// filters walks the where clause of a select statement and returns a map with all series ids
// matching the where clause and any filter expression that should be applied to each
func (m *Measurement) filters(stmt *influxql.SelectStatement) (map[uint64]influxql.Expr, error) {
if stmt.Condition == nil || stmt.OnlyTimeDimensions() {
seriesIdsToExpr := make(map[uint64]influxql.Expr)
for _, id := range m.seriesIDs {
seriesIdsToExpr[id] = nil
}
return seriesIdsToExpr, nil
}
ids, seriesIdsToExpr, err := m.walkWhereForSeriesIds(stmt.Condition)
if err != nil {
return nil, err
}
// Ensure every id is in the map and replace literal true expressions with
// nil so the engine doesn't waste time evaluating them.
for _, id := range ids {
if expr, ok := seriesIdsToExpr[id]; !ok {
seriesIdsToExpr[id] = nil
} else if b, ok := expr.(*influxql.BooleanLiteral); ok && b.Val {
seriesIdsToExpr[id] = nil
}
}
return seriesIdsToExpr, nil
}
// Plan creates an execution plan for the given SelectStatement and returns an Executor.
func (q *QueryExecutor) plan(stmt *influxql.SelectStatement, chunkSize int) (Executor, error) {
shards := map[uint64]meta.ShardInfo{} // Shards requiring mappers.
// Replace instances of "now()" with the current time, and check the resultant times.
stmt.Condition = influxql.Reduce(stmt.Condition, &influxql.NowValuer{Now: time.Now().UTC()})
tmin, tmax := influxql.TimeRange(stmt.Condition)
if tmax.IsZero() {
tmax = time.Now()
}
if tmin.IsZero() {
tmin = time.Unix(0, 0)
}
for _, src := range stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return nil, fmt.Errorf("invalid source type: %#v", src)
}
// Build the set of target shards. Using shard IDs as keys ensures each shard ID
// occurs only once.
shardGroups, err := q.MetaStore.ShardGroupsByTimeRange(mm.Database, mm.RetentionPolicy, tmin, tmax)
if err != nil {
return nil, err
}
for _, g := range shardGroups {
for _, sh := range g.Shards {
shards[sh.ID] = sh
}
}
}
// Build the Mappers, one per shard.
mappers := []Mapper{}
for _, sh := range shards {
m, err := q.ShardMapper.CreateMapper(sh, stmt.String(), chunkSize)
if err != nil {
return nil, err
}
if m == nil {
// No data for this shard, skip it.
continue
}
mappers = append(mappers, m)
}
var executor Executor
if len(mappers) > 0 {
// All Mapper are of same type, so check first to determine correct Executor type.
if _, ok := mappers[0].(*RawMapper); ok {
executor = NewRawExecutor(stmt, mappers, chunkSize)
} else {
executor = NewAggregateExecutor(stmt, mappers)
}
} else {
// With no mappers, the Executor type doesn't matter.
executor = NewRawExecutor(stmt, nil, chunkSize)
}
return executor, nil
}
// WhereFields returns a list of non-"time" fields in the WHERE section of stmt.
func (m *Measurement) WhereFields(stmt *influxql.SelectStatement) []string {
set := newStringSet()
for _, name := range stmt.NamesInWhere() {
if name != "time" && m.HasField(name) {
set.add(name)
}
}
return set.list()
}
// SelectTags returns a list of non-field tags in the SELECT section of stmt.
func (m *Measurement) SelectTags(stmt *influxql.SelectStatement) []string {
set := newStringSet()
for _, name := range stmt.NamesInSelect() {
if !m.HasField(name) && m.HasTagKey(name) {
set.add(name)
}
}
return set.list()
}
// SelectFields returns a list of fields in the SELECT section of stmt.
func (m *Measurement) SelectFields(stmt *influxql.SelectStatement) []string {
set := newStringSet()
for _, name := range stmt.NamesInSelect() {
if m.HasField(name) {
set.add(name)
continue
}
}
return set.list()
}
// NewLocalMapper returns a mapper for the given shard, which will return data for the SELECT statement.
func NewLocalMapper(shard *Shard, stmt *influxql.SelectStatement, chunkSize int) *LocalMapper {
m := &LocalMapper{
shard: shard,
stmt: stmt,
chunkSize: chunkSize,
cursors: make([]*tagSetCursor, 0),
}
m.rawMode = (stmt.IsRawQuery && !stmt.HasDistinct()) || stmt.IsSimpleDerivative()
return m
}
// expandWildcards returns a new SelectStatement with wildcards in the fields
// and/or GROUP BY exapnded with actual field names.
func (q *QueryExecutor) expandWildcards(stmt *influxql.SelectStatement) (*influxql.SelectStatement, error) {
// If there are no wildcards in the statement, return it as-is.
if !stmt.HasWildcard() {
return stmt, nil
}
// Use sets to avoid duplicate field names.
fieldSet := map[string]struct{}{}
dimensionSet := map[string]struct{}{}
var fields influxql.Fields
var dimensions influxql.Dimensions
// Iterate measurements in the FROM clause getting the fields & dimensions for each.
for _, src := range stmt.Sources {
if m, ok := src.(*influxql.Measurement); ok {
// Lookup the database. The database may not exist if no data for this database
// was ever written to the shard.
db := q.store.DatabaseIndex(m.Database)
if db == nil {
return stmt, nil
}
// Lookup the measurement in the database.
mm := db.measurements[m.Name]
if mm == nil {
return nil, ErrMeasurementNotFound(m.String())
}
// Get the fields for this measurement.
for _, name := range mm.FieldNames() {
if _, ok := fieldSet[name]; ok {
continue
}
fieldSet[name] = struct{}{}
fields = append(fields, &influxql.Field{Expr: &influxql.VarRef{Val: name}})
}
// Get the dimensions for this measurement.
for _, t := range mm.TagKeys() {
if _, ok := dimensionSet[t]; ok {
continue
}
dimensionSet[t] = struct{}{}
dimensions = append(dimensions, &influxql.Dimension{Expr: &influxql.VarRef{Val: t}})
}
}
}
// Return a new SelectStatement with the wild cards rewritten.
return stmt.RewriteWildcards(fields, dimensions), nil
}
func (s *Shard) ValidateAggregateFieldsInStatement(measurementName string, stmt *influxql.SelectStatement) error {
s.mu.RLock()
defer s.mu.RUnlock()
validateType := func(aname, fname string, t influxql.DataType) error {
if t != influxql.Float && t != influxql.Integer {
return fmt.Errorf("aggregate '%s' requires numerical field values. Field '%s' is of type %s",
aname, fname, t)
}
return nil
}
m := s.measurementFields[measurementName]
if m == nil {
return fmt.Errorf("measurement not found: %s", measurementName)
}
// If a numerical aggregate is requested, ensure it is only performed on numeric data or on a
// nested aggregate on numeric data.
for _, a := range stmt.FunctionCalls() {
// Check for fields like `derivative(mean(value), 1d)`
var nested *influxql.Call = a
if fn, ok := nested.Args[0].(*influxql.Call); ok {
nested = fn
}
switch lit := nested.Args[0].(type) {
case *influxql.VarRef:
if influxql.IsNumeric(nested) {
f := m.Fields[lit.Val]
if err := validateType(a.Name, f.Name, f.Type); err != nil {
return err
}
}
case *influxql.Distinct:
if nested.Name != "count" {
return fmt.Errorf("aggregate call didn't contain a field %s", a.String())
}
if influxql.IsNumeric(nested) {
f := m.Fields[lit.Val]
if err := validateType(a.Name, f.Name, f.Type); err != nil {
return err
}
}
default:
return fmt.Errorf("aggregate call didn't contain a field %s", a.String())
}
}
return nil
}
// createTagSetsAndFields returns the tagsets and various fields given a measurement and
// SELECT statement. It also ensures that the fields and tags exist.
func createTagSetsAndFields(m *Measurement, stmt *influxql.SelectStatement) (*tagSetsAndFields, error) {
_, tagKeys, err := stmt.Dimensions.Normalize()
if err != nil {
return nil, err
}
sfs := newStringSet()
sts := newStringSet()
wfs := newStringSet()
// Validate the fields and tags asked for exist and keep track of which are in the select vs the where
for _, n := range stmt.NamesInSelect() {
if m.HasField(n) {
sfs.add(n)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in select clause: %s", n)
}
sts.add(n)
tagKeys = append(tagKeys, n)
}
for _, n := range stmt.NamesInWhere() {
if n == "time" {
continue
}
if m.HasField(n) {
wfs.add(n)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in where clause: %s", n)
}
}
// Get the sorted unique tag sets for this statement.
tagSets, err := m.TagSets(stmt, tagKeys)
if err != nil {
return nil, err
}
return &tagSetsAndFields{
tagSets: tagSets,
selectFields: sfs.list(),
selectTags: sts.list(),
whereFields: wfs.list(),
}, nil
}
// rewriteSelectStatement performs any necessary query re-writing.
func (lm *SelectMapper) rewriteSelectStatement(stmt *influxql.SelectStatement) (*influxql.SelectStatement, error) {
var err error
// Expand regex expressions in the FROM clause.
sources, err := expandSources(stmt.Sources, lm.shard.index)
if err != nil {
return nil, err
}
stmt.Sources = sources
// Expand wildcards in the fields or GROUP BY.
stmt, err = lm.expandWildcards(stmt)
if err != nil {
return nil, err
}
stmt.RewriteDistinct()
return stmt, nil
}
// DimensionTagSets returns list of tag sets from the GROUP BY section of stmt.
func (m *Measurement) DimensionTagSets(stmt *influxql.SelectStatement) ([]*influxql.TagSet, error) {
_, tagKeys := stmt.Dimensions.Normalize()
for _, n := range stmt.NamesInDimension() {
if m.HasTagKey(n) {
tagKeys = append(tagKeys, n)
}
}
// Get the sorted unique tag sets for this statement.
tagSets, err := m.TagSets(stmt, tagKeys)
if err != nil {
return nil, err
}
return tagSets, nil
}
// RewriteSelectStatement performs any necessary query re-writing.
func (db *DatabaseIndex) RewriteSelectStatement(stmt *influxql.SelectStatement) (*influxql.SelectStatement, error) {
// Expand regex expressions in the FROM clause.
sources, err := db.ExpandSources(stmt.Sources)
if err != nil {
return nil, err
}
stmt.Sources = sources
// Expand wildcards in the fields or GROUP BY.
stmt, err = db.ExpandWildcards(stmt)
if err != nil {
return nil, err
}
stmt.RewriteDistinct()
return stmt, nil
}
// filters walks the where clause of a select statement and returns a map with all series ids
// matching the where clause and any filter expression that should be applied to each
func (m *Measurement) filters(stmt *influxql.SelectStatement) map[uint32]influxql.Expr {
seriesIdsToExpr := make(map[uint32]influxql.Expr)
if stmt.Condition == nil || stmt.OnlyTimeDimensions() {
for _, id := range m.seriesIDs {
seriesIdsToExpr[id] = nil
}
return seriesIdsToExpr
}
ids, _, _ := m.walkWhereForSeriesIds(stmt.Condition, seriesIdsToExpr)
// ensure every id is in the map
for _, id := range ids {
if _, ok := seriesIdsToExpr[id]; !ok {
seriesIdsToExpr[id] = nil
}
}
return seriesIdsToExpr
}
// expandWildcards returns a new SelectStatement with wildcards in the fields
// and/or GROUP BY expanded with actual field names.
func (lm *LocalMapper) expandWildcards(stmt *influxql.SelectStatement) (*influxql.SelectStatement, error) {
// If there are no wildcards in the statement, return it as-is.
if !stmt.HasWildcard() {
return stmt, nil
}
// Use sets to avoid duplicate field names.
fieldSet := map[string]struct{}{}
dimensionSet := map[string]struct{}{}
var fields influxql.Fields
var dimensions influxql.Dimensions
// Iterate measurements in the FROM clause getting the fields & dimensions for each.
for _, src := range stmt.Sources {
if m, ok := src.(*influxql.Measurement); ok {
// Lookup the measurement in the database.
mm := lm.shard.index.Measurement(m.Name)
if mm == nil {
// This shard have never received data for the measurement. No Mapper
// required.
return stmt, nil
}
// Get the fields for this measurement.
for _, name := range mm.FieldNames() {
if _, ok := fieldSet[name]; ok {
continue
}
fieldSet[name] = struct{}{}
fields = append(fields, &influxql.Field{Expr: &influxql.VarRef{Val: name}})
}
// Get the dimensions for this measurement.
for _, t := range mm.TagKeys() {
if _, ok := dimensionSet[t]; ok {
continue
}
dimensionSet[t] = struct{}{}
dimensions = append(dimensions, &influxql.Dimension{Expr: &influxql.VarRef{Val: t}})
}
}
}
// Return a new SelectStatement with the wild cards rewritten.
return stmt.RewriteWildcards(fields, dimensions), nil
}
// Plan creates an execution plan for the given SelectStatement and returns an Executor.
func (q *QueryExecutor) PlanSelect(stmt *influxql.SelectStatement, chunkSize int) (Executor, error) {
shards := map[uint64]meta.ShardInfo{} // Shards requiring mappers.
// It is important to "stamp" this time so that everywhere we evaluate `now()` in the statement is EXACTLY the same `now`
now := time.Now().UTC()
// Replace instances of "now()" with the current time, and check the resultant times.
stmt.Condition = influxql.Reduce(stmt.Condition, &influxql.NowValuer{Now: now})
tmin, tmax := influxql.TimeRange(stmt.Condition)
if tmax.IsZero() {
tmax = now
}
if tmin.IsZero() {
tmin = time.Unix(0, 0)
}
for _, src := range stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return nil, fmt.Errorf("invalid source type: %#v", src)
}
// Build the set of target shards. Using shard IDs as keys ensures each shard ID
// occurs only once.
shardGroups, err := q.MetaStore.ShardGroupsByTimeRange(mm.Database, mm.RetentionPolicy, tmin, tmax)
if err != nil {
return nil, err
}
for _, g := range shardGroups {
for _, sh := range g.Shards {
shards[sh.ID] = sh
}
}
}
// Build the Mappers, one per shard.
mappers := []Mapper{}
for _, sh := range shards {
m, err := q.ShardMapper.CreateMapper(sh, stmt, chunkSize)
if err != nil {
return nil, err
}
if m == nil {
// No data for this shard, skip it.
continue
}
mappers = append(mappers, m)
}
executor := NewSelectExecutor(stmt, mappers, chunkSize)
return executor, nil
}
// rewriteSelectStatement performs any necessary query re-writing.
func (q *QueryExecutor) rewriteSelectStatement(stmt *influxql.SelectStatement) (*influxql.SelectStatement, error) {
var err error
// Expand regex expressions in the FROM clause.
sources, err := q.expandSources(stmt.Sources)
if err != nil {
return nil, err
}
stmt.Sources = sources
// Expand wildcards in the fields or GROUP BY.
if stmt.HasWildcard() {
stmt, err = q.expandWildcards(stmt)
if err != nil {
return nil, err
}
}
stmt.RewriteDistinct()
return stmt, nil
}
// derivativeInterval returns the time interval for the one (and only) derivative func
func derivativeInterval(stmt *influxql.SelectStatement) (time.Duration, error) {
if len(stmt.FunctionCalls()[0].Args) == 2 {
return stmt.FunctionCalls()[0].Args[1].(*influxql.DurationLiteral).Val, nil
}
interval, err := stmt.GroupByInterval()
if err != nil {
return 0, err
}
if interval > 0 {
return interval, nil
}
return time.Second, nil
}
// CreateMappers will create a set of mappers that need to be run to execute the map phase of a MapReduceJob.
func (tx *tx) CreateMapReduceJobs(stmt *influxql.SelectStatement, tagKeys []string) ([]*influxql.MapReduceJob, error) {
jobs := []*influxql.MapReduceJob{}
for _, src := range stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return nil, fmt.Errorf("invalid source type: %#v", src)
}
// get the index and the retention policy
rp, err := tx.meta.RetentionPolicy(mm.Database, mm.RetentionPolicy)
if err != nil {
return nil, err
}
m := tx.store.Measurement(mm.Database, mm.Name)
if m == nil {
return nil, ErrMeasurementNotFound(influxql.QuoteIdent([]string{mm.Database, "", mm.Name}...))
}
tx.measurement = m
// Validate the fields and tags asked for exist and keep track of which are in the select vs the where
var selectFields []string
var whereFields []string
var selectTags []string
for _, n := range stmt.NamesInSelect() {
if m.HasField(n) {
selectFields = append(selectFields, n)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in select clause: %s", n)
}
selectTags = append(selectTags, n)
tagKeys = append(tagKeys, n)
}
for _, n := range stmt.NamesInWhere() {
if n == "time" {
continue
}
if m.HasField(n) {
whereFields = append(whereFields, n)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in where clause: %s", n)
}
}
if len(selectFields) == 0 && len(stmt.FunctionCalls()) == 0 {
return nil, fmt.Errorf("select statement must include at least one field or function call")
}
// Validate that group by is not a field
for _, d := range stmt.Dimensions {
switch e := d.Expr.(type) {
case *influxql.VarRef:
if !m.HasTagKey(e.Val) {
return nil, fmt.Errorf("can not use field in group by clause: %s", e.Val)
}
}
}
// Grab time range from statement.
tmin, tmax := influxql.TimeRange(stmt.Condition)
if tmax.IsZero() {
tmax = tx.now
}
if tmin.IsZero() {
tmin = time.Unix(0, 0)
}
// Find shard groups within time range.
var shardGroups []*meta.ShardGroupInfo
for _, group := range rp.ShardGroups {
if group.Overlaps(tmin, tmax) {
g := group
shardGroups = append(shardGroups, &g)
}
}
if len(shardGroups) == 0 {
return nil, nil
}
// get the group by interval, if there is one
var interval int64
if d, err := stmt.GroupByInterval(); err != nil {
return nil, err
} else {
interval = d.Nanoseconds()
}
// get the sorted unique tag sets for this query.
tagSets, err := m.TagSets(stmt, tagKeys)
if err != nil {
return nil, err
}
for _, t := range tagSets {
// make a job for each tagset
job := &influxql.MapReduceJob{
MeasurementName: m.Name,
TagSet: t,
TMin: tmin.UnixNano(),
TMax: tmax.UnixNano(),
}
// make a mapper for each shard that must be hit. We may need to hit multiple shards within a shard group
var mappers []influxql.Mapper
// create mappers for each shard we need to hit
for _, sg := range shardGroups {
// TODO: implement distributed queries
if len(sg.Shards) != 1 {
return nil, fmt.Errorf("distributed queries aren't supported yet. You have a replication policy with RF < # of servers in cluster")
}
shard := tx.store.Shard(sg.Shards[0].ID)
if shard == nil {
// the store returned nil which means we haven't written any data into this shard yet, so ignore it
continue
}
// get the codec for this measuremnt. If this is nil it just means this measurement was
// never written into this shard, so we can skip it and continue.
codec := shard.FieldCodec(m.Name)
if codec == nil {
continue
}
var mapper influxql.Mapper
mapper = &LocalMapper{
seriesKeys: t.SeriesKeys,
shard: shard,
db: shard.DB(),
job: job,
decoder: codec,
filters: t.Filters,
whereFields: whereFields,
selectFields: selectFields,
selectTags: selectTags,
tmin: tmin.UnixNano(),
tmax: tmax.UnixNano(),
interval: interval,
// multiple mappers may need to be merged together to get the results
// for a raw query. So each mapper will have to read at least the
// limit plus the offset in data points to ensure we've hit our mark
limit: uint64(stmt.Limit) + uint64(stmt.Offset),
}
mappers = append(mappers, mapper)
}
job.Mappers = mappers
jobs = append(jobs, job)
}
}
// always return them in sorted order so the results from running the jobs are returned in a deterministic order
sort.Sort(influxql.MapReduceJobs(jobs))
return jobs, nil
}
// Plan creates an execution plan for the given SelectStatement and returns an Executor.
func (q *QueryExecutor) PlanSelect(stmt *influxql.SelectStatement, chunkSize int) (Executor, error) {
var shardIDs []uint64
shards := map[uint64]meta.ShardInfo{} // Shards requiring mappers.
// It is important to "stamp" this time so that everywhere we evaluate `now()` in the statement is EXACTLY the same `now`
now := time.Now().UTC()
// Replace instances of "now()" with the current time, and check the resultant times.
stmt.Condition = influxql.Reduce(stmt.Condition, &influxql.NowValuer{Now: now})
tmin, tmax := influxql.TimeRange(stmt.Condition)
if tmax.IsZero() {
tmax = now
}
if tmin.IsZero() {
tmin = time.Unix(0, 0)
}
for _, src := range stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return nil, fmt.Errorf("invalid source type: %#v", src)
}
// Build the set of target shards. Using shard IDs as keys ensures each shard ID
// occurs only once.
shardGroups, err := q.MetaClient.ShardGroupsByTimeRange(mm.Database, mm.RetentionPolicy, tmin, tmax)
if err != nil {
return nil, err
}
for _, g := range shardGroups {
for _, sh := range g.Shards {
if _, ok := shards[sh.ID]; !ok {
shards[sh.ID] = sh
shardIDs = append(shardIDs, sh.ID)
}
}
}
}
// Sort shard IDs to make testing deterministic.
sort.Sort(uint64Slice(shardIDs))
// Build the Mappers, one per shard.
mappers := []Mapper{}
for _, shardID := range shardIDs {
sh := shards[shardID]
m, err := q.ShardMapper.CreateMapper(sh, stmt, chunkSize)
if err != nil {
return nil, err
}
if m == nil {
// No data for this shard, skip it.
continue
}
mappers = append(mappers, m)
}
// Certain operations on the SELECT statement can be performed by the AggregateExecutor without
// assistance from the Mappers. This allows the AggregateExecutor to prepare aggregation functions
// and mathematical functions.
stmt.RewriteDistinct()
if (stmt.IsRawQuery && !stmt.HasDistinct()) || stmt.IsSimpleDerivative() {
return NewRawExecutor(stmt, mappers, chunkSize), nil
} else {
return NewAggregateExecutor(stmt, mappers), nil
}
}
// CreateMappers will create a set of mappers that need to be run to execute the map phase of a MapReduceJob.
func (tx *tx) CreateMapReduceJobs(stmt *influxql.SelectStatement, tagKeys []string) ([]*influxql.MapReduceJob, error) {
// Parse the source segments.
database, policyName, measurement, err := splitIdent(stmt.Source.(*influxql.Measurement).Name)
if err != nil {
return nil, err
}
// Find database and retention policy.
db := tx.server.databases[database]
if db == nil {
return nil, ErrDatabaseNotFound
}
rp := db.policies[policyName]
if rp == nil {
return nil, ErrRetentionPolicyNotFound
}
// Find measurement.
m, err := tx.server.measurement(database, measurement)
if err != nil {
return nil, err
}
if m == nil {
return nil, ErrMeasurementNotFound
}
tx.measurement = m
tx.decoder = NewFieldCodec(m)
// Validate the fields and tags asked for exist and keep track of which are in the select vs the where
var selectFields []*Field
var whereFields []*Field
var selectTags []string
for _, n := range stmt.NamesInSelect() {
f := m.FieldByName(n)
if f != nil {
selectFields = append(selectFields, f)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in select clause: %s", n)
}
selectTags = append(selectTags, n)
}
for _, n := range stmt.NamesInWhere() {
if n == "time" {
continue
}
f := m.FieldByName(n)
if f != nil {
whereFields = append(whereFields, f)
continue
}
if !m.HasTagKey(n) {
return nil, fmt.Errorf("unknown field or tag name in where clause: %s", n)
}
}
// Grab time range from statement.
tmin, tmax := influxql.TimeRange(stmt.Condition)
if tmax.IsZero() {
tmax = tx.now
}
if tmin.IsZero() {
tmin = time.Unix(0, 0)
}
// Find shard groups within time range.
var shardGroups []*ShardGroup
for _, group := range rp.shardGroups {
if group.Contains(tmin, tmax) {
shardGroups = append(shardGroups, group)
}
}
if len(shardGroups) == 0 {
return nil, nil
}
// get the sorted unique tag sets for this query.
tagSets := m.tagSets(stmt, tagKeys)
jobs := make([]*influxql.MapReduceJob, 0, len(tagSets))
for _, t := range tagSets {
// make a job for each tagset
job := &influxql.MapReduceJob{
MeasurementName: m.Name,
TagSet: t,
TMin: tmin.UnixNano(),
TMax: tmax.UnixNano(),
}
// make a mapper for each shard that must be hit. We may need to hit multiple shards within a shard group
mappers := make([]influxql.Mapper, 0)
// create mappers for each shard we need to hit
for _, sg := range shardGroups {
if len(sg.Shards) != 1 { // we'll only have more than 1 shard in a group when RF < # servers in cluster
// TODO: implement distributed queries.
panic("distributed queries not implemented yet and there are too many shards in this group")
}
shard := sg.Shards[0]
mapper := &LocalMapper{
seriesIDs: t.SeriesIDs,
db: shard.store,
job: job,
decoder: NewFieldCodec(m),
filters: t.Filters,
whereFields: whereFields,
selectFields: selectFields,
selectTags: selectTags,
}
mappers = append(mappers, mapper)
}
job.Mappers = mappers
jobs = append(jobs, job)
}
// always return them in sorted order so the results from running the jobs are returned in a deterministic order
sort.Sort(influxql.MapReduceJobs(jobs))
return jobs, nil
}