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| spark-shell --packages com.databricks:spark-xml_2.10:0.4.1 | |
| val sqlContext = new org.apache.spark.sql.SQLContext(sc) | |
| val df = sqlContext.read.format("com.databricks.spark.xml").option("rowTag", "Transaction").load("/user/tsusanto/POSLog-201409300635-21.xml") | |
| val flattened = df.withColumn("LineItem", explode($"RetailTransaction.LineItem")) | |
| val selectedData = flattened.filter($"SequenceNumber" === "73" ).select($"RetailStoreID",$"WorkstationID", $"SequenceNumber",$"BusinessDayDate",$"OperatorID._OperatorName" as "OperatorName",$"OperatorID._VALUE" as "OperatorID",$"CurrencyCode",$"RetailTransaction.ReceiptDateTime",$"RetailTransaction.TransactionCount",$"LineItem.SequenceNumber",$"LineItem.Tax.TaxableAmount", $"LineItem.Tax.Amount" as "TaxAmount",$"LineItem.Tax.Percent" as "TaxPercent",$"LineItem.Sale.POSIdentity._POSIDType" as "POSIDType",$"LineItem.Sale.POSIdentity.POSItemID" as "POSItemID" ,$"LineItem.Sale.Description",$"LineItem.Sale.RegularSalesUnitPrice", $"LineItem.Sale.ExtendedAmount", $"LineItem.Sale.DiscountAmount", $"LineItem.Sale.ExtendedDiscountAmount", $"LineItem.Sale.Quantity",$"RetailTransaction.Total") | |
| selectedData.show() | |
| val headeronly = df.withColumn("Header", explode($"RetailTransaction.Total")) | |
| val headers = headeronly.filter($"SequenceNumber" === "73" ).select($"RetailStoreID",$"WorkstationID", $"SequenceNumber",$"BusinessDayDate",$"OperatorID._OperatorName" as "OperatorName",$"OperatorID._VALUE" as "OperatorID",$"CurrencyCode",$"Header._TotalType") | |
| headers.show() |
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