@Override
public Lop constructLops() throws HopsException, LopsException {
// return already created lops
if (getLops() != null) return getLops();
try {
ExecType et = optFindExecType();
Hop input = getInput().get(0);
if (et == ExecType.CP) {
Lop agg1 = null;
if (isTernaryAggregateRewriteApplicable()) {
agg1 = constructLopsTernaryAggregateRewrite(et);
} else if (isUnaryAggregateOuterCPRewriteApplicable()) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
BinaryOp binput = (BinaryOp) getInput().get(0);
agg1 =
new UAggOuterChain(
binput.getInput().get(0).constructLops(),
binput.getInput().get(1).constructLops(),
op,
dir,
HopsOpOp2LopsB.get(binput.getOp()),
DataType.MATRIX,
getValueType(),
ExecType.CP);
PartialAggregate.setDimensionsBasedOnDirection(
agg1, getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), dir);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 =
new UnaryCP(
agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else { // general case
int k = OptimizerUtils.getConstrainedNumThreads(_maxNumThreads);
if (DMLScript.USE_ACCELERATOR
&& (DMLScript.FORCE_ACCELERATOR
|| getMemEstimate() < OptimizerUtils.GPU_MEMORY_BUDGET)
&& (_op == AggOp.SUM)) {
et = ExecType.GPU;
k = 1;
}
agg1 =
new PartialAggregate(
input.constructLops(),
HopsAgg2Lops.get(_op),
HopsDirection2Lops.get(_direction),
getDataType(),
getValueType(),
et,
k);
}
setOutputDimensions(agg1);
setLineNumbers(agg1);
setLops(agg1);
if (getDataType() == DataType.SCALAR) {
agg1.getOutputParameters()
.setDimensions(1, 1, getRowsInBlock(), getColsInBlock(), getNnz());
}
} else if (et == ExecType.MR) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
// unary aggregate operation
Lop transform1 = null;
if (isUnaryAggregateOuterRewriteApplicable()) {
BinaryOp binput = (BinaryOp) getInput().get(0);
transform1 =
new UAggOuterChain(
binput.getInput().get(0).constructLops(),
binput.getInput().get(1).constructLops(),
op,
dir,
HopsOpOp2LopsB.get(binput.getOp()),
DataType.MATRIX,
getValueType(),
ExecType.MR);
PartialAggregate.setDimensionsBasedOnDirection(
transform1,
getDim1(),
getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
dir);
} else // default
{
transform1 =
new PartialAggregate(input.constructLops(), op, dir, DataType.MATRIX, getValueType());
((PartialAggregate) transform1)
.setDimensionsBasedOnDirection(
getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock());
}
setLineNumbers(transform1);
// aggregation if required
Lop aggregate = null;
Group group1 = null;
Aggregate agg1 = null;
if (requiresAggregation(input, _direction) || transform1 instanceof UAggOuterChain) {
group1 =
new Group(transform1, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
group1
.getOutputParameters()
.setDimensions(
getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), getNnz());
setLineNumbers(group1);
agg1 = new Aggregate(group1, HopsAgg2Lops.get(_op), DataType.MATRIX, getValueType(), et);
agg1.getOutputParameters()
.setDimensions(
getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock(), getNnz());
agg1.setupCorrectionLocation(PartialAggregate.getCorrectionLocation(op, dir));
setLineNumbers(agg1);
aggregate = agg1;
} else {
((PartialAggregate) transform1).setDropCorrection();
aggregate = transform1;
}
setLops(aggregate);
// cast if required
if (getDataType() == DataType.SCALAR) {
// Set the dimensions of PartialAggregate LOP based on the
// direction in which aggregation is performed
PartialAggregate.setDimensionsBasedOnDirection(
transform1,
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
dir);
if (group1 != null && agg1 != null) { // if aggregation required
group1
.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
getNnz());
agg1.getOutputParameters()
.setDimensions(1, 1, input.getRowsInBlock(), input.getColsInBlock(), getNnz());
}
UnaryCP unary1 =
new UnaryCP(
aggregate,
HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR),
getDataType(),
getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else if (et == ExecType.SPARK) {
OperationTypes op = HopsAgg2Lops.get(_op);
DirectionTypes dir = HopsDirection2Lops.get(_direction);
// unary aggregate
if (isTernaryAggregateRewriteApplicable()) {
Lop aggregate = constructLopsTernaryAggregateRewrite(et);
setOutputDimensions(aggregate); // 0x0 (scalar)
setLineNumbers(aggregate);
setLops(aggregate);
} else if (isUnaryAggregateOuterSPRewriteApplicable()) {
BinaryOp binput = (BinaryOp) getInput().get(0);
Lop transform1 =
new UAggOuterChain(
binput.getInput().get(0).constructLops(),
binput.getInput().get(1).constructLops(),
op,
dir,
HopsOpOp2LopsB.get(binput.getOp()),
DataType.MATRIX,
getValueType(),
ExecType.SPARK);
PartialAggregate.setDimensionsBasedOnDirection(
transform1,
getDim1(),
getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
dir);
setLineNumbers(transform1);
setLops(transform1);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 =
new UnaryCP(
transform1,
HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR),
getDataType(),
getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
} else // default
{
boolean needAgg = requiresAggregation(input, _direction);
SparkAggType aggtype = getSparkUnaryAggregationType(needAgg);
PartialAggregate aggregate =
new PartialAggregate(
input.constructLops(),
HopsAgg2Lops.get(_op),
HopsDirection2Lops.get(_direction),
DataType.MATRIX,
getValueType(),
aggtype,
et);
aggregate.setDimensionsBasedOnDirection(
getDim1(), getDim2(), input.getRowsInBlock(), input.getColsInBlock());
setLineNumbers(aggregate);
setLops(aggregate);
if (getDataType() == DataType.SCALAR) {
UnaryCP unary1 =
new UnaryCP(
aggregate,
HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR),
getDataType(),
getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
setLops(unary1);
}
}
}
} catch (Exception e) {
throw new HopsException(
this.printErrorLocation() + "In AggUnary Hop, error constructing Lops ", e);
}
// add reblock/checkpoint lops if necessary
constructAndSetLopsDataFlowProperties();
// return created lops
return getLops();
}
private Lop constructLopsIQM() throws HopsException, LopsException {
ExecType et = optFindExecType();
Hop input = getInput().get(0);
if (et == ExecType.MR) {
CombineUnary combine =
CombineUnary.constructCombineLop(input.constructLops(), DataType.MATRIX, getValueType());
combine
.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
SortKeys sort =
SortKeys.constructSortByValueLop(
combine,
SortKeys.OperationTypes.WithoutWeights,
DataType.MATRIX,
ValueType.DOUBLE,
ExecType.MR);
// Sort dimensions are same as the first input
sort.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
Data lit = Data.createLiteralLop(ValueType.DOUBLE, Double.toString(0.25));
lit.setAllPositions(
this.getBeginLine(), this.getBeginColumn(), this.getEndLine(), this.getEndColumn());
PickByCount pick =
new PickByCount(
sort, lit, DataType.MATRIX, getValueType(), PickByCount.OperationTypes.RANGEPICK);
pick.getOutputParameters().setDimensions(-1, -1, getRowsInBlock(), getColsInBlock(), -1);
setLineNumbers(pick);
PartialAggregate pagg =
new PartialAggregate(
pick,
HopsAgg2Lops.get(Hop.AggOp.SUM),
HopsDirection2Lops.get(Hop.Direction.RowCol),
DataType.MATRIX,
getValueType());
setLineNumbers(pagg);
// Set the dimensions of PartialAggregate LOP based on the
// direction in which aggregation is performed
pagg.setDimensionsBasedOnDirection(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock());
Group group1 = new Group(pagg, Group.OperationTypes.Sort, DataType.MATRIX, getValueType());
group1
.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
setLineNumbers(group1);
Aggregate agg1 =
new Aggregate(
group1,
HopsAgg2Lops.get(Hop.AggOp.SUM),
DataType.MATRIX,
getValueType(),
ExecType.MR);
agg1.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
agg1.setupCorrectionLocation(pagg.getCorrectionLocation());
setLineNumbers(agg1);
UnaryCP unary1 =
new UnaryCP(
agg1, HopsOpOp1LopsUS.get(OpOp1.CAST_AS_SCALAR), getDataType(), getValueType());
unary1.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(unary1);
Unary iqm =
new Unary(
sort,
unary1,
Unary.OperationTypes.MR_IQM,
DataType.SCALAR,
ValueType.DOUBLE,
ExecType.CP);
iqm.getOutputParameters().setDimensions(0, 0, 0, 0, -1);
setLineNumbers(iqm);
return iqm;
} else {
SortKeys sort =
SortKeys.constructSortByValueLop(
input.constructLops(),
SortKeys.OperationTypes.WithoutWeights,
DataType.MATRIX,
ValueType.DOUBLE,
et);
sort.getOutputParameters()
.setDimensions(
input.getDim1(),
input.getDim2(),
input.getRowsInBlock(),
input.getColsInBlock(),
input.getNnz());
PickByCount pick =
new PickByCount(
sort, null, getDataType(), getValueType(), PickByCount.OperationTypes.IQM, et, true);
pick.getOutputParameters()
.setDimensions(getDim1(), getDim2(), getRowsInBlock(), getColsInBlock(), getNnz());
setLineNumbers(pick);
return pick;
}
}