Files
loki/pkg/dataobj/sections/pointers/row_reader.go
Robert Fratto f6091a67d1 chore(engine): move to toggleable section prefetching (#19142)
dataset.readerDownloader was originally introduced in #16429, an attempt to
balance peak memory usage of reading a section with read times by downloading a
configurable size of pages in advance.

In practice, each roundtrip to object storage adds too much of a latency hit,
and we've started to set the cache limit high enough to ensure that each reader
only needs a single prefetch. Given what we've found, it no longer makes sense
to control peak memory usage via the prefetch size. Other options, such as
downloading directly to disk, may be explored in the future.

In the meantime, this PR removes the ability to specify a cache size. All
non-pruned pages will be bulk requested using the range reader (#19067) on the
first read call. Pages which have left the potential read window will continue
to be eagerly removed for garbage collection.

However, we don't want to prefetch when the dataset is entirely in memory,
which is the case when the logs section builder is performing k-way merge over
in-memory sections. To lower the memory usage of builders, prefetching is
configurable. For this initial PR, prefetching is only disabled for the logs
section builder; all other reads force prefetching.

Signed-off-by: Robert Fratto <robertfratto@gmail.com>
2025-09-09 11:54:34 -04:00

291 lines
7.8 KiB
Go

package pointers
import (
"bytes"
"context"
"errors"
"fmt"
"io"
"iter"
"maps"
"github.com/bits-and-blooms/bloom/v3"
"github.com/grafana/loki/v3/pkg/dataobj/internal/dataset"
"github.com/grafana/loki/v3/pkg/dataobj/internal/util/slicegrow"
"github.com/grafana/loki/v3/pkg/dataobj/internal/util/symbolizer"
"github.com/grafana/loki/v3/pkg/dataobj/sections/internal/columnar"
)
// RowReader reads the set of streams from an [Object].
type RowReader struct {
sec *Section
ready bool
matchIDs map[int64]struct{}
predicate RowPredicate
buf []dataset.Row
reader *dataset.Reader
columns []dataset.Column
symbols *symbolizer.Symbolizer
}
// NewRowReader creates a new RowReader that reads rows from the provided
// [Section].
func NewRowReader(sec *Section) *RowReader {
var sr RowReader
sr.Reset(sec)
return &sr
}
// MatchStreams provides a sequence of stream IDs for the logs reader to match.
// [RowReader.Read] will only return logs for the provided stream IDs.
//
// MatchStreams may be called multiple times to match multiple sets of streams.
//
// MatchStreams may only be called before reading begins or after a call to
// [RowReader.Reset].
func (r *RowReader) MatchStreams(ids iter.Seq[int64]) error {
if r.ready {
return fmt.Errorf("cannot change matched streams after reading has started")
}
if r.matchIDs == nil {
r.matchIDs = make(map[int64]struct{})
}
for id := range ids {
r.matchIDs[id] = struct{}{}
}
return nil
}
// SetPredicate sets the predicate to use for filtering logs. [LogsReader.Read]
// will only return logs for which the predicate passes.
//
// SetPredicate returns an error if the predicate is not supported by
// LogsReader.
//
// A predicate may only be set before reading begins or after a call to
// [RowReader.Reset].
func (r *RowReader) SetPredicate(p RowPredicate) error {
if r.ready {
return fmt.Errorf("cannot change predicate after reading has started")
}
r.predicate = p
return nil
}
// Read reads up to the next len(s) streams from the reader and stores them
// into s. It returns the number of streams read and any error encountered. At
// the end of the stream section, Read returns 0, io.EOF.
func (r *RowReader) Read(ctx context.Context, s []SectionPointer) (int, error) {
if r.sec == nil {
return 0, io.EOF
}
if !r.ready {
err := r.initReader()
if err != nil {
return 0, err
}
}
r.buf = slicegrow.GrowToCap(r.buf, len(s))
r.buf = r.buf[:len(s)]
n, err := r.reader.Read(ctx, r.buf)
if err != nil && !errors.Is(err, io.EOF) {
return 0, fmt.Errorf("reading rows: %w", err)
} else if n == 0 && errors.Is(err, io.EOF) {
return 0, io.EOF
}
for i := range r.buf[:n] {
if err := decodeRow(r.sec.Columns(), r.buf[i], &s[i], r.symbols); err != nil {
return i, fmt.Errorf("decoding stream: %w", err)
}
}
return n, nil
}
func (r *RowReader) initReader() error {
dset, err := columnar.MakeDataset(r.sec.inner, r.sec.inner.Columns())
if err != nil {
return fmt.Errorf("creating section dataset: %w", err)
}
columns := dset.Columns()
var predicates []dataset.Predicate
if len(r.matchIDs) > 0 {
predicates = append(predicates, streamIDPredicate(maps.Keys(r.matchIDs), columns, r.sec.Columns()))
}
if p := translatePointersPredicate(r.predicate, columns, r.sec.Columns()); p != nil {
predicates = append(predicates, p)
}
readerOpts := dataset.ReaderOptions{
Dataset: dset,
Columns: columns,
Predicates: predicates,
Prefetch: true,
}
if r.reader == nil {
r.reader = dataset.NewReader(readerOpts)
} else {
r.reader.Reset(readerOpts)
}
if r.symbols == nil {
r.symbols = symbolizer.New(128, 100_000)
} else {
r.symbols.Reset()
}
r.columns = columns
r.ready = true
return nil
}
// Reset resets the RowReader with a new decoder to read from. Reset allows
// reusing a RowReader without allocating a new one.
//
// Any set predicate is cleared when Reset is called.
//
// Reset may be called with a nil object and a negative section index to clear
// the RowReader without needing a new object.
func (r *RowReader) Reset(sec *Section) {
r.sec = sec
r.predicate = nil
r.ready = false
r.columns = nil
if r.symbols != nil {
r.symbols.Reset()
}
// We leave r.reader as-is to avoid reallocating; it'll be reset on the first
// call to Read.
}
// Close closes the RowReader and releases any resources it holds. Closed
// RowReaders can be reused by calling [RowReader.Reset].
func (r *RowReader) Close() error {
if r.reader != nil {
return r.reader.Close()
}
return nil
}
func streamIDPredicate(ids iter.Seq[int64], dsetColumns []dataset.Column, actualColumns []*Column) dataset.Predicate {
streamIDColumn := findDatasetColumn(dsetColumns, actualColumns, func(desc *Column) bool {
return desc.Type == ColumnTypeStreamID
})
if streamIDColumn == nil {
return dataset.FalsePredicate{}
}
var values []dataset.Value
for i := range ids {
values = append(values, dataset.Int64Value(i))
}
return dataset.InPredicate{
Column: streamIDColumn,
Values: dataset.NewInt64ValueSet(values),
}
}
func translatePointersPredicate(p RowPredicate, dsetColumns []dataset.Column, actualColumns []*Column) dataset.Predicate {
if p == nil {
return nil
}
nameColumn := findDatasetColumn(dsetColumns, actualColumns, func(desc *Column) bool {
return desc.Type == ColumnTypeColumnName
})
bloomColumn := findDatasetColumn(dsetColumns, actualColumns, func(desc *Column) bool {
return desc.Type == ColumnTypeValuesBloomFilter
})
startColumn := findDatasetColumn(dsetColumns, actualColumns, func(desc *Column) bool {
return desc.Type == ColumnTypeMinTimestamp
})
endColumn := findDatasetColumn(dsetColumns, actualColumns, func(desc *Column) bool {
return desc.Type == ColumnTypeMaxTimestamp
})
switch p := p.(type) {
case AndRowPredicate:
return dataset.AndPredicate{
Left: translatePointersPredicate(p.Left, dsetColumns, actualColumns),
Right: translatePointersPredicate(p.Right, dsetColumns, actualColumns),
}
case BloomExistenceRowPredicate:
return convertBloomExistenceRowPredicate(p, nameColumn, bloomColumn)
case TimeRangeRowPredicate:
return convertTimeRangeRowPredicate(p, startColumn, endColumn)
default:
panic(fmt.Sprintf("unsupported predicate type %T", p))
}
}
func convertBloomExistenceRowPredicate(p BloomExistenceRowPredicate, nameColumn, bloomColumn dataset.Column) dataset.Predicate {
if nameColumn == nil && bloomColumn == nil {
// If there are no name or bloom columns present, it means this section doesn't have any relevant columns for this predicate.
// This can happen if a whole section only contains pointers of a different Kind.
return dataset.FalsePredicate{}
}
// TODO: Make this more efficient by not re-allocating the bloom filter each time
return dataset.AndPredicate{
Left: dataset.EqualPredicate{
Column: nameColumn,
Value: dataset.BinaryValue([]byte(p.Name)),
},
Right: dataset.FuncPredicate{
Column: bloomColumn,
Keep: func(_ dataset.Column, value dataset.Value) bool {
bloomBytes := value.Binary()
bf := bloom.New(1, 1) // Dummy values
_, err := bf.ReadFrom(bytes.NewReader(bloomBytes))
if err != nil {
// If the bloom filter is invalid, we assume it would pass.
return true
}
return bf.TestString(p.Value)
},
},
}
}
func convertTimeRangeRowPredicate(p TimeRangeRowPredicate, startColumn, endColumn dataset.Column) dataset.Predicate {
return dataset.AndPredicate{
Left: dataset.GreaterThanPredicate{
Column: startColumn,
Value: dataset.Int64Value(p.Start.UnixNano() - 1),
},
Right: dataset.LessThanPredicate{
Column: endColumn,
Value: dataset.Int64Value(p.End.UnixNano() + 1),
},
}
}
func findDatasetColumn(columns []dataset.Column, actual []*Column, check func(*Column) bool) dataset.Column {
for i, desc := range actual {
if check(desc) {
return columns[i]
}
}
return nil
}