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exec: Add support for vectorized engine to use builtin functions.
Added support for the vectorized engine to use all builtin functions that are supported by distsql. The mechanism for doing this is relatively ineffecient however -- it converts each row in a batch back into a datum row, and uses the expression evaluator on this row to perform the builtin function. The goal is to in the future extend this work to create faster(vectorized) implementations of different builtin functions, and switch to those instead of the default builtin here for improved performance. This includes refactoring the materializer's batch to row code into a separate, reusable function. Release note: None
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,173 @@ | ||
| // Copyright 2019 The Cockroach Authors. | ||
| // | ||
| // Use of this software is governed by the Business Source License | ||
| // included in the file licenses/BSL.txt. | ||
| // | ||
| // As of the Change Date specified in that file, in accordance with | ||
| // the Business Source License, use of this software will be governed | ||
| // by the Apache License, Version 2.0, included in the file | ||
| // licenses/APL.txt. | ||
|
|
||
| package exec | ||
|
|
||
| import ( | ||
| "context" | ||
| "fmt" | ||
|
|
||
| "github.com/cockroachdb/apd" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/exec/coldata" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/exec/types" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/exec/types/conv" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/sem/tree" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/sqlbase" | ||
| semtypes "github.com/cockroachdb/cockroach/pkg/sql/types" | ||
| ) | ||
|
|
||
| type indexResolver struct { | ||
| row tree.Datums | ||
| colTypes []semtypes.T | ||
| } | ||
|
|
||
| var _ tree.IndexedVarContainer = &indexResolver{} | ||
|
|
||
| func (i *indexResolver) IndexedVarEval(idx int, ctx *tree.EvalContext) (tree.Datum, error) { | ||
| return i.row[idx].Eval(ctx) | ||
| } | ||
|
|
||
| func (i *indexResolver) IndexedVarResolvedType(idx int) *semtypes.T { | ||
| return &i.colTypes[idx] | ||
| } | ||
|
|
||
| func (i *indexResolver) IndexedVarNodeFormatter(idx int) tree.NodeFormatter { | ||
| n := tree.Name(fmt.Sprintf("$%d", idx)) | ||
| return &n | ||
| } | ||
|
|
||
| type defaultBuiltinOperator struct { | ||
| input Operator | ||
|
|
||
| evalCtx *tree.EvalContext | ||
| funcExpr *tree.FuncExpr | ||
| outputIdx int | ||
| colTypes []semtypes.T | ||
|
|
||
| da sqlbase.DatumAlloc | ||
| row tree.Datums | ||
|
|
||
| resolved *indexResolver | ||
| } | ||
|
|
||
| func (d *defaultBuiltinOperator) Init() { | ||
| d.input.Init() | ||
| } | ||
|
|
||
| func (d *defaultBuiltinOperator) Next(ctx context.Context) coldata.Batch { | ||
| batch := d.input.Next(ctx) | ||
| n := batch.Length() | ||
|
|
||
| if n == 0 { | ||
| return batch | ||
| } | ||
|
|
||
| outputType := d.funcExpr.ResolvedType() | ||
| outputPhysType := conv.FromColumnType(outputType) | ||
|
|
||
| if d.outputIdx == batch.Width() { | ||
| batch.AppendCol(outputPhysType) | ||
| } | ||
|
|
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| converter := conv.GetDatumToPhysicalFn(outputType) | ||
|
|
||
| writer := func(batch coldata.Batch, datum tree.Datum, i int) { | ||
| if datum == tree.DNull { | ||
| batch.ColVec(d.outputIdx).Nulls().SetNull(uint16(i)) | ||
| return | ||
| } | ||
| converted, _ := converter(datum) | ||
| switch outputPhysType { | ||
| case types.Bool: | ||
| batch.ColVec(d.outputIdx).Bool()[i] = converted.(bool) | ||
| case types.Bytes: | ||
| batch.ColVec(d.outputIdx).Bytes()[i] = converted.([]byte) | ||
| case types.Int8: | ||
| batch.ColVec(d.outputIdx).Int8()[i] = converted.(int8) | ||
| case types.Int16: | ||
| batch.ColVec(d.outputIdx).Int16()[i] = converted.(int16) | ||
| case types.Int32: | ||
| batch.ColVec(d.outputIdx).Int32()[i] = converted.(int32) | ||
| case types.Int64: | ||
| batch.ColVec(d.outputIdx).Int64()[i] = converted.(int64) | ||
| case types.Float32: | ||
| batch.ColVec(d.outputIdx).Float32()[i] = converted.(float32) | ||
| case types.Float64: | ||
| batch.ColVec(d.outputIdx).Float64()[i] = converted.(float64) | ||
| case types.Decimal: | ||
| batch.ColVec(d.outputIdx).Decimal()[i] = converted.(apd.Decimal) | ||
| default: | ||
| panic(fmt.Sprintf("unhandled type %s", outputPhysType)) | ||
| } | ||
| } | ||
|
|
||
| if sel := batch.Selection(); sel != nil { | ||
| sel = sel[:n] | ||
| for _, i := range sel { | ||
| for j := 0; j < batch.Width(); j++ { | ||
| col := batch.ColVec(j) | ||
| if col.MaybeHasNulls() && col.Nulls().NullAt(i) { | ||
| d.row[j] = tree.DNull | ||
| } else { | ||
| d.row[j] = PhysicalTypeColElemToDatum(col, i, d.da, d.colTypes[j]) | ||
| } | ||
| } | ||
|
|
||
| d.resolved.row = d.row | ||
| d.evalCtx.PushIVarContainer(d.resolved) | ||
| // Because the typechecker has passed, we won't get an error here. | ||
| res, _ := d.funcExpr.Eval(d.evalCtx) | ||
| d.evalCtx.PopIVarContainer() | ||
| writer(batch, res, int(i)) | ||
| } | ||
| } else { | ||
| for i := uint16(0); i < n; i++ { | ||
| for j := 0; j < batch.Width(); j++ { | ||
| col := batch.ColVec(j) | ||
| if col.MaybeHasNulls() && col.Nulls().NullAt(i) { | ||
| d.row[j] = tree.DNull | ||
| } else { | ||
| d.row[j] = PhysicalTypeColElemToDatum(col, i, d.da, d.colTypes[j]) | ||
| } | ||
| } | ||
|
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||
| d.evalCtx.PushIVarContainer(&indexResolver{row: d.row, colTypes: d.colTypes}) | ||
| // Because the typechecker has passed, we won't get an error here. | ||
| res, _ := d.funcExpr.Eval(d.evalCtx) | ||
| d.evalCtx.PopIVarContainer() | ||
| writer(batch, res, int(i)) | ||
| } | ||
| } | ||
| return batch | ||
| } | ||
|
|
||
| // NewBuiltinFunctionOperator returns an operator that applies builtin functions. | ||
| func NewBuiltinFunctionOperator( | ||
| tctx *tree.EvalContext, | ||
| columnTypes []semtypes.T, | ||
| input Operator, | ||
| funcExpr *tree.FuncExpr, | ||
| outputIdx int, | ||
| ) (Operator, error) { | ||
|
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||
| // For now, return the default builtin operator. Future work can specialize | ||
| // out the operators to efficient implementations of specific builtins. | ||
| op := &defaultBuiltinOperator{ | ||
| input: input, | ||
| evalCtx: tctx, | ||
| funcExpr: funcExpr, | ||
| outputIdx: outputIdx, | ||
| colTypes: columnTypes, | ||
| row: make(tree.Datums, len(columnTypes)), | ||
| resolved: &indexResolver{colTypes: columnTypes}, | ||
| } | ||
|
|
||
| return op, nil | ||
| } |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,101 @@ | ||
| // Copyright 2019 The Cockroach Authors. | ||
| // | ||
| // Use of this software is governed by the Business Source License | ||
| // included in the file licenses/BSL.txt. | ||
| // | ||
| // As of the Change Date specified in that file, in accordance with | ||
| // the Business Source License, use of this software will be governed | ||
| // by the Apache License, Version 2.0, included in the file | ||
| // licenses/APL.txt. | ||
|
|
||
| package exec | ||
|
|
||
| import ( | ||
| "fmt" | ||
| "testing" | ||
|
|
||
| "github.com/cockroachdb/cockroach/pkg/settings/cluster" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/parser" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/sem/builtins" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/sem/tree" | ||
| "github.com/cockroachdb/cockroach/pkg/sql/types" | ||
| ) | ||
|
|
||
| // Typing context to for the typechecker. | ||
| type mockTypeContext struct { | ||
| ty []types.T | ||
| } | ||
|
|
||
| func (p *mockTypeContext) IndexedVarEval(idx int, ctx *tree.EvalContext) (tree.Datum, error) { | ||
| return tree.DNull.Eval(ctx) | ||
| } | ||
|
|
||
| func (p *mockTypeContext) IndexedVarResolvedType(idx int) *types.T { | ||
| return &p.ty[idx] | ||
| } | ||
|
|
||
| func (p *mockTypeContext) IndexedVarNodeFormatter(idx int) tree.NodeFormatter { | ||
| n := tree.Name(fmt.Sprintf("$%d", idx)) | ||
| return &n | ||
| } | ||
|
|
||
| func TestBasicBuiltinFunctions(t *testing.T) { | ||
| // Trick to get the init() for the builtins package to run. | ||
| _ = builtins.AllBuiltinNames | ||
|
|
||
| testCases := []struct { | ||
| desc string | ||
| expr string | ||
| inputTuples tuples | ||
| inputTypes []types.T | ||
| outputTypes []types.T | ||
| outputTuples tuples | ||
| }{ | ||
| { | ||
| desc: "Substring test", | ||
| expr: "substring(@1, 1, 2)", | ||
| inputTuples: tuples{{"Hello"}, {"There"}}, | ||
| inputTypes: []types.T{*types.String}, | ||
| outputTuples: tuples{{"He"}, {"Th"}}, | ||
| outputTypes: []types.T{*types.String, *types.String}, | ||
| }, | ||
| { | ||
| desc: "Absolute value test", | ||
| expr: "abs(@1)", | ||
| inputTuples: tuples{{1}, {-1}}, | ||
| inputTypes: []types.T{*types.Int}, | ||
| outputTuples: tuples{{1}, {1}}, | ||
| outputTypes: []types.T{*types.Int, *types.Int}, | ||
| }, | ||
| { | ||
| desc: "String length test", | ||
| expr: "length(@1)", | ||
| inputTuples: tuples{{"Hello"}, {"The"}}, | ||
| inputTypes: []types.T{*types.String}, | ||
| outputTuples: tuples{{5}, {3}}, | ||
| outputTypes: []types.T{*types.String, *types.Int}, | ||
| }, | ||
| } | ||
|
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| tctx := tree.NewTestingEvalContext(cluster.MakeTestingClusterSettings()) | ||
|
|
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| for _, tc := range testCases { | ||
| t.Run(tc.desc, func(t *testing.T) { | ||
| runTests(t, []tuples{tc.inputTuples}, tc.outputTuples, orderedVerifier, []int{1}, | ||
| func(input []Operator) (Operator, error) { | ||
| expr, err := parser.ParseExpr(tc.expr) | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
|
|
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| p := &mockTypeContext{ty: tc.inputTypes} | ||
| typedExpr, err := tree.TypeCheck(expr, &tree.SemaContext{IVarContainer: p}, types.Any) | ||
| if err != nil { | ||
| t.Fatal(err) | ||
| } | ||
|
|
||
| return NewBuiltinFunctionOperator(tctx, tc.outputTypes, input[0], typedExpr.(*tree.FuncExpr), 1) | ||
| }) | ||
| }) | ||
| } | ||
| } |
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