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bitoollearner
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LeetCode Pyspark Solution
1 parent 0b98d21 commit 3dd748c

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‎Solved/1571. Warehouse Manager (Easy)-(Solved).ipynb‎

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"+--------+----------+-----+\n| name|product_id|units|\n+--------+----------+-----+\n|LCHouse1| 1| 1|\n|LCHouse1| 2| 10|\n|LCHouse1| 3| 5|\n|LCHouse2| 1| 2|\n|LCHouse2| 2| 2|\n|LCHouse3| 4| 1|\n+--------+----------+-----+\n\n+----------+------------+-----+------+------+\n|product_id|product_name|Width|Length|Height|\n+----------+------------+-----+------+------+\n| 1| LC-TV| 5| 50| 40|\n| 2| LC-KeyChain| 5| 5| 5|\n| 3| LC-Phone| 2| 10| 10|\n| 4| LC-T-Shirt| 4| 10| 20|\n+----------+------------+-----+------+------+\n\n"
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"warehouse_data_1571 = [\n",
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" (\"LCHouse1\", 1, 1),\n",
@@ -162,15 +183,77 @@
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"products_df_1571 = spark.createDataFrame(products_data_1571, products_columns_1571)\n",
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"products_df_1571.show()"
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]
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"joined_df_1571 = warehouse_df_1571\\\n",
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" .join(products_df_1571, on=\"product_id\")\\\n",
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" .withColumn(\"product_volume\", col(\"Width\") * col(\"Length\") * col(\"Height\"))\\\n",
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" .withColumn(\"total_volume\", col(\"product_volume\") * col(\"units\"))"
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]
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"text": [
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"+--------------+------+\n|warehouse_name|volume|\n+--------------+------+\n| LCHouse1| 12250|\n| LCHouse2| 20250|\n| LCHouse3| 800|\n+--------------+------+\n\n"
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]
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}
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],
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"joined_df_1571\\\n",
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" .groupBy(\"name\").agg(sum(\"total_volume\").alias(\"volume\"))\\\n",
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" .withColumnRenamed(\"name\", \"warehouse_name\").show()"
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]
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"language": "python",

‎Solved/1581. Customer Who Visited but Did Not Make Any Transactions (Easy)-(Solved).ipynb‎

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"text": [
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"+--------+-----------+\n|visit_id|customer_id|\n+--------+-----------+\n| 1| 23|\n| 2| 9|\n| 4| 30|\n| 5| 54|\n| 6| 96|\n| 7| 54|\n| 8| 54|\n+--------+-----------+\n\n+--------------+--------+------+\n|transaction_id|visit_id|amount|\n+--------------+--------+------+\n| 2| 5| 310|\n| 3| 5| 300|\n| 9| 5| 200|\n| 12| 1| 910|\n| 13| 2| 970|\n+--------------+--------+------+\n\n"
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"source": [
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"visits_data_1581 = [\n",
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" (1, 23), (2, 9), (4, 30), (5, 54), (6, 96), (7, 54), (8, 54)\n",
@@ -149,15 +170,76 @@
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"transactions_df_1581 = spark.createDataFrame(transactions_data_1581, transactions_columns_1581)\n",
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"transactions_df_1581.show()"
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]
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"outputs": [],
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"source": [
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"no_trans_df_1581 = visits_df_1581\\\n",
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" .join( transactions_df_1581, on=\"visit_id\", how=\"left\")\\\n",
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" .filter(col(\"transaction_id\").isNull())"
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]
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},
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"output_type": "stream",
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"output_type": "stream",
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"text": [
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"+-----------+--------------+\n|customer_id|count_no_trans|\n+-----------+--------------+\n| 30| 1|\n| 96| 1|\n| 54| 2|\n+-----------+--------------+\n\n"
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]
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}
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],
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"source": [
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"no_trans_df_1581\\\n",
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" .groupBy(\"customer_id\") \\\n",
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" .agg(count(\"visit_id\").alias(\"count_no_trans\")).show()"
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]
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}
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