Dataflow Filter::getDataflow(){
/** In the currently implementation, we assume that the boolean operator
* between each AttributeComparator is "AND".
*/
Dataflow dataflow=child_->getDataflow();
if(comparator_list_.size()==0)
generateComparatorList(dataflow);
if(dataflow.isHashPartitioned()){
for(unsigned i=0;i<dataflow.property_.partitioner.getNumberOfPartitions();i++){
if(couldHashPruned(i,dataflow.property_.partitioner))//is filtered
{
dataflow.property_.partitioner.getPartition(i)->setFiltered();
}
else{
/*
* should predict the volume of data that passes the filter.
* TODO: a precious prediction is needed based on the statistic of
* the input data, which may be maintained in the catalog module.
*/
const unsigned before_filter_cardinality=dataflow.property_.partitioner.getPartition(i)->getDataCardinality();
const unsigned after_filter_cardinality=before_filter_cardinality*predictSelectivity();
dataflow.property_.partitioner.getPartition(i)->setDataCardinality(after_filter_cardinality);
}
}
}
getcolindex(dataflow);
Schema *input_=getSchema(dataflow.attribute_list_);
for(int i=0;i<qual_.size();i++)
{
InitExprAtLogicalPlan(qual_[i],t_boolean,colindex_,input_);
}
return dataflow;
}
Dataflow Filter::getDataflow(){
/** In the currently implementation, we assume that the boolean operator
* between each AttributeComparator is "AND".
*/
Dataflow dataflow=child_->getDataflow();
generateComparatorList(dataflow);
if(dataflow.isHashPartitioned()){
for(unsigned i=0;i<dataflow.property_.partitioner.getNumberOfPartitions();i++){
if(couldHashPruned(i,dataflow.property_.partitioner))//is filtered
{
dataflow.property_.partitioner.getPartition(i)->setFiltered();
}
else{
/*
* should predict the volume of data that passes the filter.
* TODO: a precious prediction is needed based on the statistic of
* the input data, which may be maintained in the catalog module.
*/
const unsigned before_filter_datasize=dataflow.property_.partitioner.getPartition(i)->getDataSize();
const unsigned after_filter_datasize=before_filter_datasize*predictSelectivity();
dataflow.property_.partitioner.getPartition(i)->setDataSize(after_filter_datasize);
}
}
}
return dataflow;
}
