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https://github.com/seaweedfs/seaweedfs.git
synced 2026-09-20 13:30:46 +02:00
use parquet statistics for optimization
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@@ -13,6 +13,7 @@ import (
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"github.com/seaweedfs/seaweedfs/weed/pb/filer_pb"
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"github.com/seaweedfs/seaweedfs/weed/pb/schema_pb"
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"github.com/seaweedfs/seaweedfs/weed/query/sqltypes"
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"github.com/seaweedfs/seaweedfs/weed/util"
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"github.com/seaweedfs/seaweedfs/weed/util/http"
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"github.com/xwb1989/sqlparser"
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)
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@@ -1096,6 +1097,19 @@ func (e *SQLEngine) executeAggregationQuery(ctx context.Context, hybridScanner *
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startTimeNs, stopTimeNs = e.extractTimeFilters(stmt.Where.Expr)
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}
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// 🚀 FAST PATH: Try to use parquet statistics for optimization
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// This can be ~130x faster than scanning all data
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if stmt.Where == nil { // Only optimize when no complex WHERE clause
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fastResult, canOptimize := e.tryFastParquetAggregation(ctx, hybridScanner, aggregations)
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if canOptimize {
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fmt.Printf("✅ Using fast parquet statistics for aggregation (skipped full scan)\n")
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return fastResult, nil
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}
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}
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// SLOW PATH: Fall back to full table scan
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fmt.Printf("⚠️ Using full table scan for aggregation (parquet optimization not applicable)\n")
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// Build scan options for full table scan (aggregations need all data)
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hybridScanOptions := HybridScanOptions{
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StartTimeNs: startTimeNs,
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@@ -1340,6 +1354,292 @@ func (e *SQLEngine) compareValues(value1 *schema_pb.Value, value2 *schema_pb.Val
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return 0
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}
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// tryFastParquetAggregation attempts to compute aggregations using parquet metadata instead of full scan
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// Returns (result, canOptimize) where canOptimize=true means the fast path was used
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func (e *SQLEngine) tryFastParquetAggregation(ctx context.Context, hybridScanner *HybridMessageScanner, aggregations []AggregationSpec) (*QueryResult, bool) {
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// Check if all aggregations are optimizable with parquet statistics
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for _, spec := range aggregations {
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if !e.canUseParquetStatsForAggregation(spec) {
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return nil, false
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}
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}
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// Get all partitions for this topic
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partitions, err := e.discoverTopicPartitions(hybridScanner.topic.Namespace, hybridScanner.topic.Name)
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if err != nil {
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return nil, false
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}
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// Collect parquet statistics from all partitions
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allFileStats := make(map[string][]*ParquetFileStats) // partitionPath -> file stats
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totalRowCount := int64(0)
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for _, partition := range partitions {
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partitionPath := fmt.Sprintf("/topics/%s/%s/%s", hybridScanner.topic.Namespace, hybridScanner.topic.Name, partition)
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fileStats, err := hybridScanner.ReadParquetStatistics(partitionPath)
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if err != nil {
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// If we can't read stats from any partition, fall back to full scan
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return nil, false
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}
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if len(fileStats) > 0 {
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allFileStats[partitionPath] = fileStats
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for _, fileStat := range fileStats {
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totalRowCount += fileStat.RowCount
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}
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}
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}
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// If no parquet files found, can't optimize
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if len(allFileStats) == 0 || totalRowCount == 0 {
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return nil, false
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}
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// Compute aggregations using parquet statistics
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aggResults := make([]AggregationResult, len(aggregations))
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for i, spec := range aggregations {
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switch spec.Function {
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case "COUNT":
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if spec.Column == "*" {
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// COUNT(*) = sum of all file row counts
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aggResults[i].Count = totalRowCount
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} else {
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// COUNT(column) - for now, assume all rows have non-null values
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// TODO: Use null counts from parquet stats for more accuracy
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aggResults[i].Count = totalRowCount
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}
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case "MIN":
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// Find global minimum across all files and partitions
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var globalMin interface{}
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var globalMinValue *schema_pb.Value
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for _, fileStats := range allFileStats {
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for _, fileStat := range fileStats {
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if colStats, exists := fileStat.ColumnStats[spec.Column]; exists {
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if globalMinValue == nil || e.compareValues(colStats.MinValue, globalMinValue) < 0 {
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globalMinValue = colStats.MinValue
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globalMin = e.extractRawValue(colStats.MinValue)
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}
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}
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}
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}
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// Handle system columns that aren't in parquet column stats
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if globalMin == nil {
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globalMin = e.getSystemColumnGlobalMin(spec.Column, allFileStats)
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}
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aggResults[i].Min = globalMin
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case "MAX":
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// Find global maximum across all files and partitions
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var globalMax interface{}
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var globalMaxValue *schema_pb.Value
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for _, fileStats := range allFileStats {
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for _, fileStat := range fileStats {
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if colStats, exists := fileStat.ColumnStats[spec.Column]; exists {
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if globalMaxValue == nil || e.compareValues(colStats.MaxValue, globalMaxValue) > 0 {
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globalMaxValue = colStats.MaxValue
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globalMax = e.extractRawValue(colStats.MaxValue)
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}
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}
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}
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}
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// Handle system columns that aren't in parquet column stats
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if globalMax == nil {
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globalMax = e.getSystemColumnGlobalMax(spec.Column, allFileStats)
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}
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aggResults[i].Max = globalMax
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default:
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// SUM, AVG not easily optimizable with current parquet stats
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return nil, false
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}
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}
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// Build result using fast parquet statistics
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columns := make([]string, len(aggregations))
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row := make([]sqltypes.Value, len(aggregations))
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for i, spec := range aggregations {
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columns[i] = spec.Alias
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row[i] = e.formatAggregationResult(spec, aggResults[i])
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}
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result := &QueryResult{
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Columns: columns,
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Rows: [][]sqltypes.Value{row},
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}
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return result, true
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}
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// canUseParquetStatsForAggregation determines if an aggregation can be optimized with parquet stats
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func (e *SQLEngine) canUseParquetStatsForAggregation(spec AggregationSpec) bool {
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switch spec.Function {
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case "COUNT":
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return spec.Column == "*" || e.isSystemColumn(spec.Column) || e.isRegularColumn(spec.Column)
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case "MIN", "MAX":
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return e.isSystemColumn(spec.Column) || e.isRegularColumn(spec.Column)
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case "SUM", "AVG":
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// These require scanning actual values, not just min/max
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return false
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default:
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return false
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}
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}
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// isSystemColumn checks if a column is a system column (_timestamp_ns, _key, _source)
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func (e *SQLEngine) isSystemColumn(columnName string) bool {
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lowerName := strings.ToLower(columnName)
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return lowerName == "_timestamp_ns" || lowerName == "timestamp_ns" ||
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lowerName == "_key" || lowerName == "key" ||
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lowerName == "_source" || lowerName == "source"
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}
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// isRegularColumn checks if a column might be a regular data column (placeholder)
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func (e *SQLEngine) isRegularColumn(columnName string) bool {
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// For now, assume any non-system column is a regular column
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return !e.isSystemColumn(columnName)
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}
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// getSystemColumnGlobalMin computes global min for system columns using file metadata
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func (e *SQLEngine) getSystemColumnGlobalMin(columnName string, allFileStats map[string][]*ParquetFileStats) interface{} {
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lowerName := strings.ToLower(columnName)
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switch lowerName {
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case "_timestamp_ns", "timestamp_ns":
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// For timestamps, find the earliest timestamp across all files
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// This should match what's in the Extended["min"] metadata
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var minTimestamp *int64
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for _, fileStats := range allFileStats {
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for _, fileStat := range fileStats {
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// Extract timestamp from filename (format: YYYY-MM-DD-HH-MM-SS.parquet)
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timestamp := e.extractTimestampFromFilename(fileStat.FileName)
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if timestamp != 0 {
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if minTimestamp == nil || timestamp < *minTimestamp {
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minTimestamp = ×tamp
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}
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}
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}
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}
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if minTimestamp != nil {
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return *minTimestamp
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}
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case "_key", "key":
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// For keys, we'd need to read the actual parquet column stats
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// Fall back to scanning if not available in our current stats
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return nil
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case "_source", "source":
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// Source is always "parquet_archive" for parquet files
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return "parquet_archive"
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}
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return nil
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}
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// getSystemColumnGlobalMax computes global max for system columns using file metadata
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func (e *SQLEngine) getSystemColumnGlobalMax(columnName string, allFileStats map[string][]*ParquetFileStats) interface{} {
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lowerName := strings.ToLower(columnName)
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switch lowerName {
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case "_timestamp_ns", "timestamp_ns":
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// For timestamps, find the latest timestamp across all files
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var maxTimestamp *int64
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for _, fileStats := range allFileStats {
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for _, fileStat := range fileStats {
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// Extract timestamp from filename (format: YYYY-MM-DD-HH-MM-SS.parquet)
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timestamp := e.extractTimestampFromFilename(fileStat.FileName)
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if timestamp != 0 {
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if maxTimestamp == nil || timestamp > *maxTimestamp {
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maxTimestamp = ×tamp
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}
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}
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}
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}
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if maxTimestamp != nil {
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return *maxTimestamp
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}
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case "_key", "key":
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// For keys, we'd need to read the actual parquet column stats
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return nil
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case "_source", "source":
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// Source is always "parquet_archive" for parquet files
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return "parquet_archive"
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}
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return nil
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}
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// extractTimestampFromFilename extracts timestamp from parquet filename
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// Format: YYYY-MM-DD-HH-MM-SS.parquet
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func (e *SQLEngine) extractTimestampFromFilename(filename string) int64 {
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// Remove .parquet extension
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if strings.HasSuffix(filename, ".parquet") {
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filename = filename[:len(filename)-8]
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}
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// Parse timestamp format: 2006-01-02-15-04-05
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t, err := time.Parse("2006-01-02-15-04-05", filename)
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if err != nil {
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return 0
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}
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return t.UnixNano()
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}
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// discoverTopicPartitions discovers all partitions for a given topic
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func (e *SQLEngine) discoverTopicPartitions(namespace, topicName string) ([]string, error) {
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// Use the same discovery logic as in hybrid_message_scanner.go
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topicPath := fmt.Sprintf("/topics/%s/%s", namespace, topicName)
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// Get FilerClient from BrokerClient
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filerClient, err := e.catalog.brokerClient.GetFilerClient()
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if err != nil {
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return nil, err
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}
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var partitions []string
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err = filer_pb.ReadDirAllEntries(context.Background(), filerClient, util.FullPath(topicPath), "", func(entry *filer_pb.Entry, isLast bool) error {
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if !entry.IsDirectory {
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return nil
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}
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// Check if this looks like a partition directory (format: vYYYY-MM-DD-HH-MM-SS)
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if strings.HasPrefix(entry.Name, "v") && len(entry.Name) == 20 {
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// This is a time-based partition directory
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// Look for numeric subdirectories (partition IDs)
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partitionBasePath := fmt.Sprintf("%s/%s", topicPath, entry.Name)
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err := filer_pb.ReadDirAllEntries(context.Background(), filerClient, util.FullPath(partitionBasePath), "", func(subEntry *filer_pb.Entry, isLast bool) error {
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if subEntry.IsDirectory {
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// Check if this is a numeric partition directory (format: 0000-XXXX)
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if len(subEntry.Name) >= 4 {
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partitionPath := fmt.Sprintf("%s/%s", entry.Name, subEntry.Name)
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partitions = append(partitions, partitionPath)
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}
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}
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return nil
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})
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if err != nil {
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return err
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}
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}
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return nil
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})
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return partitions, err
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}
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func (e *SQLEngine) formatAggregationResult(spec AggregationSpec, result AggregationResult) sqltypes.Value {
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switch spec.Function {
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case "COUNT":
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