I recommend you here using ReactiveStateEngine to convert cumulative volume to volume and then connecting two engines in series. Here is an example:
tradesData = your_tick_data
//define Trade Table
x=tradesData.schema().colDefs
share streamTable(100:0, x.name, x.typeString) as Trade
//define OHLC outputTable
share streamTable(100:0, `datetime`symbol`open`high`low`close`volume`updatetime,[TIMESTAMP,SYMBOL,DOUBLE,DOUBLE,DOUBLE,DOUBLE,LONG,TIMESTAMP]) as OHLC
//1 min OHLC TimeSeriesEngine
tsAggrOHLC = createTimeSeriesAggregator(name="aggr_ohlc", windowSize=60000, step=60000, metrics=<[first(Price),max(Price),min(Price),last(Price),wavg(Price,Volume),now()]>, dummyTable=Trade, outputTable=OHLC, timeColumn=`Datetime, keyColumn=`Symbol)
//ReactiveStateEngine:convert cumulative volume to volume
rsAggrOHLC = createReactiveStateEngine(name="calc_vol", metrics=<[Datetime, Price, deltas(Volume) as Volume]>, dummyTable=Trade, outputTable=tsAggrOHLC, keyColumn=`Symbol)
//subscribe table and insert data into engines
subscribeTable(tableName="Trade", actionName="minuteOHLC2", offset=0, handler=append!{rsAggrOHLC}, msgAsTable=true)
replay(inputTables=tradesData, outputTables=Trade, dateColumn=`Datetime)
You can use your user defined function in any of the engine's matrics.