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Trace: • Projets • Schema Inference from Massive JSON Datasets • Recherche • Stages 2022 • Bernd Amann
en:site:recherche:logiciels:sparqlwithspark:chain4

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en:site:recherche:logiciels:sparqlwithspark:chain4 [14/09/2016 12:38] – huberten:site:recherche:logiciels:sparqlwithspark:chain4 [16/09/2016 23:10] (current) – [Chain4 query plans] hubert
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-====== Chain4 query======+{{indexmenu_n>6}} 
 + 
 + 
 +====== Chain4 query plans======
  
 The plans produced by each method are: The plans produced by each method are:
   * SPARQL RDD:   * SPARQL RDD:
-<code>+ 
 +<code scala>
 val d1 = triples.filter{case(s,(p,o))=> p==P1}.map{case(x1,(p, x2)) => (x2, x1)} 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 d2 = triples.filter{case(s,(p,o))=> p==P2}.mapValues{case(p,x3) => x3}
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   * SPARQL DF:   * SPARQL DF:
-<code>+<code scala>
 val t1 = df.where(s"p=$P1").select("s","o").withColumnRenamed("s", "x1").withColumnRenamed("o", "x2") val t1 = df.where(s"p=$P1").select("s","o").withColumnRenamed("s", "x1").withColumnRenamed("o", "x2")
 val t2 = df.where(s"p=$P2").select("s","o").withColumnRenamed("s", "x2").withColumnRenamed("o", "x3") val t2 = df.where(s"p=$P2").select("s","o").withColumnRenamed("s", "x2").withColumnRenamed("o", "x3")
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   * SPARQL Hybrid DF:   * SPARQL Hybrid DF:
-<code>+<code scala>
 val subg = df.where(s"p in ($P2, $P3, $P4)") val subg = df.where(s"p in ($P2, $P3, $P4)")
 subg.persist subg.persist
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 </code> </code>
  
-Go to [[en:site:recherche:logiciels:sparqlwithspark| other queries]]+Go to [[en:site:recherche:logiciels:sparqlwithspark]]
en/site/recherche/logiciels/sparqlwithspark/chain4.1473849525.txt.gz · Last modified: by hubert