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This documentation is for version v2.5 of the product.
For the latest version(v2.7) documentation click here
Version: v2.5 print this page

Join Using SQL

This node registers the incoming DataFrames as temporary tables and executes the SQL provided

Input

It takes in 2 DataFrames as input and produces one DataFrame as output by executing the provided SQL.

Output

The DataFrame created as a result of executing the join SQL

Type

join

Fields

NameTitleDescription
tempTable1Temp Table1Temp Table Name to be used
tempTable2Temp Table2Temp Table Name to be used
tempTable3Temp Table3Temp Table Name to be used
tempTable4Temp Table4Temp Table Name to be used
tempTable5Temp Table5Temp Table Name to be used
sqlSQLSQL to be run
outputColNamesColumn Names for the CSVNew Output Columns of the SQL
outputColTypesColumn Types for the CSVData Type of the Output Columns
outputColFormatsColumn Formats for the CSVFormat of the Output Columns

Input1

txiditemiddatepyidamount
100100012019-09-2001100
100200012019-09-2002100

Input2

py_idpay_txidpay_typeamount
011001credt_card60
011001redme_coupon20
011001redme_emp_offer20
021002credt_card160
021002redme_coupon40

Parameters

NameValue
Temp Table1transaction_temp_table
Temp Table2payment_temp_table
SQLselect a.txid, a.itemid, a.date, a.pyid, a.amount as total_amount, b.pay_type, b.amount from transaction_temp_table a JOIN payment_temp_table b ON(a.txid = b.pay_txid and a.pyid = b.py_id)

Refresh the Schema tab.

Output

txiditemiddatepyidtotal_amountpay_typeamount
100100012019-09-2001100credt_card60
100100012019-09-2001100redme_coupon20
100100012019-09-2001100redme_emp_offer20
100200012019-09-2002100credt_card160
100200012019-09-2002100redme_coupon40