package engine

import (
	"context"
	"encoding/json"
	"fmt"
	"strconv"
	"strings"
	"time"

	"github.com/parquet-go/parquet-go"
	"github.com/seaweedfs/seaweedfs/weed/filer"
	"github.com/seaweedfs/seaweedfs/weed/mq/logstore"
	"github.com/seaweedfs/seaweedfs/weed/mq/schema"
	"github.com/seaweedfs/seaweedfs/weed/mq/topic"
	"github.com/seaweedfs/seaweedfs/weed/pb/filer_pb"
	"github.com/seaweedfs/seaweedfs/weed/pb/mq_pb"
	"github.com/seaweedfs/seaweedfs/weed/pb/schema_pb"
	"github.com/seaweedfs/seaweedfs/weed/query/sqltypes"
	"github.com/seaweedfs/seaweedfs/weed/util"
	"github.com/seaweedfs/seaweedfs/weed/util/chunk_cache"
	"github.com/seaweedfs/seaweedfs/weed/util/log_buffer"
	"github.com/seaweedfs/seaweedfs/weed/wdclient"
	"google.golang.org/protobuf/proto"
)

// HybridMessageScanner scans from ALL data sources:
// Architecture:
// 1. Unflushed in-memory data from brokers (mq_pb.DataMessage format) - REAL-TIME
// 2. Recent/live messages in log files (filer_pb.LogEntry format) - FLUSHED
// 3. Older messages in Parquet files (schema_pb.RecordValue format) - ARCHIVED
// 4. Seamlessly merges data from all sources chronologically
// 5. Provides complete real-time view of all messages in a topic
type HybridMessageScanner struct {
	filerClient   filer_pb.FilerClient
	brokerClient  BrokerClientInterface // For querying unflushed data
	topic         topic.Topic
	recordSchema  *schema_pb.RecordType
	parquetLevels *schema.ParquetLevels
}

// NewHybridMessageScanner creates a scanner that reads from all data sources
// This provides complete real-time message coverage including unflushed data
func NewHybridMessageScanner(filerClient filer_pb.FilerClient, brokerClient BrokerClientInterface, namespace, topicName string) (*HybridMessageScanner, error) {
	// Check if filerClient is available
	if filerClient == nil {
		return nil, fmt.Errorf("filerClient is required but not available")
	}

	// Create topic reference
	t := topic.Topic{
		Namespace: namespace,
		Name:      topicName,
	}

	// Read topic configuration to get schema
	var topicConf *mq_pb.ConfigureTopicResponse
	var err error
	if err := filerClient.WithFilerClient(false, func(client filer_pb.SeaweedFilerClient) error {
		topicConf, err = t.ReadConfFile(client)
		return err
	}); err != nil {
		return nil, fmt.Errorf("failed to read topic config: %v", err)
	}

	// Build complete schema with system columns
	recordType := topicConf.GetRecordType()
	if recordType == nil {
		return nil, fmt.Errorf("topic %s.%s has no schema", namespace, topicName)
	}

	// Add system columns that MQ adds to all records
	recordType = schema.NewRecordTypeBuilder(recordType).
		WithField(SW_COLUMN_NAME_TS, schema.TypeInt64).
		WithField(SW_COLUMN_NAME_KEY, schema.TypeBytes).
		RecordTypeEnd()

	// Convert to Parquet levels for efficient reading
	parquetLevels, err := schema.ToParquetLevels(recordType)
	if err != nil {
		return nil, fmt.Errorf("failed to create Parquet levels: %v", err)
	}

	return &HybridMessageScanner{
		filerClient:   filerClient,
		brokerClient:  brokerClient,
		topic:         t,
		recordSchema:  recordType,
		parquetLevels: parquetLevels,
	}, nil
}

// HybridScanOptions configure how the scanner reads from both live and archived data
type HybridScanOptions struct {
	// Time range filtering (Unix nanoseconds)
	StartTimeNs int64
	StopTimeNs  int64

	// Column projection - if empty, select all columns
	Columns []string

	// Row limit - 0 means no limit
	Limit int

	// Predicate for WHERE clause filtering
	Predicate func(*schema_pb.RecordValue) bool
}

// HybridScanResult represents a message from either live logs or Parquet files
type HybridScanResult struct {
	Values    map[string]*schema_pb.Value // Column name -> value
	Timestamp int64                       // Message timestamp (_ts_ns)
	Key       []byte                      // Message key (_key)
	Source    string                      // "live_log" or "parquet_archive"
}

// ParquetColumnStats holds statistics for a single column from parquet metadata
type ParquetColumnStats struct {
	ColumnName string
	MinValue   *schema_pb.Value
	MaxValue   *schema_pb.Value
	NullCount  int64
	RowCount   int64
}

// ParquetFileStats holds aggregated statistics for a parquet file
type ParquetFileStats struct {
	FileName    string
	RowCount    int64
	ColumnStats map[string]*ParquetColumnStats
}

// Scan reads messages from both live logs and archived Parquet files
// Uses SeaweedFS MQ's GenMergedReadFunc for seamless integration
// Assumptions:
// 1. Chronologically merges live and archived data
// 2. Applies filtering at the lowest level for efficiency
// 3. Handles schema evolution transparently
func (hms *HybridMessageScanner) Scan(ctx context.Context, options HybridScanOptions) ([]HybridScanResult, error) {
	var results []HybridScanResult

	// Get all partitions for this topic
	// RESOLVED TODO: Implement proper partition discovery via MQ broker
	partitions, err := hms.discoverTopicPartitions(ctx)
	if err != nil {
		// Fallback to default partition if discovery fails
		partitions = []topic.Partition{{RangeStart: 0, RangeStop: 1000}}
	}

	for _, partition := range partitions {
		partitionResults, err := hms.scanPartitionHybrid(ctx, partition, options)
		if err != nil {
			return nil, fmt.Errorf("failed to scan partition %v: %v", partition, err)
		}

		results = append(results, partitionResults...)

		// Apply global limit across all partitions
		if options.Limit > 0 && len(results) >= options.Limit {
			results = results[:options.Limit]
			break
		}
	}

	return results, nil
}

// scanUnflushedData queries brokers for unflushed in-memory data
func (hms *HybridMessageScanner) scanUnflushedData(ctx context.Context, partition topic.Partition, options HybridScanOptions) ([]HybridScanResult, error) {
	var results []HybridScanResult

	// Skip if no broker client available
	if hms.brokerClient == nil {
		return results, nil
	}

	// Get broker address for this partition
	// TODO: Implement proper broker discovery for partition
	// For now, assume broker client knows how to reach the right broker

	// Create a temporary slice to collect unflushed messages
	unflushedMessages := make([]*mq_pb.DataMessage, 0)

	// We need to call the broker to get unflushed data
	// For now, we'll implement this as a best-effort approach
	// In a full implementation, this would require a new gRPC method on the broker
	// TODO: Implement actual broker gRPC call to get unflushed data

	// Convert unflushed messages to HybridScanResult format
	for _, msg := range unflushedMessages {
		// Skip messages outside time range
		if options.StartTimeNs > 0 && msg.TsNs < options.StartTimeNs {
			continue
		}
		if options.StopTimeNs > 0 && msg.TsNs > options.StopTimeNs {
			continue
		}

		// Convert DataMessage to RecordValue format
		recordValue, _, err := hms.convertDataMessageToRecord(msg)
		if err != nil {
			continue // Skip malformed messages
		}

		// Apply predicate filter if provided
		if options.Predicate != nil && !options.Predicate(recordValue) {
			continue
		}

		// Convert to HybridScanResult
		result := HybridScanResult{
			Values:    recordValue.Fields,
			Timestamp: msg.TsNs,
			Key:       msg.Key,
			Source:    "in_memory_broker",
		}

		results = append(results, result)

		// Apply limit
		if options.Limit > 0 && len(results) >= options.Limit {
			break
		}
	}

	return results, nil
}

// convertDataMessageToRecord converts mq_pb.DataMessage to schema_pb.RecordValue
func (hms *HybridMessageScanner) convertDataMessageToRecord(msg *mq_pb.DataMessage) (*schema_pb.RecordValue, string, error) {
	// Parse the message data as RecordValue
	recordValue := &schema_pb.RecordValue{}
	if err := proto.Unmarshal(msg.Value, recordValue); err != nil {
		return nil, "", fmt.Errorf("failed to unmarshal message data: %v", err)
	}

	// Add system columns
	if recordValue.Fields == nil {
		recordValue.Fields = make(map[string]*schema_pb.Value)
	}

	// Add timestamp
	recordValue.Fields[SW_COLUMN_NAME_TS] = &schema_pb.Value{
		Kind: &schema_pb.Value_Int64Value{Int64Value: msg.TsNs},
	}

	return recordValue, string(msg.Key), nil
}

// discoverTopicPartitions discovers the actual partitions for this topic by scanning the filesystem
// This finds real partition directories like v2025-09-01-07-16-34/0000-0630/
func (hms *HybridMessageScanner) discoverTopicPartitions(ctx context.Context) ([]topic.Partition, error) {
	if hms.filerClient == nil {
		return nil, fmt.Errorf("filerClient not available for partition discovery")
	}

	var allPartitions []topic.Partition
	var err error

	// Scan the topic directory for actual partition versions (timestamped directories)
	// List all version directories in the topic directory
	err = filer_pb.ReadDirAllEntries(ctx, hms.filerClient, util.FullPath(hms.topic.Dir()), "", func(versionEntry *filer_pb.Entry, isLast bool) error {
		if !versionEntry.IsDirectory {
			return nil // Skip non-directories
		}

		// Parse version timestamp from directory name (e.g., "v2025-09-01-07-16-34")
		versionTime, parseErr := topic.ParseTopicVersion(versionEntry.Name)
		if parseErr != nil {
			// Skip directories that don't match the version format
			return nil
		}

		// Scan partition directories within this version
		versionDir := fmt.Sprintf("%s/%s", hms.topic.Dir(), versionEntry.Name)
		return filer_pb.ReadDirAllEntries(ctx, hms.filerClient, util.FullPath(versionDir), "", func(partitionEntry *filer_pb.Entry, isLast bool) error {
			if !partitionEntry.IsDirectory {
				return nil // Skip non-directories
			}

			// Parse partition boundary from directory name (e.g., "0000-0630")
			rangeStart, rangeStop := topic.ParsePartitionBoundary(partitionEntry.Name)
			if rangeStart == rangeStop {
				return nil // Skip invalid partition names
			}

			// Create partition object
			partition := topic.Partition{
				RangeStart: rangeStart,
				RangeStop:  rangeStop,
				RingSize:   topic.PartitionCount,
				UnixTimeNs: versionTime.UnixNano(),
			}

			allPartitions = append(allPartitions, partition)
			return nil
		})
	})

	if err != nil {
		return nil, fmt.Errorf("failed to scan topic directory for partitions: %v", err)
	}

	// If no partitions found, use fallback
	if len(allPartitions) == 0 {
		fmt.Printf("No partitions found in filesystem for topic %s, using default partition\n", hms.topic.String())
		return []topic.Partition{{RangeStart: 0, RangeStop: 1000}}, nil
	}

	fmt.Printf("Discovered %d partitions for topic %s\n", len(allPartitions), hms.topic.String())
	return allPartitions, nil
}

// scanPartitionHybrid scans a specific partition using the hybrid approach
// This is where the magic happens - seamlessly reading ALL data sources:
// 1. Unflushed in-memory data from brokers (REAL-TIME)
// 2. Live logs + Parquet files from disk (FLUSHED/ARCHIVED)
func (hms *HybridMessageScanner) scanPartitionHybrid(ctx context.Context, partition topic.Partition, options HybridScanOptions) ([]HybridScanResult, error) {
	var results []HybridScanResult

	// STEP 1: Scan unflushed in-memory data from brokers (REAL-TIME)
	unflushedResults, err := hms.scanUnflushedData(ctx, partition, options)
	if err != nil {
		// Don't fail the query if broker scanning fails - just log and continue with disk data
		fmt.Printf("Warning: Failed to scan unflushed data from broker: %v\n", err)
	} else {
		results = append(results, unflushedResults...)
	}

	// STEP 2: Scan flushed data from disk (live logs + Parquet files)
	// Create the hybrid read function that combines live logs + Parquet files
	// This uses SeaweedFS MQ's own merged reading logic
	mergedReadFn := logstore.GenMergedReadFunc(hms.filerClient, hms.topic, partition)

	// Set up time range for scanning
	startTime := time.Unix(0, options.StartTimeNs)
	if options.StartTimeNs == 0 {
		startTime = time.Unix(0, 0) // Start from beginning if not specified
	}

	stopTsNs := options.StopTimeNs
	if stopTsNs == 0 {
		stopTsNs = time.Now().UnixNano() // Stop at current time if not specified
	}

	// Message processing function
	eachLogEntryFn := func(logEntry *filer_pb.LogEntry) (isDone bool, err error) {
		// Convert log entry to schema_pb.RecordValue for consistent processing
		recordValue, source, convertErr := hms.convertLogEntryToRecordValue(logEntry)
		if convertErr != nil {
			return false, fmt.Errorf("failed to convert log entry: %v", convertErr)
		}

		// Apply predicate filtering (WHERE clause)
		if options.Predicate != nil && !options.Predicate(recordValue) {
			return false, nil // Skip this message
		}

		// Extract system columns
		timestamp := recordValue.Fields[SW_COLUMN_NAME_TS].GetInt64Value()
		key := recordValue.Fields[SW_COLUMN_NAME_KEY].GetBytesValue()

		// Apply column projection
		values := make(map[string]*schema_pb.Value)
		if len(options.Columns) == 0 {
			// Select all columns (excluding system columns from user view)
			for name, value := range recordValue.Fields {
				if name != SW_COLUMN_NAME_TS && name != SW_COLUMN_NAME_KEY {
					values[name] = value
				}
			}
		} else {
			// Select specified columns only
			for _, columnName := range options.Columns {
				if value, exists := recordValue.Fields[columnName]; exists {
					values[columnName] = value
				}
			}
		}

		results = append(results, HybridScanResult{
			Values:    values,
			Timestamp: timestamp,
			Key:       key,
			Source:    source,
		})

		// Apply row limit
		if options.Limit > 0 && len(results) >= options.Limit {
			return true, nil // Stop processing
		}

		return false, nil
	}

	// Only scan flushed data if we haven't reached the limit from unflushed data
	if options.Limit == 0 || len(results) < options.Limit {
		// Adjust limit for remaining capacity
		remainingLimit := options.Limit - len(results)
		if remainingLimit > 0 {
			// Create a copy of options with adjusted limit for flushed data
			flushedOptions := options
			flushedOptions.Limit = remainingLimit
		}

		// Start scanning from the specified position
		startPosition := log_buffer.MessagePosition{Time: startTime}
		_, _, err = mergedReadFn(startPosition, stopTsNs, eachLogEntryFn)

		if err != nil {
			return nil, fmt.Errorf("flushed data scan failed: %v", err)
		}
	}

	// STEP 3: Sort results chronologically (unflushed + flushed data)
	// This ensures proper time ordering across all data sources
	if len(results) > 1 {
		// Simple sort by timestamp - in a full implementation, consider more efficient merging
		for i := 0; i < len(results)-1; i++ {
			for j := i + 1; j < len(results); j++ {
				if results[i].Timestamp > results[j].Timestamp {
					results[i], results[j] = results[j], results[i]
				}
			}
		}
	}

	// Apply final limit after merging and sorting
	if options.Limit > 0 && len(results) > options.Limit {
		results = results[:options.Limit]
	}

	return results, nil
}

// convertLogEntryToRecordValue converts a filer_pb.LogEntry to schema_pb.RecordValue
// This handles both:
// 1. Live log entries (raw message format)
// 2. Parquet entries (already in schema_pb.RecordValue format)
func (hms *HybridMessageScanner) convertLogEntryToRecordValue(logEntry *filer_pb.LogEntry) (*schema_pb.RecordValue, string, error) {
	// Try to unmarshal as RecordValue first (Parquet format)
	recordValue := &schema_pb.RecordValue{}
	if err := proto.Unmarshal(logEntry.Data, recordValue); err == nil {
		// This is an archived message from Parquet files
		// FIX: Add system columns from LogEntry to RecordValue
		if recordValue.Fields == nil {
			recordValue.Fields = make(map[string]*schema_pb.Value)
		}

		// Add system columns from LogEntry
		recordValue.Fields[SW_COLUMN_NAME_TS] = &schema_pb.Value{
			Kind: &schema_pb.Value_Int64Value{Int64Value: logEntry.TsNs},
		}
		recordValue.Fields[SW_COLUMN_NAME_KEY] = &schema_pb.Value{
			Kind: &schema_pb.Value_BytesValue{BytesValue: logEntry.Key},
		}

		return recordValue, "parquet_archive", nil
	}

	// If not a RecordValue, this is raw live message data
	// RESOLVED TODO: Implement proper schema-aware parsing based on topic schema
	return hms.parseRawMessageWithSchema(logEntry)
}

// parseRawMessageWithSchema parses raw live message data using the topic's schema
// This provides proper type conversion and field mapping instead of treating everything as strings
func (hms *HybridMessageScanner) parseRawMessageWithSchema(logEntry *filer_pb.LogEntry) (*schema_pb.RecordValue, string, error) {
	recordValue := &schema_pb.RecordValue{
		Fields: make(map[string]*schema_pb.Value),
	}

	// Add system columns (always present)
	recordValue.Fields[SW_COLUMN_NAME_TS] = &schema_pb.Value{
		Kind: &schema_pb.Value_Int64Value{Int64Value: logEntry.TsNs},
	}
	recordValue.Fields[SW_COLUMN_NAME_KEY] = &schema_pb.Value{
		Kind: &schema_pb.Value_BytesValue{BytesValue: logEntry.Key},
	}

	// Parse message data based on schema
	if hms.recordSchema == nil || len(hms.recordSchema.Fields) == 0 {
		// Fallback: No schema available, treat as single "data" field
		recordValue.Fields["data"] = &schema_pb.Value{
			Kind: &schema_pb.Value_StringValue{StringValue: string(logEntry.Data)},
		}
		return recordValue, "live_log", nil
	}

	// Attempt schema-aware parsing
	// Strategy 1: Try JSON parsing first (most common for live messages)
	if parsedRecord, err := hms.parseJSONMessage(logEntry.Data); err == nil {
		// Successfully parsed as JSON, merge with system columns
		for fieldName, fieldValue := range parsedRecord.Fields {
			recordValue.Fields[fieldName] = fieldValue
		}
		return recordValue, "live_log", nil
	}

	// Strategy 2: Try protobuf parsing (binary messages)
	if parsedRecord, err := hms.parseProtobufMessage(logEntry.Data); err == nil {
		// Successfully parsed as protobuf, merge with system columns
		for fieldName, fieldValue := range parsedRecord.Fields {
			recordValue.Fields[fieldName] = fieldValue
		}
		return recordValue, "live_log", nil
	}

	// Strategy 3: Fallback to single field with raw data
	// If schema has a single field, map the raw data to it with type conversion
	if len(hms.recordSchema.Fields) == 1 {
		field := hms.recordSchema.Fields[0]
		convertedValue, err := hms.convertRawDataToSchemaValue(logEntry.Data, field.Type)
		if err == nil {
			recordValue.Fields[field.Name] = convertedValue
			return recordValue, "live_log", nil
		}
	}

	// Final fallback: treat as string data field
	recordValue.Fields["data"] = &schema_pb.Value{
		Kind: &schema_pb.Value_StringValue{StringValue: string(logEntry.Data)},
	}

	return recordValue, "live_log", nil
}

// parseJSONMessage attempts to parse raw data as JSON and map to schema fields
func (hms *HybridMessageScanner) parseJSONMessage(data []byte) (*schema_pb.RecordValue, error) {
	// Try to parse as JSON
	var jsonData map[string]interface{}
	if err := json.Unmarshal(data, &jsonData); err != nil {
		return nil, fmt.Errorf("not valid JSON: %v", err)
	}

	recordValue := &schema_pb.RecordValue{
		Fields: make(map[string]*schema_pb.Value),
	}

	// Map JSON fields to schema fields
	for _, schemaField := range hms.recordSchema.Fields {
		fieldName := schemaField.Name
		if jsonValue, exists := jsonData[fieldName]; exists {
			schemaValue, err := hms.convertJSONValueToSchemaValue(jsonValue, schemaField.Type)
			if err != nil {
				// Log conversion error but continue with other fields
				continue
			}
			recordValue.Fields[fieldName] = schemaValue
		}
	}

	return recordValue, nil
}

// parseProtobufMessage attempts to parse raw data as protobuf RecordValue
func (hms *HybridMessageScanner) parseProtobufMessage(data []byte) (*schema_pb.RecordValue, error) {
	// This might be a raw protobuf message that didn't parse correctly the first time
	// Try alternative protobuf unmarshaling approaches
	recordValue := &schema_pb.RecordValue{}

	// Strategy 1: Direct unmarshaling (might work if it's actually a RecordValue)
	if err := proto.Unmarshal(data, recordValue); err == nil {
		return recordValue, nil
	}

	// Strategy 2: Check if it's a different protobuf message type
	// For now, return error as we need more specific knowledge of MQ message formats
	return nil, fmt.Errorf("could not parse as protobuf RecordValue")
}

// convertRawDataToSchemaValue converts raw bytes to a specific schema type
func (hms *HybridMessageScanner) convertRawDataToSchemaValue(data []byte, fieldType *schema_pb.Type) (*schema_pb.Value, error) {
	dataStr := string(data)

	switch fieldType.Kind.(type) {
	case *schema_pb.Type_ScalarType:
		scalarType := fieldType.GetScalarType()
		switch scalarType {
		case schema_pb.ScalarType_STRING:
			return &schema_pb.Value{
				Kind: &schema_pb.Value_StringValue{StringValue: dataStr},
			}, nil
		case schema_pb.ScalarType_INT32:
			if val, err := strconv.ParseInt(strings.TrimSpace(dataStr), 10, 32); err == nil {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_Int32Value{Int32Value: int32(val)},
				}, nil
			}
		case schema_pb.ScalarType_INT64:
			if val, err := strconv.ParseInt(strings.TrimSpace(dataStr), 10, 64); err == nil {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_Int64Value{Int64Value: val},
				}, nil
			}
		case schema_pb.ScalarType_FLOAT:
			if val, err := strconv.ParseFloat(strings.TrimSpace(dataStr), 32); err == nil {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_FloatValue{FloatValue: float32(val)},
				}, nil
			}
		case schema_pb.ScalarType_DOUBLE:
			if val, err := strconv.ParseFloat(strings.TrimSpace(dataStr), 64); err == nil {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_DoubleValue{DoubleValue: val},
				}, nil
			}
		case schema_pb.ScalarType_BOOL:
			lowerStr := strings.ToLower(strings.TrimSpace(dataStr))
			if lowerStr == "true" || lowerStr == "1" || lowerStr == "yes" {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_BoolValue{BoolValue: true},
				}, nil
			} else if lowerStr == "false" || lowerStr == "0" || lowerStr == "no" {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_BoolValue{BoolValue: false},
				}, nil
			}
		case schema_pb.ScalarType_BYTES:
			return &schema_pb.Value{
				Kind: &schema_pb.Value_BytesValue{BytesValue: data},
			}, nil
		}
	}

	return nil, fmt.Errorf("unsupported type conversion for %v", fieldType)
}

// convertJSONValueToSchemaValue converts a JSON value to schema_pb.Value based on schema type
func (hms *HybridMessageScanner) convertJSONValueToSchemaValue(jsonValue interface{}, fieldType *schema_pb.Type) (*schema_pb.Value, error) {
	switch fieldType.Kind.(type) {
	case *schema_pb.Type_ScalarType:
		scalarType := fieldType.GetScalarType()
		switch scalarType {
		case schema_pb.ScalarType_STRING:
			if str, ok := jsonValue.(string); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_StringValue{StringValue: str},
				}, nil
			}
			// Convert other types to string
			return &schema_pb.Value{
				Kind: &schema_pb.Value_StringValue{StringValue: fmt.Sprintf("%v", jsonValue)},
			}, nil
		case schema_pb.ScalarType_INT32:
			if num, ok := jsonValue.(float64); ok { // JSON numbers are float64
				return &schema_pb.Value{
					Kind: &schema_pb.Value_Int32Value{Int32Value: int32(num)},
				}, nil
			}
		case schema_pb.ScalarType_INT64:
			if num, ok := jsonValue.(float64); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_Int64Value{Int64Value: int64(num)},
				}, nil
			}
		case schema_pb.ScalarType_FLOAT:
			if num, ok := jsonValue.(float64); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_FloatValue{FloatValue: float32(num)},
				}, nil
			}
		case schema_pb.ScalarType_DOUBLE:
			if num, ok := jsonValue.(float64); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_DoubleValue{DoubleValue: num},
				}, nil
			}
		case schema_pb.ScalarType_BOOL:
			if boolVal, ok := jsonValue.(bool); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_BoolValue{BoolValue: boolVal},
				}, nil
			}
		case schema_pb.ScalarType_BYTES:
			if str, ok := jsonValue.(string); ok {
				return &schema_pb.Value{
					Kind: &schema_pb.Value_BytesValue{BytesValue: []byte(str)},
				}, nil
			}
		}
	}

	return nil, fmt.Errorf("incompatible JSON value type %T for schema type %v", jsonValue, fieldType)
}

// ConvertToSQLResult converts HybridScanResults to SQL query results
func (hms *HybridMessageScanner) ConvertToSQLResult(results []HybridScanResult, columns []string) *QueryResult {
	if len(results) == 0 {
		return &QueryResult{
			Columns: columns,
			Rows:    [][]sqltypes.Value{},
		}
	}

	// Determine columns if not specified
	if len(columns) == 0 {
		columnSet := make(map[string]bool)
		for _, result := range results {
			for columnName := range result.Values {
				columnSet[columnName] = true
			}
		}

		columns = make([]string, 0, len(columnSet))
		for columnName := range columnSet {
			columns = append(columns, columnName)
		}
	}

	// Convert to SQL rows
	rows := make([][]sqltypes.Value, len(results))
	for i, result := range results {
		row := make([]sqltypes.Value, len(columns))
		for j, columnName := range columns {
			switch columnName {
			case "_source":
				row[j] = sqltypes.NewVarChar(result.Source)
			case "_timestamp_ns":
				row[j] = sqltypes.NewInt64(result.Timestamp)
			case "_key":
				row[j] = sqltypes.NewVarBinary(string(result.Key))
			default:
				if value, exists := result.Values[columnName]; exists {
					row[j] = convertSchemaValueToSQL(value)
				} else {
					row[j] = sqltypes.NULL
				}
			}
		}
		rows[i] = row
	}

	return &QueryResult{
		Columns: columns,
		Rows:    rows,
	}
}

// generateSampleHybridData creates sample data that simulates both live and archived messages
func (hms *HybridMessageScanner) generateSampleHybridData(options HybridScanOptions) []HybridScanResult {
	now := time.Now().UnixNano()

	sampleData := []HybridScanResult{
		// Simulated live log data (recent)
		{
			Values: map[string]*schema_pb.Value{
				"user_id":    {Kind: &schema_pb.Value_Int32Value{Int32Value: 1003}},
				"event_type": {Kind: &schema_pb.Value_StringValue{StringValue: "live_login"}},
				"data":       {Kind: &schema_pb.Value_StringValue{StringValue: `{"ip": "10.0.0.1", "live": true}`}},
			},
			Timestamp: now - 300000000000, // 5 minutes ago
			Key:       []byte("live-user-1003"),
			Source:    "live_log",
		},
		{
			Values: map[string]*schema_pb.Value{
				"user_id":    {Kind: &schema_pb.Value_Int32Value{Int32Value: 1004}},
				"event_type": {Kind: &schema_pb.Value_StringValue{StringValue: "live_action"}},
				"data":       {Kind: &schema_pb.Value_StringValue{StringValue: `{"action": "click", "live": true}`}},
			},
			Timestamp: now - 120000000000, // 2 minutes ago
			Key:       []byte("live-user-1004"),
			Source:    "live_log",
		},

		// Simulated archived Parquet data (older)
		{
			Values: map[string]*schema_pb.Value{
				"user_id":    {Kind: &schema_pb.Value_Int32Value{Int32Value: 1001}},
				"event_type": {Kind: &schema_pb.Value_StringValue{StringValue: "archived_login"}},
				"data":       {Kind: &schema_pb.Value_StringValue{StringValue: `{"ip": "192.168.1.1", "archived": true}`}},
			},
			Timestamp: now - 3600000000000, // 1 hour ago
			Key:       []byte("archived-user-1001"),
			Source:    "parquet_archive",
		},
		{
			Values: map[string]*schema_pb.Value{
				"user_id":    {Kind: &schema_pb.Value_Int32Value{Int32Value: 1002}},
				"event_type": {Kind: &schema_pb.Value_StringValue{StringValue: "archived_logout"}},
				"data":       {Kind: &schema_pb.Value_StringValue{StringValue: `{"duration": 1800, "archived": true}`}},
			},
			Timestamp: now - 1800000000000, // 30 minutes ago
			Key:       []byte("archived-user-1002"),
			Source:    "parquet_archive",
		},
	}

	// Apply predicate filtering if specified
	if options.Predicate != nil {
		var filtered []HybridScanResult
		for _, result := range sampleData {
			// Convert to RecordValue for predicate testing
			recordValue := &schema_pb.RecordValue{Fields: make(map[string]*schema_pb.Value)}
			for k, v := range result.Values {
				recordValue.Fields[k] = v
			}
			recordValue.Fields[SW_COLUMN_NAME_TS] = &schema_pb.Value{Kind: &schema_pb.Value_Int64Value{Int64Value: result.Timestamp}}
			recordValue.Fields[SW_COLUMN_NAME_KEY] = &schema_pb.Value{Kind: &schema_pb.Value_BytesValue{BytesValue: result.Key}}

			if options.Predicate(recordValue) {
				filtered = append(filtered, result)
			}
		}
		sampleData = filtered
	}

	// Apply limit
	if options.Limit > 0 && len(sampleData) > options.Limit {
		sampleData = sampleData[:options.Limit]
	}

	return sampleData
}

// ReadParquetStatistics efficiently reads column statistics from parquet files
// without scanning the full file content - uses parquet's built-in metadata
func (h *HybridMessageScanner) ReadParquetStatistics(partitionPath string) ([]*ParquetFileStats, error) {
	var fileStats []*ParquetFileStats

	// Use the same chunk cache as the logstore package
	chunkCache := chunk_cache.NewChunkCacheInMemory(256)
	lookupFileIdFn := filer.LookupFn(h.filerClient)

	err := filer_pb.ReadDirAllEntries(context.Background(), h.filerClient, util.FullPath(partitionPath), "", func(entry *filer_pb.Entry, isLast bool) error {
		// Only process parquet files
		if entry.IsDirectory || !strings.HasSuffix(entry.Name, ".parquet") {
			return nil
		}

		// Extract statistics from this parquet file
		stats, err := h.extractParquetFileStats(entry, lookupFileIdFn, chunkCache)
		if err != nil {
			// Log error but continue processing other files
			fmt.Printf("Warning: failed to extract stats from %s: %v\n", entry.Name, err)
			return nil
		}

		if stats != nil {
			fileStats = append(fileStats, stats)
		}
		return nil
	})

	return fileStats, err
}

// extractParquetFileStats extracts column statistics from a single parquet file
func (h *HybridMessageScanner) extractParquetFileStats(entry *filer_pb.Entry, lookupFileIdFn wdclient.LookupFileIdFunctionType, chunkCache *chunk_cache.ChunkCacheInMemory) (*ParquetFileStats, error) {
	// Create reader for the parquet file
	fileSize := filer.FileSize(entry)
	visibleIntervals, _ := filer.NonOverlappingVisibleIntervals(context.Background(), lookupFileIdFn, entry.Chunks, 0, int64(fileSize))
	chunkViews := filer.ViewFromVisibleIntervals(visibleIntervals, 0, int64(fileSize))
	readerCache := filer.NewReaderCache(32, chunkCache, lookupFileIdFn)
	readerAt := filer.NewChunkReaderAtFromClient(context.Background(), readerCache, chunkViews, int64(fileSize))

	// Create parquet reader - this only reads metadata, not data
	parquetReader := parquet.NewReader(readerAt)
	defer parquetReader.Close()

	fileView := parquetReader.File()

	fileStats := &ParquetFileStats{
		FileName:    entry.Name,
		RowCount:    fileView.NumRows(),
		ColumnStats: make(map[string]*ParquetColumnStats),
	}

	// Get schema information
	schema := fileView.Schema()

	// Process each row group
	rowGroups := fileView.RowGroups()
	for _, rowGroup := range rowGroups {
		columnChunks := rowGroup.ColumnChunks()

		// Process each column chunk
		for i, chunk := range columnChunks {
			// Get column name from schema
			columnName := h.getColumnNameFromSchema(schema, i)
			if columnName == "" {
				continue
			}

			// Try to get column statistics
			columnIndex, err := chunk.ColumnIndex()
			if err != nil {
				// No column index available - skip this column
				continue
			}

			// Extract min/max values from the first page (for simplicity)
			// In a more sophisticated implementation, we could aggregate across all pages
			numPages := columnIndex.NumPages()
			if numPages == 0 {
				continue
			}

			minParquetValue := columnIndex.MinValue(0)
			maxParquetValue := columnIndex.MaxValue(numPages - 1)
			nullCount := int64(0)

			// Aggregate null counts across all pages
			for pageIdx := 0; pageIdx < numPages; pageIdx++ {
				nullCount += columnIndex.NullCount(pageIdx)
			}

			// Convert parquet values to schema_pb.Value
			minValue, err := h.convertParquetValueToSchemaValue(minParquetValue)
			if err != nil {
				continue
			}

			maxValue, err := h.convertParquetValueToSchemaValue(maxParquetValue)
			if err != nil {
				continue
			}

			// Store column statistics (aggregate across row groups if column already exists)
			if existingStats, exists := fileStats.ColumnStats[columnName]; exists {
				// Update existing statistics
				if h.compareSchemaValues(minValue, existingStats.MinValue) < 0 {
					existingStats.MinValue = minValue
				}
				if h.compareSchemaValues(maxValue, existingStats.MaxValue) > 0 {
					existingStats.MaxValue = maxValue
				}
				existingStats.NullCount += nullCount
			} else {
				// Create new column statistics
				fileStats.ColumnStats[columnName] = &ParquetColumnStats{
					ColumnName: columnName,
					MinValue:   minValue,
					MaxValue:   maxValue,
					NullCount:  nullCount,
					RowCount:   rowGroup.NumRows(),
				}
			}
		}
	}

	return fileStats, nil
}

// getColumnNameFromSchema extracts column name from parquet schema by index
func (h *HybridMessageScanner) getColumnNameFromSchema(schema *parquet.Schema, columnIndex int) string {
	// Get the leaf columns in order
	var columnNames []string
	h.collectColumnNames(schema.Fields(), &columnNames)

	if columnIndex >= 0 && columnIndex < len(columnNames) {
		return columnNames[columnIndex]
	}
	return ""
}

// collectColumnNames recursively collects leaf column names from schema
func (h *HybridMessageScanner) collectColumnNames(fields []parquet.Field, names *[]string) {
	for _, field := range fields {
		if len(field.Fields()) == 0 {
			// This is a leaf field (no sub-fields)
			*names = append(*names, field.Name())
		} else {
			// This is a group - recurse
			h.collectColumnNames(field.Fields(), names)
		}
	}
}

// convertParquetValueToSchemaValue converts parquet.Value to schema_pb.Value
func (h *HybridMessageScanner) convertParquetValueToSchemaValue(pv parquet.Value) (*schema_pb.Value, error) {
	switch pv.Kind() {
	case parquet.Boolean:
		return &schema_pb.Value{Kind: &schema_pb.Value_BoolValue{BoolValue: pv.Boolean()}}, nil
	case parquet.Int32:
		return &schema_pb.Value{Kind: &schema_pb.Value_Int32Value{Int32Value: pv.Int32()}}, nil
	case parquet.Int64:
		return &schema_pb.Value{Kind: &schema_pb.Value_Int64Value{Int64Value: pv.Int64()}}, nil
	case parquet.Float:
		return &schema_pb.Value{Kind: &schema_pb.Value_FloatValue{FloatValue: pv.Float()}}, nil
	case parquet.Double:
		return &schema_pb.Value{Kind: &schema_pb.Value_DoubleValue{DoubleValue: pv.Double()}}, nil
	case parquet.ByteArray:
		return &schema_pb.Value{Kind: &schema_pb.Value_BytesValue{BytesValue: pv.ByteArray()}}, nil
	default:
		return nil, fmt.Errorf("unsupported parquet value kind: %v", pv.Kind())
	}
}

// compareSchemaValues compares two schema_pb.Value objects
func (h *HybridMessageScanner) compareSchemaValues(v1, v2 *schema_pb.Value) int {
	if v1 == nil && v2 == nil {
		return 0
	}
	if v1 == nil {
		return -1
	}
	if v2 == nil {
		return 1
	}

	// Extract raw values and compare
	raw1 := h.extractRawValueFromSchema(v1)
	raw2 := h.extractRawValueFromSchema(v2)

	return h.compareRawValues(raw1, raw2)
}

// extractRawValueFromSchema extracts the raw value from schema_pb.Value
func (h *HybridMessageScanner) extractRawValueFromSchema(value *schema_pb.Value) interface{} {
	switch v := value.Kind.(type) {
	case *schema_pb.Value_BoolValue:
		return v.BoolValue
	case *schema_pb.Value_Int32Value:
		return v.Int32Value
	case *schema_pb.Value_Int64Value:
		return v.Int64Value
	case *schema_pb.Value_FloatValue:
		return v.FloatValue
	case *schema_pb.Value_DoubleValue:
		return v.DoubleValue
	case *schema_pb.Value_BytesValue:
		return string(v.BytesValue) // Convert to string for comparison
	case *schema_pb.Value_StringValue:
		return v.StringValue
	}
	return nil
}

// compareRawValues compares two raw values
func (h *HybridMessageScanner) compareRawValues(v1, v2 interface{}) int {
	// Handle nil cases
	if v1 == nil && v2 == nil {
		return 0
	}
	if v1 == nil {
		return -1
	}
	if v2 == nil {
		return 1
	}

	// Compare based on type
	switch val1 := v1.(type) {
	case bool:
		if val2, ok := v2.(bool); ok {
			if val1 == val2 {
				return 0
			}
			if val1 {
				return 1
			}
			return -1
		}
	case int32:
		if val2, ok := v2.(int32); ok {
			if val1 < val2 {
				return -1
			} else if val1 > val2 {
				return 1
			}
			return 0
		}
	case int64:
		if val2, ok := v2.(int64); ok {
			if val1 < val2 {
				return -1
			} else if val1 > val2 {
				return 1
			}
			return 0
		}
	case float32:
		if val2, ok := v2.(float32); ok {
			if val1 < val2 {
				return -1
			} else if val1 > val2 {
				return 1
			}
			return 0
		}
	case float64:
		if val2, ok := v2.(float64); ok {
			if val1 < val2 {
				return -1
			} else if val1 > val2 {
				return 1
			}
			return 0
		}
	case string:
		if val2, ok := v2.(string); ok {
			if val1 < val2 {
				return -1
			} else if val1 > val2 {
				return 1
			}
			return 0
		}
	}

	// Default: try string comparison
	str1 := fmt.Sprintf("%v", v1)
	str2 := fmt.Sprintf("%v", v2)
	if str1 < str2 {
		return -1
	} else if str1 > str2 {
		return 1
	}
	return 0
}