225 lines
4.2 KiB
Plaintext
225 lines
4.2 KiB
Plaintext
/*
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1 Creating a Database
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*/
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create database taxis;
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open database taxis;
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/*
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Adapt the following:
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*/
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restore Workers from WorkersNewton;
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let NSlots = 40;
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let NSlots2 = 120;
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let myPort = 1238
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/*
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2 Data Import
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2.1 Sequential Import and Distribution from the Master
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*/
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let Start = createintdarray("Start", Workers);
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delete Start;
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let RawDataById =
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[const rel(tuple([Id: int, DateTime: string, Point: string])) value ()]
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csvimport['cabsrome/taxidata00', 0, "", ";", FALSE, FALSE]
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projectextend[Id
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; Inst: str2instant(substr(.DateTime, 1, 10) + "-" + substr(.DateTime, 12, 23)),
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Pos: makepoint(
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str2real(
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substr(.Point, findFirst(.Point, " ") + 1, findFirst(.Point, ")") - 1)),
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str2real(
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substr(.Point, findFirst(.Point, "(") + 1, findFirst(.Point, " ") - 1))
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)]
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ddistribute4["RawDataById", hashvalue(.Id, 999997) , NSlots, Workers]
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/*
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3 Creating Moving Objects
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*/
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let CabsTrips = RawDataById
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dmap["CabsTrips",
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. feed sortby[Id, Inst]
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groupby[Id; TotalTrip: group feed
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approximate[Inst, Pos, TRUE, create_duration(0, 60000)]
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removeNoise[35.0, 2000.0, create_geoid("WGS1984")] ]
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projectextendstream[Id; Trip: .TotalTrip
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sim_trips[create_duration(0, 180000), 100.0, create_geoid("WGS1984")] ]
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filter[no_components(.Trip) > 1]
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consume
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]
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/*
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4 Multiplying the Dataset
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*/
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let bboxR = CabsTrips
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dmap["", . feed projectextend[; Box: bbox(.Trip)] transformstream
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collect_box[FALSE]]
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dsummarize collect_box[FALSE]
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let deltax = maxD(bboxR, 1) - minD(bboxR, 1);
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let deltay = maxD(bboxR, 2) - minD(bboxR, 2)
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query share("deltax", TRUE, Workers);
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query share("deltay", TRUE, Workers);
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let CabsId = CabsTrips
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dmap["", . feed
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loopsel[fun(t: TUPLE)
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intstream(0, 4) namedtransformstream[Nx]
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intstream(0, 1) namedtransformstream[Ny]
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product
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projectextend[
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; Id: attr(t, Id) + ((5 * .Ny) + .Nx) * 1000,
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Trip: attr(t, Trip)
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translate[[const duration value (0 0)], .Nx * deltax, .Ny * deltay]]
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]
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]
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partition["", hashvalue(.Id, 999997), 0]
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collect2["", myPort]
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dmap["CabsId", . feed consume]
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/*
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5 Partitioning
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5.1 Partitioning by Object identifier
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5.2 Spatio-temporal Partitioning
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*/
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let bboxR10 = CabsId
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dmap["", . feed projectextend[; Box: bbox(.Trip)] transformstream
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collect_box[TRUE]]
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dsummarize collect_box[TRUE]
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let grid = createCellGrid3D(11.0, 41.0, 5140.0, 2.0, 1.5, 5.0, 4, 2)
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query share("grid", TRUE, Workers)
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let CabsST = CabsId
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partitionF["", . feed
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extendstream[Cell: cellnumber(bbox(.Trip), grid)]
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extend[Box: bbox(.Trip)],
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..Cell, 0]
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collect2["", myPort]
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dmap["CabsST", . feed consume]
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/*
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6 Indexing
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6.1 By Identifier
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*/
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let CabsId_Id_btree = CabsId dmap["CabsId_Id_btree", . createbtree[Id]]
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/*
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6.2 By Spatio-temporal Information
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*/
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let CabsST_Trip_rtree = CabsST
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dmap["CabsST_Trip_rtree", . feed addid
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extend[ScaledBox: scalerect(.Box, 1000000.0, 1000000.0, 1000.0)]
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sortby[ScaledBox]
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remove[ScaledBox]
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bulkloadrtree[Box]
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]
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/*
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7 Querying
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7.1 By Identifier
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*/
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query CabsId_Id_btree CabsId
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dmap2["", . .. exactmatch[11], myPort]
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dsummarize consume
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/*
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7.2 By Spatio-temporal Dimension
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*/
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let qObject = rectangle3(12.464446, 12.5013, 41.879938, 41.911759,
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instant2real(theInstant(2014, 02, 01, 19)),
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instant2real(theInstant(2014, 02, 01, 20)));
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query share("qObject", TRUE, Workers)
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query CabsST_Trip_rtree CabsST
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dmap2["", . .. windowintersects[qObject]
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filter[gridintersects(grid, qObject, bbox(.Trip), .Cell)]
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filter[.Trip passes rectproject(qObject, 1, 2) rect2region]
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filter[.Trip present rect2periods(qObject)],
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myPort]
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dsummarize consume
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query hashvalue(11, 999997);
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query cellnumber(qObject, grid) consume
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query hashvalue(11, 999997) feed CabsId_Id_btree CabsId
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pdmap2["", . .. exactmatch[11], myPort]
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dsummarize consume
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query cellnumber(qObject, grid) CabsST_Trip_rtree CabsST
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pdmap2["", . .. windowintersects[qObject]
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filter[gridintersects(grid, qObject, bbox(.Trip), .Cell)]
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filter[.Trip passes rectproject(qObject, 1, 2) rect2region]
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filter[.Trip present rect2periods(qObject)], myPort]
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dsummarize consume
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