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The following query is needed to run in the production environment where the conversion_rate table is to be updated manually(static table) while the data in the ledger table should always be up to date as per the data in the transactions table: spark . readStream . format ( 'delta' ) . table ( 'transactions' ) . join ( table ( 'conversion_rate' ), 'currency' , 'left' ) . writeStream . option ( 'checkpointLocation' , '/tmp/ledger' ) . trigger ( processingTime = '30 minutes’) .format(' delta ') .table(' ledger ') Which of the following is true about the join’s functionality?