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mapper.go
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mapper.go
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package tsdb
import (
"encoding/binary"
"errors"
"fmt"
"sort"
"strings"
"github.com/boltdb/bolt"
"github.com/influxdb/influxdb/influxql"
)
// mapperValue is a complex type, which can encapsulate data from both raw and aggregate
// mappers. This currently allows marshalling and network system to remain simpler. For
// aggregate output Time is ignored, and actual Time-Value pairs are contained soley
// within the Value field.
type mapperValue struct {
Time int64 `json:"time,omitempty"` // Ignored for aggregate output.
Value interface{} `json:"value,omitempty"` // For aggregate, contains interval time multiple values.
}
type mapperValues []*mapperValue
func (a mapperValues) Len() int { return len(a) }
func (a mapperValues) Less(i, j int) bool { return a[i].Time < a[j].Time }
func (a mapperValues) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
type mapperOutput struct {
Name string `json:"name,omitempty"`
Tags map[string]string `json:"tags,omitempty"`
Values []*mapperValue `json:"values,omitempty"` // For aggregates contains a single value at [0]
}
func (mo *mapperOutput) key() string {
return formMeasurementTagSetKey(mo.Name, mo.Tags)
}
// RawMapper is for retrieving data, for a raw query, for a single shard.
type RawMapper struct {
shard *Shard
stmt *influxql.SelectStatement
chunkSize int
tx *bolt.Tx // Read transaction for this shard.
queryTMin int64
queryTMax int64
whereFields []string // field names that occur in the where clause
selectFields []string // field names that occur in the select clause
selectTags []string // tag keys that occur in the select clause
fieldName string // the field name being read.
decoders map[string]*FieldCodec // byte decoder per measurement
cursors []*tagSetCursor // Cursors per tag sets.
currCursorIndex int // Current tagset cursor being drained.
}
// NewRawMapper returns a mapper for the given shard, which will return data for the SELECT statement.
func NewRawMapper(shard *Shard, stmt *influxql.SelectStatement, chunkSize int) *RawMapper {
return &RawMapper{
shard: shard,
stmt: stmt,
chunkSize: chunkSize,
cursors: make([]*tagSetCursor, 0),
}
}
// Open opens the raw mapper.
func (rm *RawMapper) Open() error {
// Get a read-only transaction.
tx, err := rm.shard.DB().Begin(false)
if err != nil {
return err
}
rm.tx = tx
// Set all time-related parameters on the mapper.
rm.queryTMin, rm.queryTMax = influxql.TimeRangeAsEpochNano(rm.stmt.Condition)
// Create the TagSet cursors for the Mapper.
for _, src := range rm.stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return fmt.Errorf("invalid source type: %#v", src)
}
m := rm.shard.index.Measurement(mm.Name)
if m == nil {
// This shard have never received data for the measurement. No Mapper
// required.
return nil
}
// Create tagset cursors and determine various field types within SELECT statement.
tsf, err := createTagSetsAndFields(m, rm.stmt)
if err != nil {
return err
}
tagSets := tsf.tagSets
rm.selectFields = tsf.selectFields
rm.selectTags = tsf.selectTags
rm.whereFields = tsf.whereFields
if len(rm.selectFields) == 0 {
return fmt.Errorf("select statement must include at least one field")
}
// SLIMIT and SOFFSET the unique series
if rm.stmt.SLimit > 0 || rm.stmt.SOffset > 0 {
if rm.stmt.SOffset > len(tagSets) {
tagSets = nil
} else {
if rm.stmt.SOffset+rm.stmt.SLimit > len(tagSets) {
rm.stmt.SLimit = len(tagSets) - rm.stmt.SOffset
}
tagSets = tagSets[rm.stmt.SOffset : rm.stmt.SOffset+rm.stmt.SLimit]
}
}
// Create all cursors for reading the data from this shard.
for _, t := range tagSets {
cursors := []*seriesCursor{}
for i, key := range t.SeriesKeys {
c := createCursorForSeries(rm.tx, rm.shard, key)
if c == nil {
// No data exists for this key.
continue
}
cm := newSeriesCursor(c, t.Filters[i])
cm.SeekTo(rm.queryTMin)
cursors = append(cursors, cm)
}
tsc := newTagSetCursor(m.Name, t.Tags, cursors, rm.shard.FieldCodec(m.Name))
rm.cursors = append(rm.cursors, tsc)
}
sort.Sort(tagSetCursors(rm.cursors))
}
return nil
}
// TagSets returns the list of TagSets for which this mapper has data.
func (rm *RawMapper) TagSets() []string {
return tagSetCursors(rm.cursors).Keys()
}
// NextChunk returns the next chunk of data. Data comes in the same order as the
// tags return by TagSets. A chunk never contains data for more than 1 tagset.
// If there is no more data for any tagset, nil will be returned.
func (rm *RawMapper) NextChunk() (interface{}, error) {
var output *mapperOutput
for {
if rm.currCursorIndex == len(rm.cursors) {
// All tagset cursors processed. NextChunk'ing complete.
return nil, nil
}
cursor := rm.cursors[rm.currCursorIndex]
_, k, v := cursor.Next(rm.queryTMin, rm.queryTMax, rm.selectFields, rm.whereFields)
if v == nil {
// Tagset cursor is empty, move to next one.
rm.currCursorIndex++
if output != nil {
// There is data, so return it and continue when next called.
return output, nil
} else {
// Just go straight to the next cursor.
continue
}
}
if output == nil {
output = &mapperOutput{
Name: cursor.measurement,
Tags: cursor.tags,
}
}
value := &mapperValue{Time: k, Value: v}
output.Values = append(output.Values, value)
if len(output.Values) == rm.chunkSize {
return output, nil
}
}
}
// Close closes the mapper.
func (rm *RawMapper) Close() {
if rm != nil && rm.tx != nil {
_ = rm.tx.Rollback()
}
}
// AggMapper is for retrieving data, for an aggregate query, from a given shard.
type AggMapper struct {
shard *Shard
stmt *influxql.SelectStatement
tx *bolt.Tx // Read transaction for this shard.
queryTMin int64 // Minimum time of the query.
queryTMinWindow int64 // Minimum time of the query floored to start of interval.
queryTMax int64 // Maximum time of the query.
intervalSize int64 // Size of each interval.
mapFuncs []influxql.MapFunc // The mapping functions.
fieldNames []string // the field name being read for mapping.
whereFields []string // field names that occur in the where clause
selectFields []string // field names that occur in the select clause
selectTags []string // tag keys that occur in the select clause
numIntervals int // Maximum number of intervals to return.
currInterval int // Current interval for which data is being fetched.
cursors []*tagSetCursor // Cursors per tag sets.
currCursorIndex int // Current tagset cursor being drained.
}
// NewAggMapper returns a mapper for the given shard, which will return data for the SELECT statement.
func NewAggMapper(shard *Shard, stmt *influxql.SelectStatement) *AggMapper {
return &AggMapper{
shard: shard,
stmt: stmt,
cursors: make([]*tagSetCursor, 0),
}
}
// Open opens the aggregate mapper.
func (am *AggMapper) Open() error {
var err error
// Get a read-only transaction.
tx, err := am.shard.DB().Begin(false)
if err != nil {
return err
}
am.tx = tx
// Set up each mapping function for this statement.
aggregates := am.stmt.FunctionCalls()
am.mapFuncs = make([]influxql.MapFunc, len(aggregates))
am.fieldNames = make([]string, len(am.mapFuncs))
for i, c := range aggregates {
am.mapFuncs[i], err = influxql.InitializeMapFunc(c)
if err != nil {
return err
}
// Check for calls like `derivative(mean(value), 1d)`
var nested *influxql.Call = c
if fn, ok := c.Args[0].(*influxql.Call); ok {
nested = fn
}
switch lit := nested.Args[0].(type) {
case *influxql.VarRef:
am.fieldNames[i] = lit.Val
case *influxql.Distinct:
if c.Name != "count" {
return fmt.Errorf("aggregate call didn't contain a field %s", c.String())
}
am.fieldNames[i] = lit.Val
default:
return fmt.Errorf("aggregate call didn't contain a field %s", c.String())
}
}
// Set all time-related parameters on the mapper.
am.queryTMin, am.queryTMax = influxql.TimeRangeAsEpochNano(am.stmt.Condition)
// For GROUP BY time queries, limit the number of data points returned by the limit and offset
d, err := am.stmt.GroupByInterval()
if err != nil {
return err
}
am.intervalSize = d.Nanoseconds()
if am.queryTMin == 0 || am.intervalSize == 0 {
am.numIntervals = 1
am.intervalSize = am.queryTMax - am.queryTMin
} else {
intervalTop := am.queryTMax/am.intervalSize*am.intervalSize + am.intervalSize
intervalBottom := am.queryTMin / am.intervalSize * am.intervalSize
am.numIntervals = int((intervalTop - intervalBottom) / am.intervalSize)
}
if am.stmt.Limit > 0 || am.stmt.Offset > 0 {
// ensure that the offset isn't higher than the number of points we'd get
if am.stmt.Offset > am.numIntervals {
return nil
}
// Take the lesser of either the pre computed number of GROUP BY buckets that
// will be in the result or the limit passed in by the user
if am.stmt.Limit < am.numIntervals {
am.numIntervals = am.stmt.Limit
}
}
// If we are exceeding our MaxGroupByPoints error out
if am.numIntervals > MaxGroupByPoints {
return errors.New("too many points in the group by interval. maybe you forgot to specify a where time clause?")
}
// Ensure that the start time for the results is on the start of the window.
am.queryTMinWindow = am.queryTMin
if am.intervalSize > 0 {
am.queryTMinWindow = am.queryTMinWindow / am.intervalSize * am.intervalSize
}
// Create the TagSet cursors for the Mapper.
for _, src := range am.stmt.Sources {
mm, ok := src.(*influxql.Measurement)
if !ok {
return fmt.Errorf("invalid source type: %#v", src)
}
m := am.shard.index.Measurement(mm.Name)
if m == nil {
// This shard have never received data for the measurement. No Mapper
// required.
return nil
}
// Create tagset cursors and determine various field types within SELECT statement.
tsf, err := createTagSetsAndFields(m, am.stmt)
if err != nil {
return err
}
tagSets := tsf.tagSets
am.selectFields = tsf.selectFields
am.selectTags = tsf.selectTags
am.whereFields = tsf.whereFields
// Validate that group by is not a field
if err := m.ValidateGroupBy(am.stmt); err != nil {
return err
}
// SLIMIT and SOFFSET the unique series
if am.stmt.SLimit > 0 || am.stmt.SOffset > 0 {
if am.stmt.SOffset > len(tagSets) {
tagSets = nil
} else {
if am.stmt.SOffset+am.stmt.SLimit > len(tagSets) {
am.stmt.SLimit = len(tagSets) - am.stmt.SOffset
}
tagSets = tagSets[am.stmt.SOffset : am.stmt.SOffset+am.stmt.SLimit]
}
}
// Create all cursors for reading the data from this shard.
for _, t := range tagSets {
cursors := []*seriesCursor{}
for i, key := range t.SeriesKeys {
c := createCursorForSeries(am.tx, am.shard, key)
if c == nil {
// No data exists for this key.
continue
}
cm := newSeriesCursor(c, t.Filters[i])
cursors = append(cursors, cm)
}
tsc := newTagSetCursor(m.Name, t.Tags, cursors, am.shard.FieldCodec(m.Name))
am.cursors = append(am.cursors, tsc)
}
sort.Sort(tagSetCursors(am.cursors))
}
return nil
}
// NextChunk returns the next chunk of data, which is the next interval of data
// for the current tagset. Tagsets are always processed in the same order as that
// returned by AvailTagsSets(). When there is no more data for any tagset nil
// is returned.
func (am *AggMapper) NextChunk() (interface{}, error) {
var output *mapperOutput
for {
if am.currCursorIndex == len(am.cursors) {
// All tagset cursors processed. NextChunk'ing complete.
return nil, nil
}
cursor := am.cursors[am.currCursorIndex]
tmin, tmax := am.nextInterval()
if tmin < 0 {
// All intervals complete for this tagset. Move to the next tagset.
am.resetIntervals()
am.currCursorIndex++
continue
}
// Prep the return data for this tagset. This will hold data for a single interval
// for a single tagset.
if output == nil {
output = &mapperOutput{
Name: cursor.measurement,
Tags: cursor.tags,
Values: make([]*mapperValue, 1),
}
// Aggregate values only use the first entry in the Values field. Set the time
// to the start of the interval.
output.Values[0] = &mapperValue{
Time: tmin,
Value: make([]interface{}, 0)}
}
// Always clamp tmin. This can happen as bucket-times are bucketed to the nearest
// interval, and this can be less than the times in the query.
qmin := tmin
if qmin < am.queryTMin {
qmin = am.queryTMin
}
for i := range am.mapFuncs {
// Set the cursor to the start of the interval. This is not ideal, as it should
// really calculate the values all in 1 pass, but that would require changes
// to the mapper functions, which can come later.
cursor.SeekTo(tmin)
// Wrap the tagset cursor so it implements the mapping functions interface.
f := func() (seriesKey string, time int64, value interface{}) {
return cursor.Next(qmin, tmax, []string{am.fieldNames[i]}, am.whereFields)
}
tagSetCursor := &aggTagSetCursor{
nextFunc: f,
}
// Execute the map function which walks the entire interval, and aggregates
// the result.
values := output.Values[0].Value.([]interface{})
output.Values[0].Value = append(values, am.mapFuncs[i](tagSetCursor))
}
return output, nil
}
}
// nextInterval returns the next interval for which to return data. If start is less than 0
// there are no more intervals.
func (am *AggMapper) nextInterval() (start, end int64) {
t := am.queryTMinWindow + int64(am.currInterval+am.stmt.Offset)*am.intervalSize
// Onto next interval.
am.currInterval++
if t > am.queryTMax || am.currInterval > am.numIntervals {
start, end = -1, 1
} else {
start, end = t, t+am.intervalSize
}
return
}
// resetIntervals starts the Mapper at the first interval. Subsequent intervals
// should be retrieved via nextInterval().
func (am *AggMapper) resetIntervals() {
am.currInterval = 0
}
// TagSets returns the list of TagSets for which this mapper has data.
func (am *AggMapper) TagSets() []string {
return tagSetCursors(am.cursors).Keys()
}
// Close closes the mapper.
func (am *AggMapper) Close() {
if am != nil && am.tx != nil {
_ = am.tx.Rollback()
}
}
// aggTagSetCursor wraps a standard tagSetCursor, such that the values it emits are aggregated
// by intervals.
type aggTagSetCursor struct {
nextFunc func() (seriesKey string, time int64, value interface{})
}
// Next returns the next value for the aggTagSetCursor. It implements the interface expected
// by the mapping functions.
func (a *aggTagSetCursor) Next() (seriesKey string, time int64, value interface{}) {
return a.nextFunc()
}
// tagSetCursor is virtual cursor that iterates over mutiple series cursors, as though it were
// a single series.
type tagSetCursor struct {
measurement string // Measurement name
tags map[string]string // Tag key-value pairs
cursors []*seriesCursor // Underlying series cursors.
decoder *FieldCodec // decoder for the raw data bytes
}
// tagSetCursors represents a sortable slice of tagSetCursors.
type tagSetCursors []*tagSetCursor
func (a tagSetCursors) Len() int { return len(a) }
func (a tagSetCursors) Less(i, j int) bool { return a[i].key() < a[j].key() }
func (a tagSetCursors) Swap(i, j int) { a[i], a[j] = a[j], a[i] }
func (a tagSetCursors) Keys() []string {
keys := []string{}
for i := range a {
keys = append(keys, a[i].key())
}
sort.Strings(keys)
return keys
}
// newTagSetCursor returns a tagSetCursor
func newTagSetCursor(m string, t map[string]string, c []*seriesCursor, d *FieldCodec) *tagSetCursor {
return &tagSetCursor{
measurement: m,
tags: t,
cursors: c,
decoder: d,
}
}
func (tsc *tagSetCursor) key() string {
return formMeasurementTagSetKey(tsc.measurement, tsc.tags)
}
// Next returns the next matching series-key, timestamp and byte slice for the tagset. Filtering
// is enforced on the values. If there is no matching value, then a nil result is returned.
func (tsc *tagSetCursor) Next(tmin, tmax int64, selectFields, whereFields []string) (string, int64, interface{}) {
for {
// Find the cursor with the lowest timestamp, as that is the one to be read next.
minCursor := tsc.nextCursor(tmin, tmax)
if minCursor == nil {
// No cursor of this tagset has any matching data.
return "", 0, nil
}
timestamp, bytes := minCursor.Next()
var value interface{}
if len(selectFields) > 1 {
if fieldsWithNames, err := tsc.decoder.DecodeFieldsWithNames(bytes); err == nil {
value = fieldsWithNames
// if there's a where clause, make sure we don't need to filter this value
if minCursor.filter != nil && !matchesWhere(minCursor.filter, fieldsWithNames) {
value = nil
}
}
} else {
// With only 1 field SELECTed, decoding all fields may be avoidable, which is faster.
var err error
value, err = tsc.decoder.DecodeByName(selectFields[0], bytes)
if err != nil {
continue
}
// If there's a WHERE clase, see if we need to filter
if minCursor.filter != nil {
// See if the WHERE is only on this field or on one or more other fields.
// If the latter, we'll have to decode everything
if len(whereFields) == 1 && whereFields[0] == selectFields[0] {
if !matchesWhere(minCursor.filter, map[string]interface{}{selectFields[0]: value}) {
value = nil
}
} else { // Decode everything
fieldsWithNames, err := tsc.decoder.DecodeFieldsWithNames(bytes)
if err != nil || !matchesWhere(minCursor.filter, fieldsWithNames) {
value = nil
}
}
}
}
// Value didn't match, look for the next one.
if value == nil {
continue
}
return "", timestamp, value
}
}
// SeekTo seeks each underlying cursor to the specified key.
func (tsc *tagSetCursor) SeekTo(key int64) {
for _, c := range tsc.cursors {
c.SeekTo(key)
}
}
// IsEmpty returns whether the tagsetCursor has any more data for the given interval.
func (tsc *tagSetCursor) IsEmptyForInterval(tmin, tmax int64) bool {
for _, c := range tsc.cursors {
k, _ := c.Peek()
if k != 0 && k >= tmin && k <= tmax {
return false
}
}
return true
}
// nextCursor returns the series cursor with the lowest next timestamp, within in the specified
// range. If none exists, nil is returned.
func (tsc *tagSetCursor) nextCursor(tmin, tmax int64) *seriesCursor {
var minCursor *seriesCursor
var timestamp int64
for _, c := range tsc.cursors {
timestamp, _ = c.Peek()
if timestamp != 0 && ((timestamp == tmin) || (timestamp >= tmin && timestamp < tmax)) {
if minCursor == nil {
minCursor = c
} else {
if currMinTimestamp, _ := minCursor.Peek(); timestamp < currMinTimestamp {
minCursor = c
}
}
}
}
return minCursor
}
// seriesCursor is a cursor that walks a single series. It provides lookahead functionality.
type seriesCursor struct {
cursor *shardCursor // BoltDB cursor for a series
filter influxql.Expr
keyBuffer int64 // The current timestamp key for the cursor
valueBuffer []byte // The current value for the cursor
}
// newSeriesCursor returns a new instance of a series cursor.
func newSeriesCursor(b *shardCursor, filter influxql.Expr) *seriesCursor {
return &seriesCursor{
cursor: b,
filter: filter,
keyBuffer: -1, // Nothing buffered.
}
}
// Peek returns the next timestamp and value, without changing what will be
// be returned by a call to Next()
func (mc *seriesCursor) Peek() (key int64, value []byte) {
if mc.keyBuffer == -1 {
k, v := mc.cursor.Next()
if k == nil {
mc.keyBuffer = 0
} else {
mc.keyBuffer = int64(btou64(k))
mc.valueBuffer = v
}
}
key, value = mc.keyBuffer, mc.valueBuffer
return
}
// SeekTo positions the cursor at the key, such that Next() will return
// the key and value at key.
func (mc *seriesCursor) SeekTo(key int64) {
k, v := mc.cursor.Seek(u64tob(uint64(key)))
if k == nil {
mc.keyBuffer = 0
} else {
mc.keyBuffer, mc.valueBuffer = int64(btou64(k)), v
}
}
// Next returns the next timestamp and value from the cursor.
func (mc *seriesCursor) Next() (key int64, value []byte) {
if mc.keyBuffer != -1 {
key, value = mc.keyBuffer, mc.valueBuffer
mc.keyBuffer, mc.valueBuffer = -1, nil
} else {
k, v := mc.cursor.Next()
if k == nil {
key = 0
} else {
key, value = int64(btou64(k)), v
}
}
return
}
// createCursorForSeries creates a cursor for walking the given series key. The cursor
// consolidates both the Bolt store and any WAL cache.
func createCursorForSeries(tx *bolt.Tx, shard *Shard, key string) *shardCursor {
// Retrieve key bucket.
b := tx.Bucket([]byte(key))
// Ignore if there is no bucket or points in the cache.
partitionID := WALPartition([]byte(key))
if b == nil && len(shard.cache[partitionID][key]) == 0 {
return nil
}
// Retrieve a copy of the in-cache points for the key.
cache := make([][]byte, len(shard.cache[partitionID][key]))
copy(cache, shard.cache[partitionID][key])
// Build a cursor that merges the bucket and cache together.
cur := &shardCursor{cache: cache}
if b != nil {
cur.cursor = b.Cursor()
}
return cur
}
type tagSetsAndFields struct {
tagSets []*influxql.TagSet
selectFields []string
selectTags []string
whereFields []string
}
// 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
}
// matchesFilter returns true if the value matches the where clause
func matchesWhere(f influxql.Expr, fields map[string]interface{}) bool {
if ok, _ := influxql.Eval(f, fields).(bool); !ok {
return false
}
return true
}
func formMeasurementTagSetKey(name string, tags map[string]string) string {
if len(tags) == 0 {
return name
}
return strings.Join([]string{name, string(marshalTags(tags))}, "|")
}
// btou64 converts an 8-byte slice into an uint64.
func btou64(b []byte) uint64 { return binary.BigEndian.Uint64(b) }