LeetCode PySpark Solution

Author: bitoollearner

Solved/3050. Pizza Toppings Cost Analysis (Medium)-(Solved).ipynb

@@ -4,7 +4,10 @@
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@@ -107,15 +116,27 @@
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-   "outputs": [],
+   "outputs": [
+    {
+     "output_type": "stream",
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "+------------+----+\n|topping_name|cost|\n+------------+----+\n|   Pepperoni| 0.5|\n|     Sausage| 0.7|\n|     Chicken|0.55|\n|Extra Cheese| 0.4|\n+------------+----+\n\n"
+     ]
+    }
+   ],
    "source": [
     "toppings_data_3050 = [\n",
     "    (\"Pepperoni\", 0.50),\n",
@@ -128,15 +149,160 @@
     "toppings_df_3050 = spark.createDataFrame(toppings_data_3050, toppings_columns_3050)\n",
     "toppings_df_3050.show()"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
+   "metadata": {
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+     "tableResultSettingsMap": {},
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+    }
+   },
+   "outputs": [],
+   "source": [
+    "t1_3050 = toppings_df_3050.alias(\"t1_3050\")\n",
+    "t2_3050 = toppings_df_3050.alias(\"t2_3050\")\n",
+    "t3_3050 = toppings_df_3050.alias(\"t3_3050\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 0,
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+     "tableResultSettingsMap": {},
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+    }
+   },
+   "outputs": [
+    {
+     "output_type": "display_data",
+     "data": {
+      "text/html": [
+       "<style scoped>\n",
+       "  .table-result-container {\n",
+       "    max-height: 300px;\n",
+       "    overflow: auto;\n",
+       "  }\n",
+       "  table, th, td {\n",
+       "    border: 1px solid black;\n",
+       "    border-collapse: collapse;\n",
+       "  }\n",
+       "  th, td {\n",
+       "    padding: 5px;\n",
+       "  }\n",
+       "  th {\n",
+       "    text-align: left;\n",
+       "  }\n",
+       "</style><div class='table-result-container'><table class='table-result'><thead style='background-color: white'><tr><th>pizza</th><th>total_cost</th></tr></thead><tbody><tr><td>Chicken,Pepperoni,Sausage</td><td>1.75</td></tr><tr><td>Chicken,Extra Cheese,Sausage</td><td>1.65</td></tr><tr><td>Extra Cheese,Pepperoni,Sausage</td><td>1.6</td></tr><tr><td>Chicken,Extra Cheese,Pepperoni</td><td>1.45</td></tr></tbody></table></div>"
+      ]
+     },
+     "metadata": {
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+       "arguments": {},
+       "columnCustomDisplayInfos": {},
+       "data": [
+        [
+         "Chicken,Pepperoni,Sausage",
+         1.75
+        ],
+        [
+         "Chicken,Extra Cheese,Sausage",
+         1.65
+        ],
+        [
+         "Extra Cheese,Pepperoni,Sausage",
+         1.6
+        ],
+        [
+         "Chicken,Extra Cheese,Pepperoni",
+         1.45
+        ]
+       ],
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+       "schema": [
+        {
+         "metadata": "{}",
+         "name": "pizza",
+         "type": "\"string\""
+        },
+        {
+         "metadata": "{}",
+         "name": "total_cost",
+         "type": "\"double\""
+        }
+       ],
+       "type": "table"
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "t1_3050.join(t2_3050, col(\"t1_3050.topping_name\") < col(\"t2_3050.topping_name\")) \\\n",
+    "        .join(t3_3050, col(\"t2_3050.topping_name\") < col(\"t3_3050.topping_name\")) \\\n",
+    "        .select(\n",
+    "            concat_ws(\",\", \n",
+    "                    t1_3050[\"topping_name\"], \n",
+    "                    t2_3050[\"topping_name\"], \n",
+    "                    t3_3050[\"topping_name\"]\n",
+    "            ).alias(\"pizza\"),\n",
+    "            round(\n",
+    "                t1_3050[\"cost\"] + t2_3050[\"cost\"] + t3_3050[\"cost\"], 2\n",
+    "            ).alias(\"total_cost\")\n",
+    "        ) \\\n",
+    "        .orderBy(col(\"total_cost\").desc(), col(\"pizza\").asc()).display()\n"
+   ]
   }
  ],
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    "language": "python",