minDate <- "2014-01-01"
dateCol <- c("activityperiodid")

DT.label_ranks <- makeQry(tbl="fact_sales", schema="production", colsToAgg="gross", colsToPull=c("activityperiodid", "labelid", "storeid"), dateCol=dateCol, minDate=minDate, limit=NULL) %>% runQry(cluster=7)


addDateCols.periodid_(DT.label_ranks)

DT.label_ranks <- DT.label_ranks[activitydate >= minDate]
DT.label_ranks[, yr := year(activitydate)]
DT.label_ranks[, activityperiodid := NULL]

DT.label_ranks.spot <- aggregateDT(DT.label_ranks[storeid == 286], exclude="activitydate", colsToAgg="gross")
DT.label_ranks.spot[, ranking := rank(-gross, na.last=TRUE, ties="min"), by=list(storeid, yr)]

reshape2::dcast(DT.label_ranks.spot[ranking <= 25], labelid ~ yr, value.var=c("gross", "ranking"))

DT.label_ranks.spot[, storeid := NULL]
DT.label_ranks.spot[ranking <= 25][, sapply(yr, paste0, c("_gross", "_ranking")) %>% setNames(obj=data.table(gross[[1]], ranking[[2]], gross[[2]], ranking[[2]])), by=labelid]

DT.label_ranks.spot[ranking <= 25 & yr == 2014][order(ranking, decreasing=TRUE)]

&&& LEFT OFF HERE ... zipper combine gross and ranking
zipperCombine

DT.label_ranks.spot[]