| data Summary = Summary { | |
| count :: Int | |
| , list1 :: Map Text Int | |
| } deriving (Generic, Show) | |
| instance ToJSON Summary where | |
| toJSON (Summary {..}) = object [ | |
| "count" .= count | |
| , "list1" .= sortBy (comparing snd) $ toList names :: [(Text, Int)] | |
| ] |
| {- | |
| This program parses a zip file and for each entry in the zip generates two lists of strings. | |
| The lists of strings contain many values, some of which would be the same and some will be different. | |
| I would like to count the number of instances of each string in both lists. | |
| eg ["a1", "b1", "aa1", "aa1, "a1"] -> ["a1" -> 2, "b1" -> 1, "aa1" -> 2 ] | |
| The zip contains very many small files. |
| import Codec.Archive.Zip (sourceEntry, EntrySelector, getEntrySource, getEntry, getEntryName, getEntries, withArchive) | |
| import Control.Monad.IO.Class (MonadIO, liftIO) | |
| import Data.ByteString (ByteString) | |
| --import Data.Foldable (for) | |
| import Conduit (mapC, mapM_C, yieldMany, ($$)) | |
| import Data.Conduit (Conduit(..), yield, runConduit, (.|), awaitForever) | |
| import Data.Conduit.Binary as CB | |
| import qualified Data.Conduit.List as CL | |
| import qualified Data.Csv as Csv |
| [1 of 3] Compiling Codec.Archive.Zip.Util ( src/Codec/Archive/Zip/Util.hs, .stack-work/dist/x86_64-linux/Cabal-2.4.0.1/build/Codec/Archive/Zip/Util.o ) | |
| /home/www/projects/datamine/components/zip-conduit-0.2.2.2/src/Codec/Archive/Zip/Util.hs:110:25: warning: [-Wdeprecations] | |
| In the use of type constructor or class ‘Sink’ | |
| (imported from Data.Conduit, but defined in conduit-1.3.1.1:Data.Conduit.Internal.Conduit): | |
| Deprecated: "Use ConduitT directly" | |
| | | |
| 110 | crc32Sink :: Monad m => Sink ByteString m Word32 | |
| | ^^^^ | |
| // run using: node --expose_gc loop_reduce_test.ts | |
| // to allow for high precision timing | |
| function arrayReduceTest(ary) { | |
| return ary.reduce((acc, x) => { | |
| return acc + x; | |
| }, 0); | |
| } |
A very common pattern in relational databases is the use of a join table to create one-to-many or many-to-many relationships between entities.
eg, something like:
CREATE TABLE table1 (
id serial PRIMARY KEY
, acolumn character varying);
CREATE TABLE table2 (
| /* | |
| This is a simple node program originally written to import a large volume of data | |
| stored in XML files and import it into a postgres database. | |
| It uses the async library to implement paralell processing with a concurrency of 20. | |
| Adjusting the concurrency can alter the performance depending on the machine and the | |
| exact workload. | |
| The program is single threaded, so for multi-core machines you might want to consider | |
| using the cluster.js library to implement multi-threading for further increases in |