Conference paper (in proceedings)
      
      
     
    
      Towards dynamic SQL compilation in Apache Spark
      
      
        
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
      
        
        Published in:
        
          
            
            - Companion Proceedings of the 4th International Conference on the Art, Science, and Engineering of Programming (<Programming’20> Companion), March 23–26, 2020, Porto, Portugal. - 2020, p. 4 p.
 
       
      
      
      
      
      
       
      
      
      
        
        English
        
        
        
          Big-data systems have gained significant momentum, and Apache Spark is becoming a de-facto standard for modern data analytics. Spark relies on code generation to optimize the execution performance of SQL queries on a variety of data sources. Despite its already efficient runtime, Spark’s code generation suffers from significant runtime overheads related to data de-serialization during query execution. Such performance penalty can be significant, especially when applications operate on human-readable data formats such as CSV or JSON.
        
        
       
      
      
      
        
        
        
        
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                  Computer science and technology
                
              
            
          
        
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          Open access status
        
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          green
        
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          Persistent URL
        
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          https://n2t.net/ark:/12658/srd1324935
        
 
   
  
  
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