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--- en:site:recherche:logiciels:sparqlwithspark:watdivf5 [14/09/2016 14:53] – created hubert
+++ en:site:recherche:logiciels:sparqlwithspark:watdivf5 [16/09/2016 23:07] (current) – [WatDiv Query F5 plans] hubert
@@ Line 1: / Line 1: @@
-====== Query F5 ======
+{{indexmenu_n>3}}
-SPARQL Hybrid DF plan
-<code>
+====== WatDiv Query F5 plans======
-// 1st triple pattern
+=== SPARQL Hybrid DF plan ===
+<code scala>
+// First triple pattern
 val retailer = getIdSO("wsdbm", "Retailer3")
-val t1 = VP2EXP(getIdP("gr", "offers")).where(s"s=$retailer").select("o").withColumnRenamed("o","s")
+val idP1 = getIdP("gr", "offers")
-val e1 = sc.parallelize(1 to NB_FRAGMENTS, NB_FRAGMENTS).map(x => -1).toDF("s")
+val s1 = List(
-val t1OK = t1.unionAll(e1)
-val orderedList1 = List(
   ("gr","validThrough"),
   ("gr", "includes"),
   ("gr", "price"))
-val orderedList2 = List(
+val s2 = List(
   ("og", "title"),
   ("rdf", "type"))
-val l1 = orderedList1.map{case(ns, p) => {
+val subset = df.where(s"(p=$idP1 and s=$retailer) or p in (3,12,26,38,57)").persist
+subset.count
+val DATA = subset
+val tp1 = DATA.where(s"s=$retailer").select("o").withColumnRenamed("o","s")
+val e1 = sc.parallelize(1 to NB_FRAGMENTS, NB_FRAGMENTS).map(x => -1).toDF("s")
+val tp1a = t1.unionAll(e1)
+val l1 = s1.map{case(ns, p) => {
+  val idP = getIdP(ns, p)
+  DATA.where(s"p=$idP").select("s","o").withColumnRenamed("o", s"o$idP")}}
+val l2 = s2.map{case(ns, p) => {
+  val idP = getIdP(ns, p)
+  DATA.where(s"p=$idP").select("s","o").withColumnRenamed("o", s"o$idP")}}
+val v1 = getIdP("gr", "includes")
+val snf1 = tp1a.join(l1(0),"s").join(l1(1),"s").join(l1(2),"s").withColumnRenamed("s", "v0").withColumnRenamed(s"o$v1","s")
+val query = snf1.join(l2(0),"s").join(l2(1),"s")
+</code>
+=== S2RDF plan ===
+<code scala>
+val VP2EXP=VP2Random
+val tp1 = VP2EXP(getIdP("gr", "offers")).where(s"s=$retailer").select("o").withColumnRenamed("o","s")
+val l1 = s1.map{case(ns, p) => {
   val idP = getIdP(ns, p)
   VP2EXP(idP).withColumnRenamed("o", s"o$idP")}}
-val l2 = orderedList2.map{case(ns, p) => {
+val v1 = getIdP("gr", "includes")
+val snf1 = tp1.join(l1(0),"s").join(l1(1),"s").join(l1(2),"s").withColumnRenamed("s", "v0").withColumnRenamed(s"o$v1","s")
+val l2 = s2.map{case(ns, p) => {
+  val idP = getIdP(ns, p)
+  VP2EXP(idP).withColumnRenamed("o", s"o$idP")}}
+val query = snf1.join(l2(0),"s").join(l2(1),"s")
+</code>
+=== S2RDF + Hybrid plan ===
+<code scala>
+val VP2EXP=VP2Subject
+val s1 = List(
+  ("gr","validThrough"),
+  ("gr", "includes"),
+  ("gr", "price"))
+val s2 = List(
+  ("og", "title"),
+  ("rdf", "type"))
+// First triple pattern
+val retailer = getIdSO("wsdbm", "Retailer3")
+val tp1 = VP2EXP(getIdP("gr", "offers")).where(s"s=$retailer").select("o").withColumnRenamed("o","s")
+val e1 = sc.parallelize(1 to NB_FRAGMENTS, NB_FRAGMENTS).map(x => -1).toDF("s")
+val tp1a = tp1.unionAll(e1)
+val l1 = s1.map{case(ns, p) => {
   val idP = getIdP(ns, p)
   VP2EXP(idP).withColumnRenamed("o", s"o$idP")}}
 val v1 = getIdP("gr", "includes")
-val snf1 = t1OK.join(l1(0),"s").join(l1(1),"s").join(l1(2),"s").withColumnRenamed("s", "v0").withColumnRenamed(s"o$v1","s")
+val snf1 = tp1a.join(l1(0),"s").join(l1(1),"s").join(l1(2),"s").withColumnRenamed("s", "v0").withColumnRenamed(s"o$v1","s")
+val l2 = s2.map{case(ns, p) => {
+  val idP = getIdP(ns, p)
+  VP2EXP(idP).withColumnRenamed("o", s"o$idP")}}
 val query = snf1.join(l2(0),"s").join(l2(1),"s")
 </code>
+Go to [[en:site:recherche:logiciels:sparqlwithspark]]