optimization on product and select working
git-svn-id: http://galileo.dmi.unict.it/svn/relational/trunk@164 014f5005-505e-4b48-8d0a-63407b615a7c
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LtWorf
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@ -213,6 +213,7 @@ def swap_rename_select(n):
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them with ρ j(σ k(R)). Renaming the attributes used in the
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selection, so the operation is still valid.'''
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#TODO document into the wiki
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#FIXME selection of date.day won't work.
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changes=0
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if n.name=='σ' and n.child.name=='ρ':
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@ -248,4 +249,117 @@ def swap_rename_select(n):
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changes+=swap_rename_select(n.left)
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return changes
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def selection_and_product(n,rels):
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'''This function locates things like σ k (R*Q) and converts them into
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σ l (σ j (R) * σ i (Q)). Where j contains only attributes belonging to R,
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i contains attributes belonging to Q and l contains attributes belonging to both'''
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#TODO document in the wiki
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changes=0
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if n.name=='σ' and n.child.name=='*':
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changes=1
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l_attr=n.child.left.result_format(rels)
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r_attr=n.child.right.result_format(rels)
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tokens=tokenize_select(n.prop)
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groups=[]
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temp=[]
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for i in tokens:
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if i=='and':
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groups.append(temp)
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temp=[]
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else:
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temp.append(i)
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if len(temp)!=0:
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groups.append(temp)
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temp=[]
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left=[]
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right=[]
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both=[]
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print "Attributi R",r_attr, "Attributi L",l_attr
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print "Gruppi",groups
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for i in groups:
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l_fields=False #has fields in left?
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r_fields=False #has fields in left?
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for j in i:
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if j in l_attr:#Field in left
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l_fields=True
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if j in r_attr:#Field in right
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r_fields=True
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if l_fields and r_fields:#Fields in both
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both.append(i)
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elif l_fields:
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left.append(i)
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elif r_fields:
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right.append(i)
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else:#Unknown.. adding in both
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both.append(i)
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print "left", left, "right",right,"both",both
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#Preparing left selection
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if len(left)>0:
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l_node=optimizer.node()
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l_node.name='σ'
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l_node.kind=optimizer.UNARY
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l_node.child=n.child.left
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l_node.prop=''
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n.child.left=l_node
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while len(left)>0:
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c=left.pop(0)
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for i in c:
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l_node.prop+=i+ ' '
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if len(left)>0:
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l_node.prop+=' and '
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#Preparing right selection
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if len(right)>0:
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r_node=optimizer.node()
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r_node.name='σ'
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r_node.prop=''
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r_node.kind=optimizer.UNARY
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r_node.child=n.child.right
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n.child.right=r_node
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while len(right)>0:
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c=right.pop(0)
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for i in c:
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r_node.prop+=i+ ' '
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if len(right)>0:
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r_node.prop+=' and '
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#Changing main selection
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n.prop=''
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if len(both)!=0:
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while len(both)>0:
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c=both.pop(0)
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for i in c:
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n.prop+=i+ ' '
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if len(both)>1:
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n.prop+=' and '
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else:#No need for general select
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n.name=n.child.name
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n.kind=n.child.kind
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n.left=n.child.left
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n.right=n.child.right
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#recoursive scan
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if n.kind==optimizer.UNARY:
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changes+=selection_and_product(n.child,rels)
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elif n.kind==optimizer.BINARY:
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changes+=selection_and_product(n.right,rels)
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changes+=selection_and_product(n.left,rels)
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return changes
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general_optimizations=[duplicated_select,down_to_unions_subtractions_intersections,duplicated_projection,selection_inside_projection,subsequent_renames,swap_rename_select]
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specific_optimizations=[selection_and_product]
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@ -39,11 +39,7 @@ class node (object):
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If the node is a binary operator, it will have left and right properties.
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If the node is a unary operator, it will have a child, pointing to the child node and a prop containing
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the string with the props of the operation.
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It can be helpful to know the fields returned by an operation. Providing a dictionary with names and instances
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of relations in the constructor, the node is able to return the list of fields that the result will have.
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'''
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the string with the props of the operation.'''
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kind=None
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def __init__(self,expression=None):
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@ -80,14 +76,12 @@ class node (object):
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'''This function returns a list containing the fields that the resulting relation will have.
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Since it needs to know real instances of relations, it requires a dictionary where keys are
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the names of the relations and the values are the relation objects.'''
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print "Rels========",rels
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if rels==None:
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return
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if self.kind==RELATION:
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return rels[self.name].header.attributes
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elif self.kind==BINARY and self.name in ('-','ᑌ','ᑎ'):
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print "OK"
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return self.left.result_format(rels)
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elif self.name=='π':
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l=[]
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@ -246,16 +240,20 @@ if __name__=="__main__":
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#a= tokenize(u"π a,b (a*b)")
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#a=tokenize("(a-b*c)*(b-c)")
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import relation
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import relation,optimizations
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rels={}
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rels["P1"]= relation.relation("/home/salvo/dev/relational/trunk/samples/people.csv")
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rels["P2"]= relation.relation("/home/salvo/dev/relational/trunk/samples/people.csv")
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rels["R1"]= relation.relation("/home/salvo/dev/relational/trunk/samples/person_room.csv")
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rels["R2"]= relation.relation("/home/salvo/dev/relational/trunk/samples/person_room.csv")
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rels["D1"]= relation.relation("/home/salvo/dev/relational/trunk/samples/dates.csv")
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rels["S1"]= relation.relation("/home/salvo/dev/relational/trunk/samples/skillo.csv")
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print rels
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#n=tree("π indice,qq,name (ρ age➡qq,id➡indice (P1-P2))")
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n=tree("P1 ᐅᐊ R2")
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n=tree("σ id==3 and id==indice and indice==2 and name==5(P1 * S1)")
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print optimizations.selection_and_product(n,rels)
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print n
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print n.result_format(rels)
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