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RDFdist : RDF distribution approaches using Spark: 125 Occurrences trouvées

Partitioner(part)) // val triples = triples0.map{case(f,(s,p,o))=>((s+p+o),(s,p,o))}.partitionBy(new Ha... "+part+" partitions"); val oDist = triples.map{ case(f,(s,p,o)) => (f,1)}.reduceByKey( (a,b) => a+b) val oMean = oDist.map{case(f,c)=>c}.sum / machine val odevs = oDist.map{case(f,c)=>c}.map(score => (score - oMean) * (score - oMea

RDFdist: 125 Occurrences trouvées

Partitioner(part)) // val triples = triples0.map{case(f,(s,p,o))=>((s+p+o),(s,p,o))}.partitionBy(new Ha... "+part+" partitions"); val oDist = triples.map{ case(f,(s,p,o)) => (f,1)}.reduceByKey( (a,b) => a+b) val oMean = oDist.map{case(f,c)=>c}.sum / machine val odevs = oDist.map{case(f,c)=>c}.map(score => (score - oMean) * (score - oMea

Chain6 query plans: 17 Occurrences trouvées

SPARQL RDD: <code scala> val d1 = triples.filter{case(s,(p,o))=> p==P1}.map{case(x1,(p, x2))=> (x2, x1)} val d2 = triples.filter{case(s,(p,o))=> p==P2}.mapValues{case(p,x3) => x3} val d3 = triples.filter{case(s,(p,o))=> p==P3}.mapValues{

Chain4 query plans: 11 Occurrences trouvées

SPARQL RDD: <code scala> val d1 = triples.filter{case(s,(p,o))=> p==P1}.map{case(x1,(p, x2)) => (x2, x1)} val d2 = triples.filter{case(s,(p,o))=> p==P2}.mapValues{case(p,x3) => x3} val d3 = triples.filter{case(s,(p,o))=> p==P3}.mapValues{

Utilities: 11 Occurrences trouvées

} </code> === QUERY utilities === <code scala> case class v(n:Int) def sparqlSplit(sparql: List[(An... , (String, String), Any)] = { return sparql.map{case(s,p,o)=>(s,p.split(":"),o)}.map{case(s,p,o)=>(s,(p(0), p(1)), o)} } //persist VPs accessed by a query... Map[Int,org.apache.spark.sql.DataFrame])={ q.map{case(_,(ns,p),_) => vps(getIdP(ns, p)).persist().count

WatDiv Query C3 plans: 8 Occurrences trouvées

"givenName")) //persist all C3 VPs c3AllProp.map{case(ns, p) => VP2Random(getIdP(ns, p)).persist().coun... by increasing tp size val order = c3AllProp.map{ case(ns,p) => (p, getIdP(ns,p), VP2Size.get(getIdP(ns,p)).get)}.sortBy{case (p, idp, s)=> s} order.foreach(println) /* (Locat... ("wsdbm", "friendOf")) val l1 = orderedList.map{case(ns, p) => { val idP = getIdP(ns, p) VP2EXP(id

WatDiv Query S1 plans: 8 Occurrences trouvées

("gr", "price")) val triples = orderedProp.map{case(ns, p) => { val idP = getIdP(ns, p) DATA.wher... ("gr", "price")) val triples = orderedProp.map{case(ns, p) => { val idP = getIdP(ns, p) DATA.wher... ("sorg", "priceValidUntil")) val tpSize = tp.map{case(ns, p) => (p, getIdP(ns,p), VP2Size.get(getIdP(ns, p)).get)}.sortBy{case (p, idp, size)=> size} val selections = tpSize.ma

Supports Cours: 6 Occurrences trouvées

,Manufacturer#1,Brand#13,LARGE BRUSHED BRASS,1,LG CASE,902.00,final platelets hang f </code> En étant da... b.reduce(_+_)/tab.size val inner = lineitem .map{case(partkey,quantity,_)=>(partkey,quantity)} .groupB... lues(x=>.2*myAvg(x)) val outer = lineitem .map{case(partkey,quantity,extended)=>(partkey,(quantity,extended))} .join(part.map(x=>(x,null))) .map{case(partkey,((quantity,extended),_))=>(partkey,(quant

WatDiv Query F5 plans: 6 Occurrences trouvées

("s") val tp1a = t1.unionAll(e1) val l1 = s1.map{case(ns, p) => { val idP = getIdP(ns, p) DATA.wher... thColumnRenamed("o", s"o$idP")}} val l2 = s2.map{case(ns, p) => { val idP = getIdP(ns, p) DATA.wher... ("o").withColumnRenamed("o","s") val l1 = s1.map{case(ns, p) => { val idP = getIdP(ns, p) VP2EXP(id... ).withColumnRenamed(s"o$v1","s") val l2 = s2.map{case(ns, p) => { val idP = getIdP(ns, p) VP2EXP(id

[TME II-1] Introduction à Spark (Algèbre RDD): 6 Occurrences trouvées

eur identifié par son UserID val q2a = notes.map{case(userId,movieId,rating,ts)=>(userId,1)}.reduceByKe... ation donnée par le Zip-code val q2b = utilis.map{case(userId,gender,age,occup,zipcode)=>(userId,zipcode)} join(notes.map{case(userId,movieId,rating,ts)=>(userId,1)}) map{case (userId,(zipcode, nb))=>(zipcode, 1)} reduceByKey(_+_)

SnowFlake query Q8 plans: 5 Occurrences trouvées

tById.count val conceptByName = conceptById.map{ case (id, (name, start, length)) => (name, (id, start,... .count val propertyByName = propertyById. map{ case (id, (name, start, length)) => (name, (id, start,... aFrame contenant les données val d = triples.map{case(s,(p,o))=> (s,p,o)}.toDF("subject", "predicate", ... oupBy(x => x.getLong(0)) val c = b.flatMap{ case (s, rowList) => { // on sait qu'il y a a

Ancien TME 2016: Jointure parallèle: 5 Occurrences trouvées

,date) val jointureParDiffusion = RATINGSRDD.map{ case( user, N) => (user, N, UsersDiffusion.value(user)... 18 ans : <code scala> val U18 = USERSRDD.filter{ case(numU, (genre, age, profession, ville)) => age == ... (U18.collect.toMap) val j18 = RATINGSRDD.flatMap{ case(numU, note) => { U18Diffusion.value.get(numU) match { case Some(user) => Seq((numU,note,user)) case None

TME Données réparties et jointure parallèle: 5 Occurrences trouvées

lasses et Fonctions auxiliaires==== <code scala> case class Triplet(sujet: String, prop: String, objet:... sujet (s1=s2) val jointureParBroadcast = T2.map{ case(s2,o2) => (s2, o2, dicoReplique.value(s2)) } joi... c.broadcast(T1.collect.toMap) val J = T2.flatMap{ case(s2,o2) => { dicoReplique.value.get(o2) match { case Some(o1) => Seq((s2,o2, o1)) case None => Seq

EPIQUE Project Description: 4 Occurrences trouvées

rs of science involved in the project will design case studies (esp. in biology, ecology, economics) of ... f “diversity” or of “function” in ecology); those case studies will in turn contribute to fine-tune the ... ogy. Sociologists and historians have indeed good case studies on the building, structure and dissipatio... ocus was not on efficiency and interaction in the case of large corpora. ==== Patent mining and visual

EPIQUE Project Description: 4 Occurrences trouvées

Oracle avec SQLWorkbench: 4 Occurrences trouvées

Star shape query plans: 4 Occurrences trouvées

[Pré-requis] Introduction à Scala: 3 Occurrences trouvées

Recueil d'examens: 3 Occurrences trouvées

TME PL/SQL: 2 Occurrences trouvées

Loading WatDiv Dataset: 2 Occurrences trouvées

TME XQuery: 1 Occurrences trouvées

Economical context : the "Bloggy" Web: 1 Occurrences trouvées

Project description: 1 Occurrences trouvées

Mobility for epidemiology: 1 Occurrences trouvées

TME 8 JDBC (ancien): 1 Occurrences trouvées

Topic Extraction and Alignment for Large Scientific Document Collections: 1 Occurrences trouvées

TME XQuery : séance 1 (ancienne page): 1 Occurrences trouvées

TME 1 - SQL avancé sur la base Mondial: 1 Occurrences trouvées

[TME II-2] Algèbre Spark: Dataset: 1 Occurrences trouvées