet\")\n", - "df_trace[df_trace[\"id\"] == \"1019\"]" + "df_trace.head()" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 141, "id": "346f097f", "metadata": { "scrolled": true @@ -421,7 +364,7 @@ "4 2599.999649 179306 " ] }, - "execution_count": 5, + "execution_count": 141, "metadata": {}, "output_type": "execute_result" } @@ -432,45 +375,6 @@ ] }, { - "cell_type": "code", - "execution_count": 6, - "id": "bdba9fe5", - "metadata": {}, - "outputs": [], - "source": [ - "df_meta_new = df_meta[df_meta[\"start_time\"] == df_meta[\"start_time\"].min()].iloc[:20]" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "f11c06bb", - "metadata": {}, - "outputs": [ - { - "ename": "NameError", - "evalue": "name 'Path' is not defined", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[7], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m output_file \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../Python_scripts/meta_small.parquet\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 2\u001b[0m output_file_path \u001b[38;5;241m=\u001b[39m \u001b[43mPath\u001b[49m(output_file)\n\u001b[1;32m 4\u001b[0m df_meta_new\u001b[38;5;241m.\u001b[39mto_parquet(output_file_path, index\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m 6\u001b[0m output_file \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m../Python_scripts/trace_small.parquet\u001b[39m\u001b[38;5;124m\"\u001b[39m\n", - "\u001b[0;31mNameError\u001b[0m: name 'Path' is not defined" - ] - } - ], - "source": [ - "output_file = \"../Python_scripts/meta_small.parquet\"\n", - "output_file_path = Path(output_file)\n", - "\n", - "df_meta_new.to_parquet(output_file_path, index=False)\n", - "\n", - "output_file = \"../Python_scripts/trace_small.parquet\"\n", - "output_file_path = Path(output_file)\n", - "df_trace_new.to_parquet(output_file_path, index=False)" - ] - }, - { "cell_type": "markdown", "id": "13bf9fdb", "metadata": {}, @@ -488,7 +392,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 144, "id": "0d400ffd", "metadata": {}, "outputs": [], @@ -521,230 +425,150 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": 145, "id": "a9a61332", "metadata": {}, "outputs": [ { "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", - "\n", - " .dataframe tbody tr th {\n", - " vertical-align: top;\n", - " }\n", - "\n", - " .dataframe thead th {\n", - " text-align: right;\n", - " }\n", - "</style>\n", - "<table border=\"1\" class=\"dataframe\">\n", - " <thead>\n", - " <tr style=\"text-align: right;\">\n", - " <th></th>\n", - " <th>timestamp</th>\n", - " <th>hosts_up</th>\n", - " <th>hosts_down</th>\n", - " <th>servers_pending</th>\n", - " <th>servers_active</th>\n", - " <th>attempts_success</th>\n", - " <th>attempts_failure</th>\n", - " <th>attempts_error</th>\n", - " <th>absolute_timestamp</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>0</th>\n", - " <td>1970-01-01 00:04:00+00:00</td>\n", - " <td>9</td>\n", - " <td>0</td>\n", - " <td>44</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>1</th>\n", - " <td>1970-01-01 00:04:00+00:00</td>\n", - " <td>9</td>\n", - " <td>0</td>\n", - " <td>44</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>2</th>\n", - " <td>1970-01-01 00:04:00+00:00</td>\n", - " 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"outputs": [ + { + "data": { + "text/plain": [ + "1970-01-01 00:05:00+00:00 1\n", + "1970-03-01 23:55:00+00:00 1\n", + "1970-03-02 00:45:00+00:00 1\n", + "1970-03-02 00:40:00+00:00 1\n", + "1970-03-02 00:35:00+00:00 1\n", + " ..\n", + "1970-01-30 23:50:00+00:00 1\n", + "1970-01-30 23:45:00+00:00 1\n", + "1970-01-30 23:40:00+00:00 1\n", + "1970-01-30 23:35:00+00:00 1\n", + "1970-04-01 00:10:00+00:00 1\n", + "Name: timestamp, Length: 25922, dtype: int64" + ] + }, + "execution_count": 146, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_host_single.timestamp.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 149, + "id": "89977c44", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([50, 49, 48, 47, 46, 45, 44, 35, 34, 16, 15, 14, 13, 12, 11, 10])" + ] + }, + "execution_count": 149, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_server_single.timestamp.value_counts().unique()" + ] + }, + { + "cell_type": "code", + "execution_count": 148, + "id": "eadd08e4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "1970-01-01 00:05:00+00:00 1\n", + "1970-03-01 23:55:00+00:00 1\n", + "1970-03-02 00:45:00+00:00 1\n", + "1970-03-02 00:40:00+00:00 1\n", + "1970-03-02 00:35:00+00:00 1\n", + " ..\n", + "1970-01-30 23:50:00+00:00 1\n", + "1970-01-30 23:45:00+00:00 1\n", + "1970-01-30 23:40:00+00:00 1\n", + "1970-01-30 23:35:00+00:00 1\n", + "1970-04-01 00:10:00+00:00 1\n", + "Name: timestamp, Length: 25922, dtype: int64" + ] + }, + "execution_count": 148, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df_service_single.timestamp.value_counts()" + ] + }, + { + "cell_type": "code", + "execution_count": 104, + "id": "a32f9d66", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "array([44, 45, 46, 47, 49, 50, 34, 16, 14, 13, 12, 11, 10], dtype=int32)" + ] + }, + "execution_count": 104, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "(df_service_single.servers_active + df_service_single.servers_pending).unique() " + ] + }, + { + "cell_type": "code", + "execution_count": 102, + "id": "16f4a6b6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" ] }, - "execution_count": 51, + "execution_count": 102, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df_service_multi" + "set(d1) == set(d2)" ] }, { @@ -757,7 +581,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 150, "id": "82f0a24a", "metadata": {}, "outputs": [ @@ -765,8 +589,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "single topology: 2227379391.0896\n", - "multi topology: 5865296669.647482\n" + "single topology: 2227253755.2781296\n", + "multi topology: 5864872551.731657\n" ] } ], @@ -785,7 +609,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 151, "id": "e94db3a6", "metadata": {}, "outputs": [ @@ -793,8 +617,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "single topology: 0.5759617370100649\n", - "multi topology: 0.3424842677740509\n" + "single topology: 0.5760561514665646\n", + "multi topology: 0.3425398748402685\n" ] } ], @@ -813,7 +637,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 152, "id": "8d7daa45", "metadata": {}, "outputs": [ @@ -821,8 +645,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "single topology: 0.5759617370100649\n", - "multi topology: 0.3424842677740509\n" + "single topology: 0.5760561514665646\n", + "multi topology: 0.3425398748402685\n" ] } ], @@ -841,13 +665,13 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 153, "id": "5df8f9aa", "metadata": {}, "outputs": [ { "data": { - "image/png": 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t7e3SugEAQOPl1pkbq9WqPn36KD093d5WUVGh9PR0DRgwoNb7qaioUElJSX2UCAAAmhi3ztxIUmJiosaNG6eoqCj169dPKSkpKi4uVkJCgiQpLi5O7du3V1JSkqSLa2iioqLUuXNnlZSUaMOGDXrzzTf12muvufM0AABAI+H2cBMbG6uCggLNnDlTeXl5ioyM1MaNG+2LjHNycuTh8a8JpuLiYk2cOFHff/+9mjdvrm7duumtt95SbGysu04BAAA0IhbDMAx3F9GQioqKFBgYqMLCQgUEBLh8/+PTdju97bL4vi6sBAAA83Dk+7tJ3i0FAABQE8INAAAwFbevuQEAAI3QO3VYyzpmtevqcAIzNwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFQINwAAwFScCjfHjh1zdR0AAAAu4VS46dKli4YOHaq33npL58+fd3VNAAAATnMq3Ozdu1e9evVSYmKiwsLC9PDDD2vXrl2urg0AAMBhToWbyMhIvfzyyzpx4oSWL1+u3NxcDR48WD169FBycrIKCgpcXScAAECt1GlBsZeXl+655x6tWbNG8+bN05EjRzR16lTZbDbFxcUpNzfXVXUCAADUSp3CzRdffKGJEyeqbdu2Sk5O1tSpU3X06FFt3rxZJ06c0MiRI11VJwAAQK14ObNRcnKyVqxYoaysLA0fPlxvvPGGhg8fLg+Pi1mpY8eOSktLU3h4uCtrBQAAuCKnws1rr72mBx54QPHx8Wrbtm21fUJCQrRs2bI6FQcAAOAop8LN4cOHr9jHarVq3LhxzuweAADAaU6tuVmxYoXWrFlTpX3NmjVauXJlnYsCAABwllPhJikpScHBwVXaQ0JC9NJLL9W5KAAAAGc5FW5ycnLUsWPHKu0dOnRQTk5OnYsCAABwllPhJiQkRAcOHKjSvn//frVu3brORQEAADjLqXAzevRo/fGPf9TWrVtVXl6u8vJyffLJJ5oyZYr+8Ic/uLpGAACAWnPqbqk5c+YoOztbt956q7y8Lu6ioqJCcXFxrLkBAABu5VS4sVqtWr16tebMmaP9+/erefPm6tmzpzp06ODq+gAAABziVLi5pGvXruratauragEAAKgzp8JNeXm50tLSlJ6erpMnT6qioqLS55988olLigMAAHCUU+FmypQpSktL05133qkePXrIYrG4ui4AAACnOBVuVq1apb/97W8aPny4q+sBAACoE6duBbdarerSpYurawEAAKgzp8LNE088oZdfflmGYbi6HgAAgDpx6rLUtm3btHXrVn300Ue6/vrr1axZs0qfr1271iXFAQAAOMqpcBMUFKS7777b1bUAAADUmVPhZsWKFa6uAwAAwCWcWnMjSRcuXNCWLVv0l7/8RWfOnJEknThxQmfPnnVZcQAAAI5yaubmu+++0+23366cnByVlJRo2LBh8vf317x581RSUqLU1FRX1wkAAFArTs3cTJkyRVFRUfr555/VvHlze/vdd9+t9PR0lxUHAADgKKdmbj777DPt2LFDVqu1Unt4eLh++OEHlxQGAADgDKdmbioqKlReXl6l/fvvv5e/v3+diwIAAHCWU+HmtttuU0pKiv29xWLR2bNnNWvWLB7JAAAA3Mqpy1KLFi1STEyMunfvrvPnz2vMmDE6fPiwgoOD9e6777q6RgAAgFpzKtz85je/0f79+7Vq1SodOHBAZ8+e1fjx43XfffdVWmAMAADQ0JwKN5Lk5eWl+++/35W1AAAA1JlT4eaNN9647OdxcXFOFQMAAFBXToWbKVOmVHpfVlamc+fOyWq1ytfXl3ADAADcxqm7pX7++edKr7NnzyorK0uDBw9mQTEAAHArp58t9WsRERGaO3dulVkdAACAhuSycCNdXGR84sQJV+4SAADAIU6tuXn//fcrvTcMQ7m5uXr11Vc1aNAglxQGAADgDKfCzahRoyq9t1gsatOmjW655RYtWrTIFXUBAAA4xalwU1FR4eo6AAAAXMKla24AAADczamZm8TExFr3TU5OduYQAAAATnEq3Ozbt0/79u1TWVmZrr32WknSN998I09PT9144432fhaLxTVVAgAA1JJT4WbEiBHy9/fXypUr1bJlS0kXf9gvISFBQ4YM0RNPPOHSIgEAAGrLqTU3ixYtUlJSkj3YSFLLli31wgsvcLcUAABwK6fCTVFRkQoKCqq0FxQU6MyZM3UuCgAAwFlOhZu7775bCQkJWrt2rb7//nt9//33eu+99zR+/Hjdc889rq4RAACg1pxac5OamqqpU6dqzJgxKisru7gjLy+NHz9eCxYscGmBAAAAjnAq3Pj6+urPf/6zFixYoKNHj0qSOnfurBYtWri0OAAAAEfV6Uf8cnNzlZubq4iICLVo0UKGYbiqLgAAAKc4FW5+/PFH3XrrreratauGDx+u3NxcSdL48eO5DRwAALiVU+Hm8ccfV7NmzZSTkyNfX197e2xsrDZu3Oiy4gAAABzl1Jqbjz/+WJs2bdJvfvObSu0RERH67rvvXFIYAACAM5yauSkuLq40Y3PJTz/9JG9v7zoXBQAA4Cynws2QIUP0xhtv2N9bLBZVVFRo/vz5Gjp0qMP7W7JkicLDw+Xj46P+/ftr165dNfZdunSphgwZopYtW6ply5aKjo6+bH8AAHB1cSrczJ8/X6+//rruuOMOlZaW6qmnnlKPHj306aefat68eQ7ta/Xq1UpMTNSsWbO0d+9e9e7dWzExMTp58mS1/TMyMjR69Ght3bpVO3fulM1m02233aYffvjBmVMBAAAm41S46dGjh7755hsNHjxYI0eOVHFxse655x7t27dPnTt3dmhfycnJmjBhghISEtS9e3elpqbK19dXy5cvr7b/22+/rYkTJyoyMlLdunXTX//6V1VUVCg9Pd2ZUwEAACbj8ILisrIy3X777UpNTdX06dPrdPDS0lLt2bNH06ZNs7d5eHgoOjpaO3furNU+zp07p7KyMrVq1araz0tKSlRSUmJ/X1RUVKeaAQBA4+bwzE2zZs104MABlxz81KlTKi8vV2hoaKX20NBQ5eXl1WofTz/9tNq1a6fo6OhqP09KSlJgYKD9ZbPZ6lw3AABovJy6LHX//fdr2bJlrq7FYXPnztWqVau0bt06+fj4VNtn2rRpKiwstL+OHz/ewFUCAICG5NTv3Fy4cEHLly/Xli1b1KdPnyrPlEpOTq7VfoKDg+Xp6an8/PxK7fn5+QoLC7vstgsXLtTcuXO1ZcsW9erVq8Z+3t7e3J4OAMBVxKFwc+zYMYWHh+uf//ynbrzxRknSN998U6mPxWKp9f6sVqv69Omj9PR0jRo1SpLsi4MnT55c43bz58/Xiy++qE2bNikqKsqRUwAAACbnULiJiIhQbm6utm7dKuni4xZeeeWVKmtmHJGYmKhx48YpKipK/fr1U0pKioqLi5WQkCBJiouLU/v27ZWUlCRJmjdvnmbOnKl33nlH4eHh9rU5fn5+8vPzc7oOAABgDg6Fm18/9fujjz5ScXFxnQqIjY1VQUGBZs6cqby8PEVGRmrjxo32wJSTkyMPj38tDXrttddUWlqq//iP/6i0n1mzZmn27Nl1qgUAADR9Tq25ueTXYcdZkydPrvEyVEZGRqX32dnZLjkmAAAwJ4fulrJYLFXW1DiyxgYAAKC+OXxZKj4+3n730fnz5/XII49UuVtq7dq1rqsQAADAAQ6Fm3HjxlV6f//997u0GAAAgLpyKNysWLGivuoAAABwCad+oRgAAKCxItwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABTIdwAAABT8XJ3AQAAoGbj03Y7ve2y+L4urKTpYOYGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYCuEGAACYitvDzZIlSxQeHi4fHx/1799fu3btqrHvV199pd/97ncKDw+XxWJRSkpKwxUKAACaBLeGm9WrVysxMVGzZs3S3r171bt3b8XExOjkyZPV9j937pw6deqkuXPnKiwsrIGrBQAATYFbw01ycrImTJighIQEde/eXampqfL19dXy5cur7d+3b18tWLBAf/jDH+Tt7V2rY5SUlKioqKjSCwAAmJfbwk1paan27Nmj6OjofxXj4aHo6Gjt3LnTZcdJSkpSYGCg/WWz2Vy2bwAA0Pi4LdycOnVK5eXlCg0NrdQeGhqqvLw8lx1n2rRpKiwstL+OHz/usn0DAIDGx8vdBdQ3b2/vWl/CAgAATZ/bZm6Cg4Pl6emp/Pz8Su35+fksFgYAAE5zW7ixWq3q06eP0tPT7W0VFRVKT0/XgAED3FUWAABo4tx6WSoxMVHjxo1TVFSU+vXrp5SUFBUXFyshIUGSFBcXp/bt2yspKUnSxUXIX3/9tf2ff/jhB2VmZsrPz09dunRx23kAAIDGw63hJjY2VgUFBZo5c6by8vIUGRmpjRs32hcZ5+TkyMPjX5NLJ06c0A033GB/v3DhQi1cuFA33XSTMjIyGrp8AADQCLl9QfHkyZM1efLkaj/7dWAJDw+XYRgNUBUAAGiq3P74BQAAAFci3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFMh3AAAAFPxcncBAACgfoxP2+30tsusLiykgTFzAwAATIVwAwAATIVwAwAATIVwAwAATIVwAwAATIVwAwAATIVwAwAATIVwAwAATIVwAwAATIVfKG5M3ol1ftsxq11XBwAATRgzNwAAwFQINwAAwFS4LAWYXV0ud9YFl0oBuAnhBmgK3BVQAKAJ4rIUAAAwFWZuXOzR/BnOb2wLclkdAABcrZi5AQAApkK4AQAApsJlKdTJ+LTdTm+7LL6vCysBAOAiZm4AAICpEG4AAICpcFkKAIBGrC534S4OfcGFlTQdhBuzaIIP3WS9DgA0XpnHTzu9baTLqnAO4QZA49MEwzqAxoNwAzSUq+0RClfb+QJoNFhQDAAATIVwAwAATIXLUgAA1Dcu0zYoZm4AAICpEG4AAICpEG4AAICpEG4AAICpsKAYTRK/bowa8QOAwFWPmRsAAGAqzNw0InV6joctyGV1AADQlBFuAACoZ3X5yyscx2UpAABgKszcAI7gV0YBoNFj5gYAAJgK4QYAAJgKl6Vw1anTb+RYXVgIAKBeEG4A4BJ+ABAwBcINrjqP5s9wfmN+TwgAGj3CDdymLiFjcegLLqwEAGAmLCgGAACmwswN6rTAtk6XeJogHpEBAI0f4QYAgFrInBfj7hJQS4QbAHAF7rQCGg3CDZqkq+1yWF1wKa0JqEMwqtO/36c3Ob0tYQ6NGeHGJOryP7hHRVBA40IgA1zjav2LIOEGQL2oS0Bx13GvumDURB8EW6dfGY/v68JK0Fg1inCzZMkSLViwQHl5eerdu7cWL16sfv361dh/zZo1+tOf/qTs7GxFRERo3rx5Gj58eANWDFwd3BVQ0PjV6c9GXRfm1uF3rlgUfHVwe7hZvXq1EhMTlZqaqv79+yslJUUxMTHKyspSSEhIlf47duzQ6NGjlZSUpN/+9rd65513NGrUKO3du1c9evRwwxkAtcOMQuPnrn9HTXGWy52u1kstqD2LYRiGOwvo37+/+vbtq1dffVWSVFFRIZvNpkcffVTPPPNMlf6xsbEqLi7WBx98YG/7t3/7N0VGRio1NfWKxysqKlJgYKAKCwsVEBDguhP5//hbAQDgalenxeo1cOT7260zN6WlpdqzZ4+mTZtmb/Pw8FB0dLR27txZ7TY7d+5UYmJipbaYmBitX7++2v4lJSUqKSmxvy8sLJR0cZDqw9nzF+plvwAANBX18R17aZ+1mZNxa7g5deqUysvLFRoaWqk9NDRUhw4dqnabvLy8avvn5eVV2z8pKUnPPfdclXabzeZk1QAA4LJmB9bbrs+cOaPAwMvv3+1rburbtGnTKs30VFRU6KefflLr1q1lsVhceqyioiLZbDYdP368Xi554SLGuWEwzg2DcW44jHXDqK9xNgxDZ86cUbt27a7Y163hJjg4WJ6ensrPz6/Unp+fr7CwsGq3CQsLc6i/t7e3vL29K7UFBQU5X3QtBAQE8B9OA2CcGwbj3DAY54bDWDeM+hjnK83YXOLWp4JbrVb16dNH6enp9raKigqlp6drwIAB1W4zYMCASv0lafPmzTX2BwAAVxe3X5ZKTEzUuHHjFBUVpX79+iklJUXFxcVKSEiQJMXFxal9+/ZKSkqSJE2ZMkU33XSTFi1apDvvvFOrVq3SF198oddff92dpwEAABoJt4eb2NhYFRQUaObMmcrLy1NkZKQ2btxoXzSck5MjD49/TTANHDhQ77zzjmbMmKFnn31WERERWr9+faP4jRtvb2/NmjWrymUwuBbj3DAY54bBODccxrphNIZxdvvv3AAAALiSW9fcAAAAuBrhBgAAmArhBgAAmArhBgAAmArhxkFLlixReHi4fHx81L9/f+3ateuy/desWaNu3brJx8dHPXv21IYNGxqo0qbNkXFeunSphgwZopYtW6ply5aKjo6+4r8XXOTon+dLVq1aJYvFolGjRtVvgSbh6DifPn1akyZNUtu2beXt7a2uXbvy/45acHScU1JSdO2116p58+ay2Wx6/PHHdf78+Qaqtmn69NNPNWLECLVr104Wi6XG5zr+UkZGhm688UZ5e3urS5cuSktLq/c6ZaDWVq1aZVitVmP58uXGV199ZUyYMMEICgoy8vPzq+2/fft2w9PT05g/f77x9ddfGzNmzDCaNWtmfPnllw1cedPi6DiPGTPGWLJkibFv3z7j4MGDRnx8vBEYGGh8//33DVx50+LoOF/y7bffGu3btzeGDBlijBw5smGKbcIcHeeSkhIjKirKGD58uLFt2zbj22+/NTIyMozMzMwGrrxpcXSc3377bcPb29t4++23jW+//dbYtGmT0bZtW+Pxxx9v4Mqblg0bNhjTp0831q5da0gy1q1bd9n+x44dM3x9fY3ExETj66+/NhYvXmx4enoaGzdurNc6CTcO6NevnzFp0iT7+/LycqNdu3ZGUlJStf3vvfde484776zU1r9/f+Phhx+u1zqbOkfH+dcuXLhg+Pv7GytXrqyvEk3BmXG+cOGCMXDgQOOvf/2rMW7cOMJNLTg6zq+99prRqVMno7S0tKFKNAVHx3nSpEnGLbfcUqktMTHRGDRoUL3WaSa1CTdPPfWUcf3111dqi42NNWJiYuqxMsPgslQtlZaWas+ePYqOjra3eXh4KDo6Wjt37qx2m507d1bqL0kxMTE19odz4/xr586dU1lZmVq1alVfZTZ5zo7z888/r5CQEI0fP74hymzynBnn999/XwMGDNCkSZMUGhqqHj166KWXXlJ5eXlDld3kODPOAwcO1J49e+yXro4dO6YNGzZo+PDhDVLz1cJd34Nu/4XipuLUqVMqLy+3/3LyJaGhoTp06FC12+Tl5VXbPy8vr97qbOqcGedfe/rpp9WuXbsq/0HhX5wZ523btmnZsmXKzMxsgArNwZlxPnbsmD755BPdd9992rBhg44cOaKJEyeqrKxMs2bNaoiymxxnxnnMmDE6deqUBg8eLMMwdOHCBT3yyCN69tlnG6Lkq0ZN34NFRUX6v//7PzVv3rxejsvMDUxl7ty5WrVqldatWycfHx93l2MaZ86c0dixY7V06VIFBwe7uxxTq6ioUEhIiF5//XX16dNHsbGxmj59ulJTU91dmqlkZGTopZde0p///Gft3btXa9eu1Ycffqg5c+a4uzS4ADM3tRQcHCxPT0/l5+dXas/Pz1dYWFi124SFhTnUH86N8yULFy7U3LlztWXLFvXq1as+y2zyHB3no0ePKjs7WyNGjLC3VVRUSJK8vLyUlZWlzp0712/RTZAzf57btm2rZs2aydPT09523XXXKS8vT6WlpbJarfVac1PkzDj/6U9/0tixY/Xggw9Kknr27Kni4mI99NBDmj59eqVnGsJ5NX0PBgQE1NusjcTMTa1ZrVb16dNH6enp9raKigqlp6drwIAB1W4zYMCASv0lafPmzTX2h3PjLEnz58/XnDlztHHjRkVFRTVEqU2ao+PcrVs3ffnll8rMzLS/7rrrLg0dOlSZmZmy2WwNWX6T4cyf50GDBunIkSP28ChJ33zzjdq2bUuwqYEz43zu3LkqAeZSoDR45KLLuO17sF6XK5vMqlWrDG9vbyMtLc34+uuvjYceesgICgoy8vLyDMMwjLFjxxrPPPOMvf/27dsNLy8vY+HChcbBgweNWbNmcSt4LTg6znPnzjWsVqvx97//3cjNzbW/zpw5465TaBIcHedf426p2nF0nHNycgx/f39j8uTJRlZWlvHBBx8YISEhxgsvvOCuU2gSHB3nWbNmGf7+/sa7775rHDt2zPj444+Nzp07G/fee6+7TqFJOHPmjLFv3z5j3759hiQjOTnZ2Ldvn/Hdd98ZhmEYzzzzjDF27Fh7/0u3gj/55JPGwYMHjSVLlnAreGO0ePFi45prrjGsVqvRr18/4x//+If9s5tuuskYN25cpf5/+9vfjK5duxpWq9W4/vrrjQ8//LCBK26aHBnnDh06GJKqvGbNmtXwhTcxjv55/iXCTe05Os47duww+vfvb3h7exudOnUyXnzxRePChQsNXHXT48g4l5WVGbNnzzY6d+5s+Pj4GDabzZg4caLx888/N3zhTcjWrVur/f/tpbEdN26ccdNNN1XZJjIy0rBarUanTp2MFStW1HudFsNg/g0AAJgHa24AAICpEG4AAICpEG4AAICpEG4AAICpEG4AAICpEG4AAICpEG4AAICpEG4AAICpEG4AmEJ4eLhSUlLs7y0Wi9avXy9Jys7OlsViUWZmZr3WcPPNN+uxxx6r12MAuDLCDYBK8vLy9Oijj6pTp07y9vaWzWbTiBEjKj38Ljw8XBaLRRaLRS1atNCNN96oNWvW2D+Pj4/XqFGjquw7IyNDFotFp0+fdrq+tLQ0BQUFVWnfvXu3HnrooWq3sdlsys3NVY8ePZw+7i/VdB5r167VnDlzXHIMAM4j3ACwy87OVp8+ffTJJ59owYIF+vLLL7Vx40YNHTpUkyZNqtT3+eefV25urvbt26e+ffsqNjZWO3bscFPlUps2beTr61vtZ56engoLC5OXl1e91tCqVSv5+/vX6zEAXBnhBoDdxIkTZbFYtGvXLv3ud79T165ddf311ysxMVH/+Mc/KvX19/dXWFiYunbtqiVLlqh58+b6n//5nzodv7oZkczMTFksFmVnZysjI0MJCQkqLCy0zxzNnj1bUtXLUr/068tS8fHx9u1/+crIyJAkvfnmm4qKirKf45gxY3Ty5En7voYOHSpJatmypSwWi+Lj4yVVvSz1888/Ky4uTi1btpSvr6/uuOMOHT582P75pVmoTZs26brrrpOfn59uv/125ebm1mkcgasd4QaAJOmnn37Sxo0bNWnSJLVo0aLK59VdCrrEy8tLzZo1U2lpaT1WKA0cOFApKSkKCAhQbm6ucnNzNXXqVIf38/LLL9u3z83N1ZQpUxQSEqJu3bpJksrKyjRnzhzt379f69evV3Z2tj3A2Gw2vffee5KkrKws5ebm6uWXX672OPHx8friiy/0/vvva+fOnTIMQ8OHD1dZWZm9z7lz57Rw4UK9+eab+vTTT5WTk+PUOQH4l/qdowXQZBw5ckSGYdi/4GurtLRUixYtUmFhoW655ZZ6qu4iq9WqwMBAWSwWhYWFOb2fwMBABQYGSrq4TuYvf/mLtmzZYt/nAw88YO/bqVMnvfLKK+rbt6/Onj0rPz8/tWrVSpIUEhJSY+g7fPiw3n//fW3fvl0DBw6UJL399tuy2Wxav369fv/730u6GKRSU1PVuXNnSdLkyZP1/PPPO31uAJi5AfD/GYbhUP+nn35afn5+8vX11bx58zR37lzdeeed9VRd/di3b5/Gjh2rV199VYMGDbK379mzRyNGjNA111wjf39/3XTTTZKknJycWu/74MGD8vLyUv/+/e1trVu31rXXXquDBw/a23x9fe3BRpLatm1rvwQGwDnM3ACQJEVERMhisejQoUO16v/kk08qPj5efn5+Cg0NlcVisX8WEBCg7777rso2p0+flqenZ7WXvSTJw+Pi37d+GbR+eQnHlfLy8nTXXXfpwQcf1Pjx4+3txcXFiomJUUxMjN5++221adNGOTk5iomJqZfLbs2aNav03mKxOBw0AVTGzA0ASRfv9ImJidGSJUtUXFxc5fNf3/YcHBysLl26KCwsrFKwkaRrr71WX331lUpKSiq17927Vx07dqzyhX5JmzZtJKnSgtpf/zaN1WpVeXl5bU+rWufPn9fIkSPVrVs3JScnV/rs0KFD+vHHHzV37lwNGTJE3bp1qzKTYrVaJemydVx33XW6cOGCPv/8c3vbjz/+qKysLHXv3r1O9QO4PMINALslS5aovLxc/fr103vvvafDhw/r4MGDeuWVVzRgwIBa7+e+++6TxWJRXFyc9uzZoyNHjmj58uVKSUnRE088UeN2Xbp0kc1m0+zZs3X48GF9+OGHWrRoUaU+4eHhOnv2rNLT03Xq1CmdO3fO4fN8+OGHdfz4cb3yyisqKChQXl6e8vLyVFpaqmuuuUZWq1WLFy/WsWPH9P7771f57ZoOHTrIYrHogw8+UEFBgc6ePVvlGBERERo5cqQmTJigbdu2af/+/br//vvVvn17jRw50uGaAdQe4QaAXadOnbR3714NHTpUTzzxhHr06KFhw4YpPT1dr732Wq33ExQUpM8++0xlZWW66667FBkZqVdeeUXJycl6+OGHa9yuWbNmevfdd3Xo0CH16tVL8+bN0wsvvFCpz8CBA/XII48oNjZWbdq00fz58x0+z//93/9Vbm6uunfvrrZt29pfO3bsUJs2bZSWlqY1a9aoe/fumjt3rhYuXFhp+/bt2+u5557TM888o9DQUE2ePLna46xYsUJ9+vTRb3/7Ww0YMECGYWjDhg01zlwBcA2LwcVdAABgIszcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAUyHcAAAAU/l/2yJfAXBOEIwAAAAASUVORK5CYII=", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -874,131 +698,23 @@ }, { "cell_type": "code", - "execution_count": 15, - "id": "520e42a4", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1.000000 36807\n", - "0.026394 10\n", - "0.063165 10\n", - "0.080042 10\n", - "0.021973 10\n", - " ... \n", - "0.519209 1\n", - "0.505311 1\n", - "0.494024 1\n", - "0.493425 1\n", - "0.385138 1\n", - "Name: cpu_utilization, Length: 19790, dtype: int64" - ] - }, - "execution_count": 15, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_host_single.cpu_utilization.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 122, - "id": "a8c35267", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([b'\\xf8\\x8b\\xb8\\xa8rL\\x81\\xec\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x02',\n", - " b'\\x1b9\\x89jQ\\xa8t\\x9b\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x03',\n", - " b'\\xc5\\x84\\x13:\\xc9\\x16\\xab<\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00',\n", - " b'S\\xcb\\x9f\\x0ct~\\xa2\\xea\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x04',\n", - " b'\\xe2 \\xa89{\\x1d\\xcd\\xaf\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00',\n", - " b'\\x06\\xc4]\\x18\\x80\\tEO\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01',\n", - " b',\\x82\\x9a\\xbe\\x1fE2\\xe1\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x05',\n", - " b'>\\xe5x\\x90A\\xc9\\x8a\\xc3\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x01',\n", - " b'nx\\x9ej\\xa1\\xb9e\\xf4\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00'],\n", - " dtype=object)" - ] - }, - "execution_count": 122, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_host_multi.host_id.unique()" - ] - }, - { - "cell_type": "code", - "execution_count": 123, - "id": "68546b09", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "1 704537\n", - "4 590697\n", - "8 388895\n", - "2 312916\n", - "32 43210\n", - "Name: cpu_count, dtype: int64" - ] - }, - "execution_count": 123, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_server_single.cpu_count.value_counts()" - ] - }, - { - "cell_type": "code", - "execution_count": 124, - "id": "326abd0c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "43209\n", - "43215\n" - ] - } - ], - "source": [ - "print(len(df_service_multi))\n", - "print(len(df_service_single))" - ] - }, - { - "cell_type": "code", - "execution_count": 23, + "execution_count": 154, "id": "42c0c638", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "<matplotlib.legend.Legend at 0x7fda07bf34c0>" + "<matplotlib.legend.Legend at 0x7f6fc2cc78b0>" ] }, - "execution_count": 23, + "execution_count": 154, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -1018,23 +734,23 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": 155, "id": "1a688c2d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "<matplotlib.legend.Legend at 0x7fd9cfa736d0>" + "<matplotlib.legend.Legend at 0x7f6fc02a5db0>" ] }, - "execution_count": 50, + "execution_count": 155, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -1054,7 +770,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 156, "id": "dc4e17cd", "metadata": {}, "outputs": [ @@ -1080,1413 +796,173 @@ " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>timestamp</th>\n", - " <th>hosts_up</th>\n", - " <th>hosts_down</th>\n", - " <th>servers_pending</th>\n", - " <th>servers_active</th>\n", - " <th>attempts_success</th>\n", - " <th>attempts_failure</th>\n", - " <th>attempts_error</th>\n", - " <th>absolute_timestamp</th>\n", - " </tr>\n", - " </thead>\n", - " <tbody>\n", - " <tr>\n", - " <th>129629</th>\n", - " <td>1970-04-01 00:30:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>10</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-11-10 14:04:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>129630</th>\n", - " <td>1970-04-01 00:31:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>10</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-11-10 14:05:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>129631</th>\n", - " <td>1970-04-01 00:32:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>10</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-11-10 14:06:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>129632</th>\n", - " <td>1970-04-01 00:33:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>10</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-11-10 14:07:46+00:00</td>\n", - " </tr>\n", - " <tr>\n", - " <th>129633</th>\n", - " <td>1970-04-01 00:34:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>10</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-11-10 14:08:46+00:00</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", 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- " <tr>\n", - " <th>43214</th>\n", - " <td>1970-01-31 00:15:00+00:00</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>0</td>\n", - " <td>16</td>\n", - " <td>49</td>\n", - " <td>1</td>\n", - " <td>0</td>\n", - " <td>2013-09-11 13:49:46+00:00</td>\n", + " <td>1970-01-01 00:00:00+00:00</td>\n", + " <td>2013-08-12 13:35:46+00:00</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ - " timestamp hosts_up hosts_down servers_pending \\\n", - "43205 1970-01-31 00:06:00+00:00 1 0 35 \n", - "43206 1970-01-31 00:07:00+00:00 1 0 35 \n", - "43207 1970-01-31 00:08:00+00:00 1 0 35 \n", - "43208 1970-01-31 00:09:00+00:00 1 0 35 \n", - "43209 1970-01-31 00:10:00+00:00 1 0 35 \n", - "43210 1970-01-31 00:11:00+00:00 1 0 16 \n", - "43211 1970-01-31 00:13:00+00:00 1 0 16 \n", - "43212 1970-01-31 00:13:00+00:00 1 0 16 \n", - "43213 1970-01-31 00:14:00+00:00 1 0 16 \n", - "43214 1970-01-31 00:15:00+00:00 1 0 0 \n", + " timestamp \\\n", + "0 1970-01-01 00:05:00+00:00 \n", + "1 1970-01-01 00:05:00+00:00 \n", + "2 1970-01-01 00:05:00+00:00 \n", + "3 1970-01-01 00:05:00+00:00 \n", + "4 1970-01-01 00:05:00+00:00 \n", "\n", - " servers_active attempts_success attempts_failure attempts_error \\\n", - "43205 15 15 0 0 \n", - "43206 15 15 0 0 \n", - "43207 15 15 0 0 \n", - "43208 15 15 0 0 \n", - "43209 0 15 0 0 \n", - "43210 0 33 1 0 \n", - "43211 0 33 1 0 \n", - "43212 0 33 1 0 \n", - "43213 0 33 1 0 \n", - "43214 16 49 1 0 \n", + " server_id \\\n", + "0 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x06\\xc4]\\x1... \n", + "1 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x1b9\\x89jQ\\... \n", + "2 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00,\\x82\\x9a\\xb... \n", + "3 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00>\\xe5x\\x90A\\... \n", + "4 b'\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00e~\\xec\\xdd<\\... \n", "\n", - " absolute_timestamp \n", - "43205 2013-09-11 13:40:46+00:00 \n", - "43206 2013-09-11 13:41:46+00:00 \n", - "43207 2013-09-11 13:42:46+00:00 \n", - "43208 2013-09-11 13:43:46+00:00 \n", - "43209 2013-09-11 13:44:46+00:00 \n", - "43210 2013-09-11 13:45:46+00:00 \n", - "43211 2013-09-11 13:47:46+00:00 \n", - "43212 2013-09-11 13:47:46+00:00 \n", - "43213 2013-09-11 13:48:46+00:00 \n", - "43214 2013-09-11 13:49:46+00:00 " - ] - }, - "execution_count": 239, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df_service_single.tail(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 237, - "id": "5a40d667", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "<div>\n", - "<style scoped>\n", - " .dataframe tbody tr th:only-of-type {\n", - " vertical-align: middle;\n", - " }\n", + " host_id mem_capacity cpu_count \\\n", + "0 b'\\xe2 \\xa89{\\x1d\\xcd\\xaf\\x00\\x00\\x00\\x00\\x00\\... 181 1 \n", + "1 b'\\xe2 \\xa89{\\x1d\\xcd\\xaf\\x00\\x00\\x00\\x00\\x00\\... 260 1 \n", + "2 b'\\xe2 \\xa89{\\x1d\\xcd\\xaf\\x00\\x00\\x00\\x00\\x00\\... 250 1 \n", + "3 b'\\xe2 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13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>4</td>\n", - " <td>11703.997664</td>\n", - " <td>6213632</td>\n", - " </tr>\n", - " <tr>\n", - " <th>33</th>\n", - " <td>23</td>\n", - " <td>379</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>2</td>\n", - " <td>5199.999270</td>\n", - " <td>8359936</td>\n", - " </tr>\n", - " <tr>\n", - " <th>34</th>\n", - " <td>12</td>\n", - " <td>141</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>2</td>\n", - " <td>5851.998636</td>\n", - " <td>8388608</td>\n", - " </tr>\n", - " <tr>\n", - " <th>35</th>\n", - " <td>11</td>\n", - " <td>1247</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>4</td>\n", - " <td>10399.997352</td>\n", - " <td>16353280</td>\n", - " </tr>\n", - " <tr>\n", - " <th>36</th>\n", - " <td>14</td>\n", - " <td>205</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.999608</td>\n", - " <td>20971520</td>\n", - " </tr>\n", - " <tr>\n", - " <th>37</th>\n", - " <td>15</td>\n", - " <td>242</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.996968</td>\n", - " <td>40802304</td>\n", - " </tr>\n", - " <tr>\n", - " <th>38</th>\n", - " <td>16</td>\n", - " <td>244</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.994648</td>\n", - " <td>40761344</td>\n", - " </tr>\n", - " <tr>\n", - " <th>39</th>\n", - " <td>17</td>\n", - " <td>272</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.997032</td>\n", - " <td>33554432</td>\n", - " </tr>\n", - " <tr>\n", - " <th>40</th>\n", - " <td>18</td>\n", - " <td>281</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.996936</td>\n", - " <td>33554432</td>\n", - " </tr>\n", - " <tr>\n", - " <th>41</th>\n", - " <td>20</td>\n", - " <td>323</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>2</td>\n", - " <td>5199.999298</td>\n", - " <td>8388608</td>\n", - " </tr>\n", - " <tr>\n", - " <th>42</th>\n", - " <td>13</td>\n", - " <td>190</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>20799.999608</td>\n", - " <td>20971520</td>\n", - " </tr>\n", - " <tr>\n", - " <th>43</th>\n", - " <td>49</td>\n", - " <td>997</td>\n", - " <td>2013-08-12 13:35:46+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>8</td>\n", - " <td>19199.997832</td>\n", - " <td>16644096</td>\n", - " </tr>\n", - " <tr>\n", - " <th>44</th>\n", - " <td>6</td>\n", - " <td>1132</td>\n", - " <td>2013-08-20 11:22:04+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>1</td>\n", - " <td>2925.999318</td>\n", - " <td>191739</td>\n", - " </tr>\n", - " <tr>\n", - " <th>45</th>\n", - " <td>4</td>\n", - " <td>1073</td>\n", - " <td>2013-08-21 11:07:12+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>1</td>\n", - " <td>2599.999649</td>\n", - " <td>179306</td>\n", - " </tr>\n", - " <tr>\n", - " <th>46</th>\n", - " <td>21</td>\n", - " <td>331</td>\n", - " <td>2013-08-22 11:12:20+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>4</td>\n", - " <td>10799.996356</td>\n", - " <td>16644096</td>\n", - " </tr>\n", - " <tr>\n", - " <th>47</th>\n", - " <td>32</td>\n", - " <td>557</td>\n", - " <td>2013-08-29 14:28:12+00:00</td>\n", - " <td>2013-09-05 06:49:07+00:00</td>\n", - " <td>1</td>\n", - " <td>2926.000121</td>\n", - " <td>3145728</td>\n", - " </tr>\n", - " <tr>\n", - " <th>48</th>\n", - " <td>3</td>\n", - " <td>1052</td>\n", - " <td>2013-08-29 14:38:12+00:00</td>\n", - " <td>2013-09-05 07:09:07+00:00</td>\n", - " <td>1</td>\n", - " <td>2926.000107</td>\n", - " <td>131245</td>\n", - " </tr>\n", - " <tr>\n", - " <th>49</th>\n", - " <td>19</td>\n", - " <td>308</td>\n", - " <td>2013-09-04 07:58:58+00:00</td>\n", - " <td>2013-09-11 13:39:58+00:00</td>\n", - " <td>2</td>\n", - " <td>5199.999902</td>\n", - " <td>6291456</td>\n", - " </tr>\n", - " </tbody>\n", - "</table>\n", - "</div>" - ], - "text/plain": [ - " index id start_time stop_time \\\n", - "0 0 1019 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "1 26 466 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "2 27 467 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "3 28 501 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "4 29 506 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "5 30 550 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "6 31 554 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "7 33 578 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "8 34 607 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "9 35 626 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "10 36 636 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "11 37 677 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "12 38 720 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "13 39 740 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "14 40 750 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "15 41 796 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "16 42 832 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "17 43 841 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "18 44 851 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "19 45 857 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "20 46 871 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "21 47 915 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "22 25 463 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "23 48 957 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "24 24 449 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "25 22 378 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "26 1 1023 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "27 2 1026 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "28 5 1129 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "29 7 1138 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "30 8 1147 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "31 9 1152 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "32 10 116 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "33 23 379 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "34 12 141 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "35 11 1247 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "36 14 205 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "37 15 242 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "38 16 244 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "39 17 272 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "40 18 281 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "41 20 323 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "42 13 190 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "43 49 997 2013-08-12 13:35:46+00:00 2013-09-11 13:39:58+00:00 \n", - "44 6 1132 2013-08-20 11:22:04+00:00 2013-09-11 13:39:58+00:00 \n", - "45 4 1073 2013-08-21 11:07:12+00:00 2013-09-11 13:39:58+00:00 \n", - "46 21 331 2013-08-22 11:12:20+00:00 2013-09-11 13:39:58+00:00 \n", - "47 32 557 2013-08-29 14:28:12+00:00 2013-09-05 06:49:07+00:00 \n", - "48 3 1052 2013-08-29 14:38:12+00:00 2013-09-05 07:09:07+00:00 \n", - "49 19 308 2013-09-04 07:58:58+00:00 2013-09-11 13:39:58+00:00 \n", + " uptime downtime provision_time boot_time \\\n", + "0 300000 0 1970-01-01 00:00:00+00:00 1970-01-01 00:00:00+00:00 \n", + "1 300000 0 1970-01-01 00:00:00+00:00 1970-01-01 00:00:00+00:00 \n", + "2 300000 0 1970-01-01 00:00:00+00:00 1970-01-01 00:00:00+00:00 \n", + "3 300000 0 1970-01-01 00:00:00+00:00 1970-01-01 00:00:00+00:00 \n", + "4 300000 0 1970-01-01 00:00:00+00:00 1970-01-01 00:00:00+00:00 \n", "\n", - " cpu_count cpu_capacity mem_capacity \n", - "0 1 2926.000135 181352 \n", - "1 4 10399.997372 3141632 \n", - "2 4 10399.998408 3133440 \n", - "3 4 10399.999796 3141632 \n", - "4 4 10399.998452 3133440 \n", - "5 1 2599.999951 1867776 \n", - "6 1 2926.000135 4194304 \n", - "7 1 2599.999626 2092352 \n", - "8 1 2599.999626 4058292 \n", - "9 4 10399.998504 16355328 \n", - "10 4 10399.998500 16361472 \n", - "11 4 10399.999796 8257536 \n", - "12 8 23407.996128 33419264 \n", - "13 32 86399.988608 130457600 \n", - "14 8 20799.995096 33394652 \n", - "15 1 2925.999560 4194304 \n", - "16 2 5199.999232 8388608 \n", - "17 2 5851.999120 2095104 \n", - "18 2 5852.000242 4194304 \n", - "19 1 2926.000073 2097152 \n", - "20 4 11704.000748 16703488 \n", - "21 1 2599.999636 262144 \n", - "22 4 10399.998504 3149824 \n", - "23 4 10399.999788 8388608 \n", - "24 4 10399.998520 8392704 \n", - "25 2 5199.999280 8359936 \n", - "26 1 2925.999560 260096 \n", - "27 1 2925.999717 249972 \n", - "28 1 2925.999494 124928 \n", - "29 1 2599.999602 156776 \n", - "30 1 2599.999649 103484 \n", - "31 1 2925.999560 195624 \n", - "32 4 11703.997664 6213632 \n", - "33 2 5199.999270 8359936 \n", - "34 2 5851.998636 8388608 \n", - "35 4 10399.997352 16353280 \n", - "36 8 20799.999608 20971520 \n", - "37 8 20799.996968 40802304 \n", - "38 8 20799.994648 40761344 \n", - "39 8 20799.997032 33554432 \n", - "40 8 20799.996936 33554432 \n", - "41 2 5199.999298 8388608 \n", - "42 8 20799.999608 20971520 \n", - "43 8 19199.997832 16644096 \n", - "44 1 2925.999318 191739 \n", - "45 1 2599.999649 179306 \n", - "46 4 10799.996356 16644096 \n", - "47 1 2926.000121 3145728 \n", - "48 1 2926.000107 131245 \n", - "49 2 5199.999902 6291456 " + " absolute_timestamp \n", + "0 2013-08-12 13:35:46+00:00 \n", + "1 2013-08-12 13:35:46+00:00 \n", + "2 2013-08-12 13:35:46+00:00 \n", + "3 2013-08-12 13:35:46+00:00 \n", + "4 2013-08-12 13:35:46+00:00 " ] }, - "execution_count": 237, + "execution_count": 156, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "df_meta.sort_values(\"start_time\").reset_index()" + "df_server_single.head()" ] }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 157, "id": "b0e6c7bf", "metadata": {}, "outputs": [], @@ -2496,23 +972,23 @@ }, { "cell_type": "code", - "execution_count": 46, - "id": "18b9b0a8", + "execution_count": 161, + "id": "aea7b79d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[<matplotlib.lines.Line2D at 0x7fd93666ead0>]" + "[<matplotlib.lines.Line2D at 0x7f6f842c6470>]" ] }, - "execution_count": 46, + "execution_count": 161, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -2522,7 +998,7 @@ } ], "source": [ - "window = 5000\n", + "window = 2000\n", "avg_utilization = []\n", "\n", "for ind in range(len(utilization) - window + 1):\n", @@ -2533,38 +1009,23 @@ }, { "cell_type": "code", - "execution_count": 47, - "id": "c8e19983", - "metadata": {}, - "outputs": [], - "source": [ - "sum_util = []\n", - "\n", - "last_util = 0\n", - "for util in utilization:\n", - " sum_util.append(util + last_util)\n", - " last_util = sum_util[-1]" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "67bbf95a", + "execution_count": 129, + "id": "575f824b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "[<matplotlib.lines.Line2D at 0x7fd9366b70d0>]" + "[<matplotlib.lines.Line2D at 0x7f6f872c7fa0>]" ] }, - "execution_count": 49, + "execution_count": 129, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "<Figure size 640x480 with 1 Axes>" ] @@ -2574,8 +1035,32 @@ } ], "source": [ + "sum_util = []\n", + "\n", + "last_util = 0\n", + "for util in utilization:\n", + " sum_util.append(util + last_util)\n", + " last_util = sum_util[-1]\n", + " \n", "plt.plot(sum_util)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d99dfce2", + "metadata": {}, + "outputs": [], + "source": [ + "output_file = \"../Python_scripts/meta_small.parquet\"\n", + "output_file_path = Path(output_file)\n", + "\n", + "df_meta_new.to_parquet(output_file_path, index=False)\n", + "\n", + "output_file = \"../Python_scripts/trace_small.parquet\"\n", + "output_file_path = Path(output_file)\n", + "df_trace_new.to_parquet(output_file_path, index=False)" + ] } ], "metadata": { |