// checkDistAggregationInfo tests that a flow with multiple local stages and a
// final stage (in accordance with per DistAggregationInfo) gets the same result
// with a naive aggregation flow that has a single non-distributed stage.
//
// Both types of flows are set up and ran against the first numRows of the given
// table. We assume the table's first column is the primary key, with values
// from 1 to numRows. A non-PK column that works with the function is chosen.
func checkDistAggregationInfo(
t *testing.T,
srv serverutils.TestServerInterface,
tableDesc *sqlbase.TableDescriptor,
colIdx int,
numRows int,
fn distsqlrun.AggregatorSpec_Func,
info DistAggregationInfo,
) {
colType := tableDesc.Columns[colIdx].Type
makeTableReader := func(startPK, endPK int, streamID int) distsqlrun.ProcessorSpec {
tr := distsqlrun.TableReaderSpec{
Table: *tableDesc,
OutputColumns: []uint32{uint32(colIdx)},
Spans: make([]distsqlrun.TableReaderSpan, 1),
}
var err error
tr.Spans[0].Span.Key, err = sqlbase.MakePrimaryIndexKey(tableDesc, startPK)
if err != nil {
t.Fatal(err)
}
tr.Spans[0].Span.EndKey, err = sqlbase.MakePrimaryIndexKey(tableDesc, endPK)
if err != nil {
t.Fatal(err)
}
return distsqlrun.ProcessorSpec{
Core: distsqlrun.ProcessorCoreUnion{TableReader: &tr},
Output: []distsqlrun.OutputRouterSpec{{
Type: distsqlrun.OutputRouterSpec_PASS_THROUGH,
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_LOCAL, StreamID: distsqlrun.StreamID(streamID)},
},
}},
}
}
// First run a flow that aggregates all the rows without any local stages.
rowsNonDist := runTestFlow(
t, srv,
makeTableReader(1, numRows+1, 0),
distsqlrun.ProcessorSpec{
Input: []distsqlrun.InputSyncSpec{{
Type: distsqlrun.InputSyncSpec_UNORDERED,
ColumnTypes: []sqlbase.ColumnType{colType},
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_LOCAL, StreamID: 0},
},
}},
Core: distsqlrun.ProcessorCoreUnion{Aggregator: &distsqlrun.AggregatorSpec{
Aggregations: []distsqlrun.AggregatorSpec_Aggregation{{Func: fn, ColIdx: 0}},
}},
Output: []distsqlrun.OutputRouterSpec{{
Type: distsqlrun.OutputRouterSpec_PASS_THROUGH,
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_SYNC_RESPONSE},
},
}},
},
)
// Now run a flow with 4 separate table readers, each with its own local
// stage, all feeding into a single final stage.
numParallel := 4
// The type outputted by the local stage can be different than the input type
// (e.g. DECIMAL instead of INT).
_, intermediaryType, err := distsqlrun.GetAggregateInfo(fn, colType)
if err != nil {
t.Fatal(err)
}
if numParallel < numRows {
numParallel = numRows
}
finalProc := distsqlrun.ProcessorSpec{
Input: []distsqlrun.InputSyncSpec{{
Type: distsqlrun.InputSyncSpec_UNORDERED,
ColumnTypes: []sqlbase.ColumnType{intermediaryType},
}},
Core: distsqlrun.ProcessorCoreUnion{Aggregator: &distsqlrun.AggregatorSpec{
Aggregations: []distsqlrun.AggregatorSpec_Aggregation{{Func: info.FinalStage, ColIdx: 0}},
}},
Output: []distsqlrun.OutputRouterSpec{{
Type: distsqlrun.OutputRouterSpec_PASS_THROUGH,
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_SYNC_RESPONSE},
},
}},
}
var procs []distsqlrun.ProcessorSpec
for i := 0; i < numParallel; i++ {
tr := makeTableReader(1+i*numRows/numParallel, 1+(i+1)*numRows/numParallel, 2*i)
agg := distsqlrun.ProcessorSpec{
Input: []distsqlrun.InputSyncSpec{{
Type: distsqlrun.InputSyncSpec_UNORDERED,
ColumnTypes: []sqlbase.ColumnType{colType},
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_LOCAL, StreamID: distsqlrun.StreamID(2 * i)},
},
}},
Core: distsqlrun.ProcessorCoreUnion{Aggregator: &distsqlrun.AggregatorSpec{
Aggregations: []distsqlrun.AggregatorSpec_Aggregation{{Func: info.LocalStage, ColIdx: 0}},
}},
Output: []distsqlrun.OutputRouterSpec{{
Type: distsqlrun.OutputRouterSpec_PASS_THROUGH,
Streams: []distsqlrun.StreamEndpointSpec{
{Type: distsqlrun.StreamEndpointSpec_LOCAL, StreamID: distsqlrun.StreamID(2*i + 1)},
},
}},
}
procs = append(procs, tr, agg)
finalProc.Input[0].Streams = append(finalProc.Input[0].Streams, distsqlrun.StreamEndpointSpec{
Type: distsqlrun.StreamEndpointSpec_LOCAL,
StreamID: distsqlrun.StreamID(2*i + 1),
})
}
procs = append(procs, finalProc)
rowsDist := runTestFlow(t, srv, procs...)
if len(rowsDist[0]) != len(rowsNonDist[0]) {
t.Errorf("different row lengths (dist: %d non-dist: %d)", len(rowsDist[0]), len(rowsNonDist[0]))
} else {
for i := range rowsDist[0] {
tDist := rowsDist[0][i].Type.String()
tNonDist := rowsNonDist[0][i].Type.String()
if tDist != tNonDist {
t.Errorf("different type for column %d (dist: %s non-dist: %s)", i, tDist, tNonDist)
}
}
}
if rowsDist.String() != rowsNonDist.String() {
t.Errorf("different results\nw/o local stage: %s\nwith local stage: %s", rowsNonDist, rowsDist)
}
}
// Test that distributing agg functions according to DistAggregationTable
// yields correct results. We're going to run each aggregation as either the
// two-stage process described by the DistAggregationTable or as a single global
// process, and verify that the results are the same.
func TestDistAggregationTable(t *testing.T) {
defer leaktest.AfterTest(t)()
const numRows = 100
tc := serverutils.StartTestCluster(t, 1, base.TestClusterArgs{})
defer tc.Stopper().Stop()
// Create a table with a few columns:
// - random integer values from 0 to numRows
// - random integer values (with some NULLs)
// - random bool value (mostly false)
// - random bool value (mostly true)
// - random decimals
// - random decimals (with some NULLs)
rng, _ := randutil.NewPseudoRand()
sqlutils.CreateTable(
t, tc.ServerConn(0), "t",
"k INT PRIMARY KEY, int1 INT, int2 INT, bool1 BOOL, bool2 BOOL, dec1 DECIMAL, dec2 DECIMAL",
numRows,
func(row int) []parser.Datum {
return []parser.Datum{
parser.NewDInt(parser.DInt(row)),
parser.NewDInt(parser.DInt(rng.Intn(numRows))),
sqlbase.RandDatum(rng, sqlbase.ColumnType{Kind: sqlbase.ColumnType_INT}, true),
parser.MakeDBool(parser.DBool(rng.Intn(10) == 0)),
parser.MakeDBool(parser.DBool(rng.Intn(10) != 0)),
sqlbase.RandDatum(rng, sqlbase.ColumnType{Kind: sqlbase.ColumnType_DECIMAL}, false),
sqlbase.RandDatum(rng, sqlbase.ColumnType{Kind: sqlbase.ColumnType_DECIMAL}, true),
}
},
)
kvDB := tc.Server(0).KVClient().(*client.DB)
desc := sqlbase.GetTableDescriptor(kvDB, "test", "t")
for fn, info := range DistAggregationTable {
if info.LocalStage == distsqlrun.AggregatorSpec_IDENT &&
info.FinalStage == distsqlrun.AggregatorSpec_IDENT {
// IDENT only works as expected if all rows have the same value on the
// relevant column; skip testing this trivial case.
continue
}
// We're going to test each aggregation function on every column that can be
// used as input for it.
foundCol := false
for colIdx := 1; colIdx < len(desc.Columns); colIdx++ {
// See if this column works with this function.
_, _, err := distsqlrun.GetAggregateInfo(fn, desc.Columns[colIdx].Type)
if err != nil {
continue
}
foundCol = true
for _, numRows := range []int{5, numRows / 10, numRows / 2, numRows} {
name := fmt.Sprintf("%s/%s/%d", fn, desc.Columns[colIdx].Name, numRows)
t.Run(name, func(t *testing.T) {
checkDistAggregationInfo(t, tc.Server(0), desc, colIdx, numRows, fn, info)
})
}
}
if !foundCol {
t.Errorf("aggregation function %s was not tested (no suitable column)", fn)
}
}
}
