cqlite-core 0.15.0

//! Comprehensive Schema Discovery and Validation System
//!
//! This module provides advanced schema discovery capabilities that can extract, parse,
//! validate, and export schema information from SSTable files across different Cassandra versions.
//! It supports all complex data types including UDTs, collections, frozen types, and indexes.

mod analysis;
mod exporter;
mod inference;
mod model;
mod validator;

use std::collections::HashMap;
use std::path::PathBuf;
use std::sync::Arc;
use std::time::{Duration, SystemTime};

use tokio::sync::RwLock;

use crate::{
    parser::header::{CassandraVersion, SSTableHeader},
    platform::Platform,
    schema::UdtRegistry,
    types::Value,
    Config, Result,
};

use self::exporter::SchemaExporter;
use self::inference::TypeInferenceEngine;
use self::validator::SchemaValidator;

// Re-export the public data model unchanged.
pub use self::model::{
    CachingOptions, CollectionKind, CollectionType, ColumnDefinition, CompactionStrategy,
    CompressionOptions, ConsistencyResults, DiscoveryMethod, DiscoveryMetrics, FieldConflict,
    IndexDefinition, IndexType, SchemaDiscoveryConfig, SchemaInfo, SchemaMetadata, TableOptions,
    TypeInconsistency, TypeInfo, UDTDefinition, UdtConflict, UdtFieldDefinition, UdtFieldInfo,
    ValidationError, ValidationErrorType, ValidationResults, ValidationStatus, ValidationWarning,
    ValidationWarningType,
};

/// Main schema discovery engine
#[derive(Debug)]
pub struct SchemaDiscoveryEngine {
    /// Configuration
    config: SchemaDiscoveryConfig,
    /// Platform abstraction
    #[allow(dead_code)]
    platform: Arc<Platform>,
    /// Core configuration
    #[allow(dead_code)]
    core_config: Config,
    /// Schema cache
    schema_cache: Arc<RwLock<HashMap<String, (SchemaInfo, SystemTime)>>>,
    /// UDT registry for managing discovered UDTs
    #[allow(dead_code)]
    udt_registry: Arc<RwLock<UdtRegistry>>,
    /// Type inference engine
    #[allow(dead_code)]
    type_inference: Arc<TypeInferenceEngine>,
    /// Schema validator
    #[allow(dead_code)]
    validator: Arc<SchemaValidator>,
    /// Schema exporter
    exporter: Arc<SchemaExporter>,
}

impl SchemaDiscoveryEngine {
    /// Create a new schema discovery engine
    pub async fn new(
        config: SchemaDiscoveryConfig,
        platform: Arc<Platform>,
        core_config: Config,
    ) -> Result<Self> {
        let udt_registry = Arc::new(RwLock::new(UdtRegistry::new()));
        let type_inference = Arc::new(TypeInferenceEngine::new());
        let validator = Arc::new(SchemaValidator::new());
        let exporter = Arc::new(SchemaExporter::new());

        Ok(Self {
            config,
            platform,
            core_config,
            schema_cache: Arc::new(RwLock::new(HashMap::new())),
            udt_registry,
            type_inference,
            validator,
            exporter,
        })
    }

    /// Discover schema from a collection of SSTable files
    pub async fn discover_schema(
        &self,
        keyspace: &str,
        table: &str,
        sstable_files: &[PathBuf],
    ) -> Result<SchemaInfo> {
        let cache_key = format!("{}.{}", keyspace, table);
        let start_time = SystemTime::now();

        // Check cache first
        if self.config.enable_schema_cache {
            if let Some(cached_schema) = self.get_cached_schema(&cache_key).await {
                return Ok(cached_schema);
            }
        }

        // Perform comprehensive schema discovery
        let mut discovery_context = DiscoveryContext::new(keyspace, table, sstable_files);

        // Phase 1: Extract metadata from headers
        self.extract_header_metadata(&mut discovery_context).await?;

        // Phase 2: Sample data for type inference
        self.sample_data_for_inference(&mut discovery_context)
            .await?;

        // Phase 3: Discover UDTs and complex types
        if self.config.enable_udt_discovery {
            self.discover_udts(&mut discovery_context).await?;
        }

        // Phase 4: Analyze collections
        if self.config.enable_collection_analysis {
            self.analyze_collection_types(&mut discovery_context)
                .await?;
        }

        // Phase 5: Discover indexes
        if self.config.enable_index_discovery {
            self.discover_indexes(&mut discovery_context).await?;
        }

        // Phase 6: Infer complete schema
        let schema_info = self.build_schema_info(&mut discovery_context).await?;

        // Phase 7: Schema validation (disabled - unimplemented)
        let validated_schema = schema_info;

        // Calculate discovery metrics
        let discovery_time = start_time.elapsed().unwrap_or(Duration::ZERO);
        let final_schema =
            self.add_performance_metrics(validated_schema, discovery_time, &discovery_context);

        // Cache the result
        if self.config.enable_schema_cache {
            self.cache_schema(cache_key, final_schema.clone()).await;
        }

        Ok(final_schema)
    }

    /// Generate CQL CREATE TABLE statement from schema
    pub async fn generate_cql(&self, schema: &SchemaInfo) -> Result<String> {
        self.exporter.generate_cql(schema).await
    }

    /// Export schema as JSON
    #[cfg(feature = "experimental")]
    pub async fn export_json(&self, schema: &SchemaInfo) -> Result<String> {
        self.exporter.export_json(schema).await
    }

    #[cfg(not(feature = "experimental"))]
    pub async fn export_json(&self, _schema: &SchemaInfo) -> Result<String> {
        Err(crate::error::Error::unsupported_format(
            "JSON export requires experimental feature",
        ))
    }

    /// Export schema as JSON with custom configuration
    #[cfg(feature = "experimental")]
    pub async fn export_json_with_config(
        &self,
        schema: &SchemaInfo,
        config: &crate::schema::json_exporter::JsonExportConfig,
    ) -> Result<String> {
        self.exporter.export_json_with_config(schema, config).await
    }

    #[cfg(not(feature = "experimental"))]
    pub async fn export_json_with_config<T>(
        &self,
        _schema: &SchemaInfo,
        _config: &T,
    ) -> Result<String> {
        Err(crate::error::Error::unsupported_format(
            "JSON export requires experimental feature",
        ))
    }

    /// Generate schema comparison report
    pub async fn compare_schemas(
        &self,
        schema1: &SchemaInfo,
        schema2: &SchemaInfo,
    ) -> Result<String> {
        self.exporter
            .generate_comparison_report(schema1, schema2)
            .await
    }

    // Private implementation methods follow...

    async fn get_cached_schema(&self, cache_key: &str) -> Option<SchemaInfo> {
        let cache = self.schema_cache.read().await;
        if let Some((schema, cached_at)) = cache.get(cache_key) {
            let ttl = Duration::from_secs(self.config.cache_ttl_seconds);
            if cached_at.elapsed().unwrap_or(Duration::MAX) < ttl {
                return Some(schema.clone());
            }
        }
        None
    }

    async fn cache_schema(&self, cache_key: String, schema: SchemaInfo) {
        let mut cache = self.schema_cache.write().await;
        cache.insert(cache_key, (schema, SystemTime::now()));

        // Simple cache eviction
        if cache.len() > 100 {
            let oldest_key = cache
                .iter()
                .min_by_key(|(_, (_, time))| time)
                .map(|(key, _)| key.clone());

            if let Some(key) = oldest_key {
                cache.remove(&key);
            }
        }
    }

    fn add_performance_metrics(
        &self,
        mut schema: SchemaInfo,
        discovery_time: Duration,
        _context: &DiscoveryContext,
    ) -> SchemaInfo {
        schema.metadata.performance_metrics = DiscoveryMetrics {
            total_time_ms: discovery_time.as_millis() as u64,
            header_parsing_time_ms: 0, // TODO: Track individual phase times
            data_sampling_time_ms: 0,
            type_inference_time_ms: 0,
            validation_time_ms: 0,
            peak_memory_usage_bytes: 0, // TODO: Track memory usage
        };
        schema
    }
}

/// Context for schema discovery process
#[derive(Debug)]
struct DiscoveryContext {
    #[allow(dead_code)]
    keyspace: String,
    #[allow(dead_code)]
    table: String,
    #[allow(dead_code)]
    source_files: Vec<PathBuf>,
    #[allow(dead_code)]
    headers: Vec<SSTableHeader>,
    #[allow(dead_code)]
    column_samples: HashMap<String, Vec<Value>>,
    #[allow(dead_code)]
    discovered_udts: HashMap<String, UDTDefinition>,
    #[allow(dead_code)]
    collection_types: HashMap<String, CollectionType>,
    #[allow(dead_code)]
    indexes: Vec<IndexDefinition>,
    #[allow(dead_code)]
    table_options: TableOptions,
    #[allow(dead_code)]
    total_rows_sampled: usize,
    #[allow(dead_code)]
    cassandra_version: Option<CassandraVersion>,
}

impl DiscoveryContext {
    fn new(keyspace: &str, table: &str, files: &[PathBuf]) -> Self {
        Self {
            keyspace: keyspace.to_string(),
            table: table.to_string(),
            source_files: files.to_vec(),
            headers: Vec::new(),
            column_samples: HashMap::new(),
            discovered_udts: HashMap::new(),
            collection_types: HashMap::new(),
            indexes: Vec::new(),
            table_options: TableOptions {
                compaction: None,
                compression: None,
                caching: None,
                bloom_filter_fp_chance: None,
                gc_grace_seconds: None,
                default_time_to_live: None,
                memtable_flush_period_in_ms: None,
                additional_properties: HashMap::new(),
            },
            total_rows_sampled: 0,
            cassandra_version: None,
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[tokio::test]
    async fn test_schema_discovery_engine_creation() {
        let config = SchemaDiscoveryConfig::default();
        let core_config = Config::default();
        let platform = Arc::new(Platform::new(&core_config).await.unwrap());

        let engine = SchemaDiscoveryEngine::new(config, platform, core_config)
            .await
            .unwrap();

        // Test basic functionality
        assert!(engine.schema_cache.read().await.is_empty());
    }

    #[test]
    fn test_discovery_context_creation() {
        let files = vec![PathBuf::from("test.sst")];
        let context = DiscoveryContext::new("test_ks", "test_table", &files);

        assert_eq!(context.keyspace, "test_ks");
        assert_eq!(context.table, "test_table");
        assert_eq!(context.source_files.len(), 1);
    }

    #[test]
    fn test_schema_info_serialization() {
        let schema_info = SchemaInfo {
            keyspace: "test".to_string(),
            table: "users".to_string(),
            partition_key: Vec::new(),
            clustering_keys: Vec::new(),
            regular_columns: Vec::new(),
            static_columns: Vec::new(),
            collection_types: HashMap::new(),
            user_defined_types: Vec::new(),
            indexes: Vec::new(),
            table_options: TableOptions {
                compaction: None,
                compression: None,
                caching: None,
                bloom_filter_fp_chance: None,
                gc_grace_seconds: None,
                default_time_to_live: None,
                memtable_flush_period_in_ms: None,
                additional_properties: HashMap::new(),
            },
            metadata: SchemaMetadata {
                discovered_at: std::time::UNIX_EPOCH,
                source_files: Vec::new(),
                total_rows_sampled: 0,
                cassandra_version: None,
                discovery_method: DiscoveryMethod::HeaderMetadata,
                version: 1,
                validation_results: ValidationResults {
                    status: ValidationStatus::Valid,
                    errors: Vec::new(),
                    warnings: Vec::new(),
                    consistency_results: ConsistencyResults {
                        files_analyzed: 0,
                        schema_mismatches: 0,
                        type_inconsistencies: Vec::new(),
                        udt_conflicts: Vec::new(),
                    },
                },
                performance_metrics: DiscoveryMetrics {
                    total_time_ms: 0,
                    header_parsing_time_ms: 0,
                    data_sampling_time_ms: 0,
                    type_inference_time_ms: 0,
                    validation_time_ms: 0,
                    peak_memory_usage_bytes: 0,
                },
            },
        };

        // Test that it can be serialized and deserialized
        let json = serde_json::to_string(&schema_info).unwrap();
        let deserialized: SchemaInfo = serde_json::from_str(&json).unwrap();
        assert_eq!(deserialized.keyspace, "test");
        assert_eq!(deserialized.table, "users");
    }

    #[tokio::test]
    async fn test_extract_header_metadata_stub() {
        let config = SchemaDiscoveryConfig::default();
        let core_config = Config::default();
        let platform = Arc::new(Platform::new(&core_config).await.unwrap());

        let engine = SchemaDiscoveryEngine::new(config, platform, core_config)
            .await
            .unwrap();

        let mut context = DiscoveryContext::new("test_ks", "test_table", &[]);

        // Test that the stub method executes without panicking
        let result = engine.extract_header_metadata(&mut context).await;
        assert!(
            result.is_ok(),
            "extract_header_metadata stub should return Ok(())"
        );
    }

    #[tokio::test]
    async fn test_sample_data_for_inference_stub() {
        let config = SchemaDiscoveryConfig::default();
        let core_config = Config::default();
        let platform = Arc::new(Platform::new(&core_config).await.unwrap());

        let engine = SchemaDiscoveryEngine::new(config, platform, core_config)
            .await
            .unwrap();

        let mut context = DiscoveryContext::new("test_ks", "test_table", &[]);

        // Test that the stub method executes without panicking
        let result = engine.sample_data_for_inference(&mut context).await;
        assert!(
            result.is_ok(),
            "sample_data_for_inference stub should return Ok(())"
        );
    }
}