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fix: performance: Speed up PostingsReport when called with a large number of intervals. (#1683)
It is still very slow for large journals, but at least it doesn't run any slower for interval reports.
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@ -21,9 +21,10 @@ module Hledger.Reports.PostingsReport (
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)
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where
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import Data.List (nub, sortOn)
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import Data.List (nub, sortBy, sortOn)
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import Data.List.Extra (nubSort)
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import Data.Maybe (fromMaybe, isJust, isNothing)
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import Data.Ord (comparing)
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import Data.Text (Text)
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import Data.Time.Calendar (Day)
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import Safe (headMay)
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@ -174,10 +175,26 @@ mkpostingsReportItem showdate showdesc wd mperiod p b =
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-- aggregated to the specified depth if any.
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-- Each summary posting will have a non-Nothing interval end date.
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summarisePostingsByInterval :: Interval -> WhichDate -> Maybe Int -> Bool -> DateSpan -> [Posting] -> [SummaryPosting]
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summarisePostingsByInterval interval wd mdepth showempty reportspan ps = concatMap summarisespan $ splitSpan interval reportspan
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summarisePostingsByInterval interval wd mdepth showempty reportspan =
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concatMap (\(s,ps) -> summarisePostingsInDateSpan s wd mdepth showempty $ map snd ps)
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-- Group postings into their columns. We try to be efficient, since
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-- there can possibly be a very large number of intervals (cf #1683)
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. groupByCols colspans
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. dropWhile (beforeStart . fst)
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. sortBy (comparing fst)
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. map (\p -> (getDate p, p))
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where
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summarisespan s = summarisePostingsInDateSpan s wd mdepth showempty (postingsinspan s)
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postingsinspan s = filter (isPostingInDateSpan' wd s) ps
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groupByCols [] _ = []
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groupByCols (c:cs) [] = if showempty then (c,[]) : groupByCols cs [] else []
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groupByCols (c:cs) ps = (c, matches) : groupByCols cs later
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where (matches, later) = span ((spanEnd c >) . Just . fst) ps
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-- The date spans to be included as report columns.
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colspans = splitSpan interval reportspan
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beforeStart = maybe (const True) (>) $ spanStart =<< headMay colspans
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getDate = case wd of
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PrimaryDate -> postingDate
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SecondaryDate -> postingDate2
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-- | Given a date span (representing a report interval) and a list of
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-- postings within it, aggregate the postings into one summary posting per
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