Anatomy of a translating compiler

How to build a programming language in Scala?

Transcript

1. Anatomy of a translating compiler … or how to use debugger all the time. 1 Serge Smertin Senior Resident Solutions Architect Databricks
3. Apache Spark query execution recap
4. 4 code IN(4*, 5*)
5. 5 code IN(4*, 5*)
6. 6 code IN(4*, 5*)
7. 7 SearchCommand( FieldIn("code", Seq( Wildcard("4*"), Wildcard("5*") )))
8. 8 SearchCommand( FieldIn("code", Seq( Wildcard("4*"), Wildcard("5*") ))) Or( Like(UnresolvedAttribute("code"), Literal.create("4%"), '\\'), Like(UnresolvedAttribute("code"), Literal.create("5%"), '\\'))
9. 9 SearchCommand( FieldIn("code", Seq( Wildcard("4*"), Wildcard("5*") ))) Or( Like(UnresolvedAttribute("code"), Literal.create("4%"), '\\'), Like(UnresolvedAttribute("code"), Literal.create("5%"), '\\')) private def expression(ctx: LogicalContext , expr: ast.Expr): Expression = expr match { case ast.FieldIn(field, exprs) if exprs.exists(_.isInstanceOf[ast.Wildcard]) => val expand = (expr: ast.Expr) => ast.Binary(ast.Field(field), ast.Equals, expr) expression(ctx, exprs.tail.foldLeft(expand(exprs.head)) { (left, right) => ast.Binary(left, ast.Or, expand(right)) }) case ast.FieldIn(field, exprs) => In(UnresolvedAttribute(field), exprs.map(expression(ctx, _))) case ast.Binary(left, ast.Equals, ast.Wildcard(pattern)) => like(ctx, left, pattern) case ast.Binary(left, symbol, right) => symbol match { case ast.Or => Or(attrOrExpr(ctx, left), attrOrExpr(ctx, right)) // ... } // ... }
10. 10 SearchCommand( FieldIn("code", Seq( Wildcard("4*"), Wildcard("5*") ))) Or( Like(UnresolvedAttribute("code"), Literal.create("4%"), '\\'), Like(UnresolvedAttribute("code"), Literal.create("5%"), '\\')) display(spark.table('main') .where((F.col('code').like('4%') | F.col('code').like('5%'))))
11. 11 SearchCommand( FieldIn("code", Seq( Wildcard("4*"), Wildcard("5*") ))) Or( Like(UnresolvedAttribute("code"), Literal.create("4%"), '\\'), Like(UnresolvedAttribute("code"), Literal.create("5%"), '\\')) display(spark.table('main') .where((F.col('code').like('4%') | F.col('code').like('5%')))) case relation: UnresolvedRelation => s"spark.table(${q(relation.name)})" private def unfoldWheres(expr: Expression): String = expr match { case And(left, right) => s"${unfoldWheres(left)}\n${unfoldWheres(right)}" case _ => s".where(${expressionCode(expr)})" } private def expressionCode(expr: Expression): String = expr match { case b: BinaryOperator => val symbol = jvmToPythonOverrides.getOrElse(b.symbol, b.symbol) s"(${expressionCode(b.left)} $symbol ${expressionCode(b.right)})" case attr: UnresolvedAttribute => s"F.col(${q(attr.name)})" case Like(col, Literal(value, _ @ StringType), _) => s"${expressionCode(col)}.like('$value')" case _ => s"F.expr(${q(expr.sql)})" }