open database nrw_node1;

let grid = [const cellgrid2d value (7.29 51.37 0.025 0.025 20)];

#query share ("grid", TRUE);

#for Hagen- db only: let grid = [const cellgrid2d value (7.34 51.12 0.016 0.016 20)]

### added

query share("grid", TRUE, SEC2WORKERS);

let eichlinghofen = [const region value ( 
    ( 
        ( 
            (7.394967670776298 51.47332155746125)
            (7.419515247680575 51.47332155746125)
            (7.419515247680575 51.48716614802665)
            (7.394967670776298 51.48716614802665))))];
            
let EichlinghofenUpper = eichlinghofen;

### added

query share("eichlinghofen", TRUE, SEC2WORKERS)

### added

query share("EichlinghofenUpper", TRUE, SEC2WORKERS)

#random distribution of the Roads relation
let RoadsDfRandom = Roads feed dfdistribute3["RoadsDfRandom", 50, TRUE, SEC2WORKERS];

#B.Huber
#The following datatypes are only to get cost constants, without any entry in 
#the systemtables SEC2DISTRIBUTED or SEC2DISTINDEXES.

let BuildingsDfRandom = Buildings feed dfdistribute3["", 50, TRUE, SEC2WORKERS];

let BuildingsOsmIdLT3 = Buildings feed filter[substr(.Osm_id,1,1) < '3'] consume;
let BuildingsOsmIdGE3 = Buildings feed filter[substr(.Osm_id,1,1) >= '3'] consume;

let BuildingsDfLT3 = BuildingsOsmIdLT3 feed dfdistribute3["", 50, TRUE, SEC2WORKERS];
let BuildingsDfGE3 = BuildingsOsmIdGE3 feed dfdistribute3["", 50, TRUE, SEC2WORKERS];

let BuildingsDfLT3Matrix = BuildingsDfLT3 partitionF["", .  feed, hashvalue(..Osm_id, 999997), 0];
let BuildingsDfGE3Matrix = BuildingsDfGE3 partitionF["", .  feed, hashvalue(..Osm_id, 999997), 0];

let BuildingsDfGE3Reduce = BuildingsDfGE3Matrix areduce["",. feed ,1236];

let BuildingsDfLT3Collect = BuildingsDfLT3Matrix collect2["",1236];
let BuildingsDfGE3Collect = BuildingsDfGE3Matrix collect2["",1236];

let BuildingsDfLT3_10000 = BuildingsOsmIdLT3 feed head[10000] dfdistribute3["", 50, TRUE, SEC2WORKERS];
let BuildingsDfLT3_200000 = BuildingsOsmIdLT3 feed head[200000] dfdistribute3["", 50, TRUE, SEC2WORKERS];

let BuildingsDfGE3_10000 = BuildingsOsmIdLT3 feed head[10000] dfdistribute3["", 50, TRUE, SEC2WORKERS];
let BuildingsDfGE3_200000 = BuildingsOsmIdGE3 feed head[200000] dfdistribute3["", 50, TRUE, SEC2WORKERS];


#B.Huber end



# 1:59 min

#Roads distribution with spatial attribute 
let RoadsDfSpatial = RoadsDfRandom partitionF["", . feed extend[EnlargedBox: enlargeRect(bbox(.GeoData), 0.01, 0.01)] extendstream[Cell: cellnumber(.EnlargedBox, grid)] extend[Original: .Cell = cellnumber(.EnlargedBox, grid) transformstream extract[Elem]], ..Cell, 0] collect2["RoadsDfSpatial", 54321];

let 

# 2:53 min

#distribute places  
let PlacesDfModuloPop = Places feed dfdistribute2["PlacesDfModuloPop", Population,50, SEC2WORKERS];

# 2.3 sec

#create BuildingsDSpatialIndex as darray distributed over geometry- attribute via grid
let BuildingsDSpatialIndex = Buildings feed extend[EnlargedBox: enlargeRect(bbox(.GeoData), 0.01, 0.01)] extendstream[Cell: cellnumber(.EnlargedBox, grid)] extend[Original: .Cell = cellnumber(.EnlargedBox, grid) transformstream extract[Elem]] ddistribute2["BuildingsDSpatialIndex", Cell, 50, SEC2WORKERS];

#spatial index for buildings
let BuildingsDSpatialIndex_GeoData = BuildingsDSpatialIndex dloop["", . feed addid extend[Box: scalerect(.EnlargedBox, 1000000.0, 1000000.0)] sortby[Box] remove[Box] bulkloadrtree[EnlargedBox]];

#distribute Waterways 
let WaterwaysDFunction = Waterways feed ddistribute4["WaterwaysDFunction", hashvalue(.Type, 999997),50, SEC2WORKERS];

#replicate railways
query share ("Railways", TRUE, SEC2WORKERS);

#distribute Natural and create index
let NaturalDFunctionIndex = Natural feed ddistribute4["NaturalDFunctionIndex", hashvalue(.Type, 999997),50, SEC2WORKERS];
let NaturalDFunctionIndex_Type = NaturalDFunctionIndex dloop["NaturalDFunctionIndex_Type", . createbtree[Type]];

close database;