/// TODO: this method is same as the one for ScanPrel...eventually we should consolidate
/// this and few other methods in a common base class which would be extended
/// by both logical and physical rels.
@Override
public RelOptCost computeSelfCost(final RelOptPlanner planner) {
final ScanStats stats = groupScan.getScanStats(settings);
int columnCount = getRowType().getFieldCount();
double ioCost = 0;
boolean isStarQuery =
Iterables.tryFind(
getRowType().getFieldNames(),
new Predicate<String>() {
@Override
public boolean apply(String input) {
return Preconditions.checkNotNull(input).equals("*");
}
})
.isPresent();
if (isStarQuery) {
columnCount = STAR_COLUMN_COST;
}
// double rowCount = RelMetadataQuery.getRowCount(this);
double rowCount = stats.getRecordCount();
if (rowCount < 1) {
rowCount = 1;
}
if (PrelUtil.getSettings(getCluster()).useDefaultCosting()) {
return planner
.getCostFactory()
.makeCost(rowCount * columnCount, stats.getCpuCost(), stats.getDiskCost());
}
double cpuCost =
rowCount * columnCount; // for now, assume cpu cost is proportional to row count.
// Even though scan is reading from disk, in the currently generated plans all plans will
// need to read the same amount of data, so keeping the disk io cost 0 is ok for now.
// In the future we might consider alternative scans that go against projections or
// different compression schemes etc that affect the amount of data read. Such alternatives
// would affect both cpu and io cost.
DrillCostFactory costFactory = (DrillCostFactory) planner.getCostFactory();
return costFactory.makeCost(rowCount, cpuCost, ioCost, 0);
}
@Override
public RelWriter explainTerms(RelWriter pw) {
return super.explainTerms(pw).item("groupscan", groupScan.getDigest());
}
@Override
public Void visitGroupScan(GroupScan groupScan, Wrapper wrapper) {
Stats stats = wrapper.getStats();
stats.addMaxWidth(groupScan.getMaxParallelizationWidth());
return super.visitGroupScan(groupScan, wrapper);
}
