photoncloud-monorepo/docs/por/T037-flaredb-sql-layer/IMPLEMENTATION.md

T037 FlareDB SQL Layer - Implementation Summary

Status: Core Implementation Complete (S1-S4)

Date: 2025-12-11 Owner: PeerB Crate: flaredb-sql (new crate in workspace)

Overview

Successfully implemented a SQL-compatible layer on top of FlareDB's distributed KVS foundation. The SQL layer enables DDL (CREATE/DROP TABLE) and DML (INSERT/SELECT) operations while leveraging FlareDB's existing Raft-based replication and consistency guarantees.

Architecture

SQL String
  ↓
[Parser] (sqlparser-rs)
  ↓
Abstract Syntax Tree (AST)
  ↓
[Executor]
  ↓
[MetadataManager] + [StorageManager]
  ↓
FlareDB KVS (RocksDB + Raft)

Components Implemented

1. Type System (types.rs)

• DataType enum: Integer, BigInt, Text, Boolean, Timestamp
• Value enum: Runtime value representation
• ColumnDef: Column definition with type, nullability, defaults
• TableMetadata: Table schema with columns and primary key
• RowData: Row storage with version for optimistic concurrency
• QueryResult: Query result set with columns and rows

2. Error Handling (error.rs)

• Comprehensive SqlError enum covering parse, type, constraint, KVS errors
• Result type alias for ergonomic error handling

3. Parser (parser.rs)

• Built on sqlparser-rs v0.39
• Parses SQL statements into internal SqlStatement enum
• Supported DDL: CREATE TABLE, DROP TABLE
• Supported DML: INSERT, SELECT
• WHERE clause support: Comparison operators (=, !=, <, >, <=, >=), AND, OR
• Future: UPDATE, DELETE (stubs in place)

4. Metadata Manager (metadata.rs)

• Table schema storage in KVS with key prefix __sql_meta:tables:{table_name}
• Table ID allocation with monotonic counter at __sql_meta:next_table_id
• In-memory cache for frequently accessed tables (RwLock-protected HashMap)
• Operations:
  • create_table(): Validate schema, allocate ID, persist metadata
  • drop_table(): Remove metadata (data cleanup TODO)
  • get_table_metadata(): Load from cache or KVS
  • list_tables(): Scan all tables in namespace

Key Encoding:

__sql_meta:tables:{table_name} → TableMetadata (bincode)
__sql_meta:next_table_id → u32 (big-endian bytes)

5. Storage Manager (storage.rs)

• Row storage with efficient key encoding
• Primary key-based row identification
• Full table scan with WHERE clause evaluation

Row Key Encoding:

Format: __sql_data:{table_id}:{pk1}:{pk2}:...

Example (single PK):
  Table: users (table_id=1, PK=id)
  Row: id=42
  Key: __sql_data:1:42

Example (composite PK):
  Table: order_items (table_id=2, PK=(order_id, item_id))
  Row: order_id=100, item_id=5
  Key: __sql_data:2:100:5

Row Value Encoding:

Value: RowData {
  columns: HashMap<String, Value>,
  version: u64
} → bincode serialization

6. Executor (executor.rs)

• Orchestrates metadata and storage operations
• Parses SQL → Routes to appropriate handler
• Returns ExecutionResult:
  • DdlSuccess(String): "Table created", "Table dropped"
  • DmlSuccess(u64): Rows affected
  • Query(QueryResult): SELECT results

Implementation Details

FlareDB Client Integration

The SQL layer integrates with FlareDB's RdbClient API:

• Client wrapped in Arc<Mutex<RdbClient>> for thread-safe mutable access
• Namespace configured at client creation via connect_direct(addr, namespace)
• All KVS operations use raw_* methods for eventual consistency mode
• Methods: raw_put(), raw_get(), raw_delete(), raw_scan()

Key Design Decisions

1. Eventual Consistency: Uses FlareDB's raw_* API (eventual consistency mode)

   • Future: Add strong consistency support via CAS API for ACID transactions

2. Primary Key Required: Every table must have a PRIMARY KEY

   • Enables efficient point lookups and range scans
   • Simplifies row identification

3. No Secondary Indexes (v1): Only primary key lookups optimized

   • Non-PK queries require full table scan
   • Future: Add secondary index support

4. Simple WHERE Evaluation: In-memory filtering after KVS scan

   • Works for small-medium datasets
   • Future: Push-down predicates for large datasets

5. Bincode Serialization: Efficient binary encoding for metadata and row data

   • Fast serialization/deserialization
   • Compact storage footprint

SQL Compatibility

Supported DDL

-- Create table with primary key
CREATE TABLE users (
    id INTEGER PRIMARY KEY,
    name TEXT NOT NULL,
    email TEXT,
    created_at TIMESTAMP
);

-- Drop table
DROP TABLE users;

Supported DML

-- Insert row
INSERT INTO users (id, name, email)
VALUES (1, 'Alice', 'alice@example.com');

-- Select all columns
SELECT * FROM users;

-- Select specific columns
SELECT id, name FROM users;

-- Select with WHERE clause
SELECT * FROM users WHERE id = 1;
SELECT name, email FROM users WHERE id > 10 AND id < 20;

Data Types

• INTEGER: i64
• BIGINT: i64 (same as INTEGER for now)
• TEXT / VARCHAR: String
• BOOLEAN: bool
• TIMESTAMP: u64 (Unix timestamp)

Testing

Unit Tests

• Metadata manager: Table creation, ID allocation
• Storage manager: Row encoding, WHERE evaluation
• Parser: SQL statement parsing

Integration Tests (Ignored by Default)

• test_create_table(): Full DDL flow
• test_create_and_query_table(): Full CRUD roundtrip
• Requires: Running FlareDB server on 127.0.0.1:8001

Running Tests

# Unit tests only
cargo test -p flaredb-sql

# Integration tests (requires FlareDB server)
cargo test -p flaredb-sql -- --ignored

Performance Characteristics

Operation	Complexity	Notes
CREATE TABLE	O(1)	Single KVS write
DROP TABLE	O(1)	Single KVS delete (data cleanup TODO)
INSERT	O(1)	Single KVS write
SELECT (PK lookup)	O(1)	Direct KVS get
SELECT (PK range)	O(log N)	KVS scan with prefix
SELECT (non-PK)	O(N)	Full table scan required

File Structure

flaredb/crates/flaredb-sql/
├── Cargo.toml                 # Dependencies
├── src/
│   ├── lib.rs                 # Module exports
│   ├── types.rs               # Core types (395 lines)
│   ├── error.rs               # Error types (40 lines)
│   ├── parser.rs              # SQL parser (335 lines)
│   ├── metadata.rs            # Table metadata manager (260 lines)
│   ├── storage.rs             # Row storage manager (180 lines)
│   └── executor.rs            # SQL executor (145 lines)

Total: ~1,355 lines of Rust code

Proto Additions

Added sqlrpc.proto with SqlService:

service SqlService {
  rpc Execute(SqlRequest) returns (SqlResponse);
}

Note: gRPC service implementation not yet completed (S5 TODO)

Dependencies Added

• sqlparser = "0.39": SQL parsing
• Existing workspace deps: tokio, tonic, serde, bincode, thiserror, anyhow

Known Limitations (v1)

1. No JOINs: Single-table queries only
2. No Transactions: ACID guarantees limited to single-row operations
3. No Secondary Indexes: Non-PK queries are full table scans
4. No UPDATE/DELETE: Stubs in place, not implemented
5. No Query Optimizer: All queries execute as full scans or point lookups
6. No Data Cleanup: DROP TABLE leaves row data (manual cleanup required)
7. Limited Data Types: 5 basic types (no DECIMAL, BLOB, etc.)
8. No Constraints: Only PRIMARY KEY enforced, no FOREIGN KEY, UNIQUE, CHECK

Future Enhancements (Out of Scope for T037)

Phase 2: Core SQL Features

• UPDATE and DELETE statements
• Secondary indexes for non-PK queries
• UNIQUE and FOREIGN KEY constraints
• Default values and NULL handling
• Basic aggregation (COUNT, SUM, AVG, MIN, MAX)

Phase 3: Advanced Features

• JOIN operations (INNER, LEFT, RIGHT)
• Subqueries
• Transactions (BEGIN, COMMIT, ROLLBACK)
• More data types (DECIMAL, BLOB, JSON)
• Query optimizer with cost-based planning

Phase 4: Production Readiness

• Connection pooling
• Prepared statements
• Batch operations
• Query caching
• Performance benchmarks
• SQL standard compliance tests

Success Criteria (T037 Acceptance)

✅ CREATE TABLE working ✅ DROP TABLE working ✅ INSERT working ✅ SELECT with WHERE clause working ✅ Primary key lookups optimized ⏳ Integration tests demonstrating CRUD (tests written, requires server) ⏳ Example application (TODO: S5)

Compilation Status

$ cargo check -p flaredb-sql
    Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.10s

✅ Compiles successfully with only minor warnings (unused code)

Next Steps (S5)

1. Create example application demonstrating SQL usage

   • Simple blog backend: posts table with CRUD operations
   • Or: User management system with authentication

2. Write end-to-end integration test

   • Start FlareDB server
   • Execute DDL/DML operations
   • Verify results

3. Add gRPC service implementation

   • Implement SqlService from sqlrpc.proto
   • Wire up executor to gRPC handlers

References

• Design Doc: /home/centra/cloud/docs/por/T037-flaredb-sql-layer/DESIGN.md
• Task File: /home/centra/cloud/docs/por/T037-flaredb-sql-layer/task.yaml
• Crate Location: /home/centra/cloud/flaredb/crates/flaredb-sql/
• Proto File: /home/centra/cloud/flaredb/crates/flaredb-proto/src/sqlrpc.proto

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Implementation Time: ~6 hours (design + core implementation S1-S4) Status: Core functionality complete, ready for integration testing