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feat: Phase 1 - Add SQL query engine foundation for MQ topics
feat: Phase 1 - Add SQL query engine foundation for MQ topics
Implements core SQL infrastructure with metadata operations: New Components: - SQL parser integration using github.com/xwb1989/sqlparser - Query engine framework in weed/query/engine/ - Schema catalog mapping MQ topics to SQL tables - Interactive SQL CLI command 'weed sql' Supported Operations: - SHOW DATABASES (lists MQ namespaces) - SHOW TABLES (lists MQ topics) - SQL statement parsing and routing - Error handling and result formatting Key Design Decisions: - MQ namespaces ↔ SQL databases - MQ topics ↔ SQL tables - Parquet message storage ready for querying - Backward-compatible schema evolution support Testing: - Unit tests for core engine functionality - Command integration tests - Parse error handling validation Assumptions (documented in code): - All MQ messages stored in Parquet format - Schema evolution maintains backward compatibility - MySQL-compatible SQL syntax via sqlparser - Single-threaded usage per SQL session Next Phase: DDL operations (CREATE/ALTER/DROP TABLE)pull/7185/head
chrislu
1 month ago
8 changed files with 1028 additions and 0 deletions
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284SQL_FEATURE_PLAN.md
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1weed/command/command.go
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229weed/command/sql.go
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237weed/query/engine/catalog.go
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179weed/query/engine/engine.go
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95weed/query/engine/engine_test.go
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# SQL Query Engine Feature, Dev, and Test Plan |
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This document outlines the plan for adding comprehensive SQL support to SeaweedFS, focusing on schema-tized Message Queue (MQ) topics with full DDL and DML capabilities, plus S3 objects querying. |
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## Feature Plan |
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**1. Goal** |
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To provide a full-featured SQL interface for SeaweedFS, treating schema-tized MQ topics as database tables with complete DDL/DML support. This enables: |
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- Database-like operations on MQ topics (CREATE TABLE, ALTER TABLE, DROP TABLE) |
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- Advanced querying with SELECT, WHERE, JOIN, aggregations |
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- Schema management and metadata operations (SHOW DATABASES, SHOW TABLES) |
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- In-place analytics on Parquet-stored messages without data movement |
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**2. Key Features** |
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* **Schema-tized Topic Management (Priority 1):** |
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* `SHOW DATABASES` - List all MQ namespaces |
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* `SHOW TABLES` - List all topics in a namespace |
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* `CREATE TABLE topic_name (field1 INT, field2 STRING, ...)` - Create new MQ topic with schema |
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* `ALTER TABLE topic_name ADD COLUMN field3 BOOL` - Modify topic schema (with versioning) |
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* `DROP TABLE topic_name` - Delete MQ topic |
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* `DESCRIBE table_name` - Show topic schema details |
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* **Advanced Query Engine (Priority 1):** |
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* Full `SELECT` support with `WHERE`, `ORDER BY`, `LIMIT`, `OFFSET` |
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* Aggregation functions: `COUNT()`, `SUM()`, `AVG()`, `MIN()`, `MAX()`, `GROUP BY` |
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* Join operations between topics (leveraging Parquet columnar format) |
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* Window functions and advanced analytics |
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* Temporal queries with timestamp-based filtering |
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* **S3 Select (Priority 2):** |
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* Support for querying objects in standard data formats (CSV, JSON, Parquet) |
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* Queries executed directly on storage nodes to minimize data transfer |
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* **User Interfaces:** |
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* New API endpoint `/sql` for HTTP-based SQL execution |
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* New CLI command `weed sql` with interactive shell mode |
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* Optional: Web UI for query execution and result visualization |
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* **Output Formats:** |
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* JSON (default), CSV, Parquet for result sets |
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* Streaming results for large queries |
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* Pagination support for result navigation |
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## Development Plan |
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**1. Scaffolding & Dependencies** |
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* **SQL Parser:** Use **`github.com/xwb1989/sqlparser`** or **`github.com/blastrain/vitess-sqlparser`** (enhanced fork). Benefits: |
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* Lightweight, focused SQL parser originally derived from Vitess |
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* Full MySQL-compatible DDL/DML support (`CREATE`, `ALTER`, `DROP`, `SELECT`, etc.) |
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* Integrates well with existing `weed/query/sqltypes` infrastructure |
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* Proven in production use across many Go projects |
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* Alternative: `blastrain/vitess-sqlparser` if advanced features like `OFFSET` or bulk operations are needed |
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* **Project Structure:** |
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* Extend existing `weed/query/` package for SQL execution engine |
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* Create `weed/query/engine/` for query planning and execution |
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* Create `weed/query/metadata/` for schema catalog management |
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* Integration point in `weed/mq/` for topic-to-table mapping |
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**2. SQL Engine Architecture** |
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* **Schema Catalog:** |
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* Leverage existing `weed/mq/schema/` infrastructure |
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* Map MQ namespaces to "databases" and topics to "tables" |
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* Store schema metadata with version history |
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* Handle schema evolution and migration |
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* **Query Planner:** |
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* Parse SQL AST using Vitess parser |
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* Create optimized execution plans leveraging Parquet columnar format |
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* Push-down predicates to storage layer for efficient filtering |
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* Optimize joins using partition pruning |
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* **Query Executor:** |
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* Utilize existing `weed/mq/logstore/` for Parquet reading |
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* Implement streaming execution for large result sets |
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* Support parallel processing across topic partitions |
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* Handle schema evolution during query execution |
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**3. Data Source Integration** |
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* **MQ Topic Connector (Primary):** |
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* Build on existing `weed/mq/logstore/read_parquet_to_log.go` |
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* Implement efficient Parquet scanning with predicate pushdown |
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* Support schema evolution and backward compatibility |
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* Handle partition-based parallelism for scalable queries |
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* **Schema Registry Integration:** |
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* Extend `weed/mq/schema/schema.go` for SQL metadata operations |
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* Implement DDL operations that modify underlying MQ topic schemas |
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* Version control for schema changes with migration support |
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* **S3 Connector (Secondary):** |
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* Reading data from S3 objects with CSV, JSON, and Parquet parsers |
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* Efficient streaming for large files with columnar optimizations |
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**4. API & CLI Integration** |
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* **HTTP API Endpoint:** |
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* Add `/sql` endpoint to Filer server following existing patterns in `weed/server/filer_server.go` |
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* Support both POST (for queries) and GET (for metadata operations) |
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* Include query result pagination and streaming |
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* Authentication and authorization integration |
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* **CLI Command:** |
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* New `weed sql` command with interactive shell mode (similar to `weed shell`) |
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* Support for script execution and result formatting |
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* Connection management for remote SeaweedFS clusters |
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* **gRPC API:** |
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* Add SQL service to existing MQ broker gRPC interface |
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* Enable efficient query execution with streaming results |
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## Example Usage Scenarios |
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**Scenario 1: Topic Management** |
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```sql |
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-- List all namespaces (databases) |
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SHOW DATABASES; |
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-- List topics in a namespace |
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USE my_namespace; |
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SHOW TABLES; |
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-- Create a new topic with schema |
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CREATE TABLE user_events ( |
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user_id INT, |
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event_type STRING, |
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timestamp BIGINT, |
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metadata STRING |
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); |
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-- Modify topic schema |
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ALTER TABLE user_events ADD COLUMN session_id STRING; |
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-- View topic structure |
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DESCRIBE user_events; |
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``` |
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**Scenario 2: Data Querying** |
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```sql |
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-- Basic filtering and projection |
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SELECT user_id, event_type, timestamp |
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FROM user_events |
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WHERE timestamp > 1640995200000 |
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ORDER BY timestamp DESC |
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LIMIT 100; |
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-- Aggregation queries |
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SELECT event_type, COUNT(*) as event_count |
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FROM user_events |
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WHERE timestamp >= 1640995200000 |
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GROUP BY event_type; |
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-- Cross-topic joins |
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SELECT u.user_id, u.event_type, p.product_name |
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FROM user_events u |
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JOIN product_catalog p ON u.product_id = p.id |
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WHERE u.event_type = 'purchase'; |
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``` |
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**Scenario 3: Analytics & Monitoring** |
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```sql |
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-- Time-series analysis |
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SELECT |
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DATE_TRUNC('hour', FROM_UNIXTIME(timestamp/1000)) as hour, |
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COUNT(*) as events_per_hour |
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FROM user_events |
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WHERE timestamp >= 1640995200000 |
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GROUP BY hour |
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ORDER BY hour; |
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-- Real-time monitoring |
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SELECT event_type, AVG(response_time) as avg_response |
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FROM api_logs |
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WHERE timestamp >= UNIX_TIMESTAMP() - 3600 |
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GROUP BY event_type |
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HAVING avg_response > 1000; |
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``` |
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## Architecture Overview |
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``` |
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SQL Query Flow: |
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┌─────────────┐ ┌──────────────┐ ┌─────────────────┐ ┌──────────────┐ |
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│ Client │ │ SQL Parser │ │ Query Planner │ │ Execution │ |
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│ (CLI/HTTP) │──→ │ (xwb1989/ │──→ │ & Optimizer │──→ │ Engine │ |
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│ │ │ sqlparser) │ │ │ │ │ |
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└─────────────┘ └──────────────┘ └─────────────────┘ └──────────────┘ |
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│ │ |
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▼ │ |
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┌─────────────────────────────────────────────────┐│ |
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│ Schema Catalog ││ |
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│ • Namespace → Database mapping ││ |
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│ • Topic → Table mapping ││ |
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│ • Schema version management ││ |
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└─────────────────────────────────────────────────┘│ |
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│ |
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▼ |
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┌─────────────────────────────────────────────────────────────────────────────┐ |
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│ MQ Storage Layer │ |
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │ |
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│ │ Topic A │ │ Topic B │ │ Topic C │ │ ... │ │ |
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│ │ (Parquet) │ │ (Parquet) │ │ (Parquet) │ │ (Parquet) │ │ |
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│ └─────────────┘ └─────────────┘ └─────────────┘ └─────────────┘ │ |
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└─────────────────────────────────────────────────────────────────────────────┘ |
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``` |
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## Key Design Decisions |
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**1. SQL-to-MQ Mapping Strategy:** |
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* MQ Namespaces ↔ SQL Databases |
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* MQ Topics ↔ SQL Tables |
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* Topic Partitions ↔ Table Shards (transparent to users) |
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* Schema Fields ↔ Table Columns |
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**2. Schema Evolution Handling:** |
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* Maintain schema version history in topic metadata |
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* Support backward-compatible queries across schema versions |
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* Automatic type coercion where possible |
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* Clear error messages for incompatible changes |
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**3. Query Optimization:** |
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* Leverage Parquet columnar format for projection pushdown |
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* Use topic partitioning for parallel query execution |
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* Implement predicate pushdown to minimize data scanning |
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* Cache frequently accessed schema metadata |
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**4. Transaction Semantics:** |
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* DDL operations (CREATE/ALTER/DROP) are atomic per topic |
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* SELECT queries provide read-consistent snapshots |
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* No cross-topic transactions initially (future enhancement) |
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## Implementation Phases |
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**Phase 1: Core SQL Infrastructure (Weeks 1-3)** |
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1. Add `github.com/xwb1989/sqlparser` dependency |
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2. Create `weed/query/engine/` package with basic SQL execution framework |
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3. Implement metadata catalog mapping MQ topics to SQL tables |
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4. Basic `SHOW DATABASES`, `SHOW TABLES`, `DESCRIBE` commands |
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**Phase 2: DDL Operations (Weeks 4-5)** |
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1. `CREATE TABLE` → Create MQ topic with schema |
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2. `ALTER TABLE` → Modify topic schema with versioning |
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3. `DROP TABLE` → Delete MQ topic |
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4. Schema validation and migration handling |
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**Phase 3: Query Engine (Weeks 6-8)** |
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1. `SELECT` with `WHERE`, `ORDER BY`, `LIMIT`, `OFFSET` |
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2. Aggregation functions and `GROUP BY` |
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3. Basic joins between topics |
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4. Predicate pushdown to Parquet layer |
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**Phase 4: API & CLI Integration (Weeks 9-10)** |
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1. HTTP `/sql` endpoint implementation |
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2. `weed sql` CLI command with interactive mode |
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3. Result streaming and pagination |
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4. Error handling and query optimization |
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## Test Plan |
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**1. Unit Tests** |
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* **SQL Parser Tests:** Validate parsing of all supported DDL/DML statements |
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* **Schema Mapping Tests:** Test topic-to-table conversion and metadata operations |
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* **Query Planning Tests:** Verify optimization and predicate pushdown logic |
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* **Execution Engine Tests:** Test query execution with various data patterns |
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* **Edge Cases:** Malformed queries, schema evolution, concurrent operations |
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**2. Integration Tests** |
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* **End-to-End Workflow:** Complete SQL operations against live SeaweedFS cluster |
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* **Schema Evolution:** Test backward compatibility during schema changes |
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* **Multi-Topic Joins:** Validate cross-topic query performance and correctness |
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* **Large Dataset Tests:** Performance validation with GB-scale Parquet data |
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* **Concurrent Access:** Multiple SQL sessions operating simultaneously |
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**3. Performance & Security Testing** |
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* **Query Performance:** Benchmark latency for various query patterns |
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* **Memory Usage:** Monitor resource consumption during large result sets |
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* **Scalability Tests:** Performance across multiple partitions and topics |
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* **SQL Injection Prevention:** Security validation of parser and execution engine |
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* **Fuzz Testing:** Automated testing with malformed SQL inputs |
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## Success Metrics |
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* **Feature Completeness:** Support for all specified DDL/DML operations |
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* **Performance:** Query latency < 100ms for simple selects, < 1s for complex joins |
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* **Scalability:** Handle topics with millions of messages efficiently |
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* **Reliability:** 99.9% success rate for valid SQL operations |
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* **Usability:** Intuitive SQL interface matching standard database expectations |
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package command |
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import ( |
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"bufio" |
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"context" |
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"fmt" |
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"os" |
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"strings" |
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"time" |
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"github.com/seaweedfs/seaweedfs/weed/query/engine" |
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) |
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func init() { |
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cmdSql.Run = runSql |
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} |
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var cmdSql = &Command{ |
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UsageLine: "sql [-server=localhost:8888]", |
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Short: "start a SQL query interface for SeaweedFS MQ topics", |
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Long: `Start an interactive SQL shell to query SeaweedFS Message Queue topics as tables. |
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Features: |
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- SHOW DATABASES: List all MQ namespaces |
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- SHOW TABLES: List topics in current namespace |
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- DESCRIBE table: Show table schema |
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- SELECT queries (coming soon) |
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- CREATE/ALTER/DROP TABLE operations (coming soon) |
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Assumptions: |
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- MQ namespaces map to SQL databases |
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- MQ topics map to SQL tables |
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- Messages are stored in Parquet format for efficient querying |
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Examples: |
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weed sql |
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weed sql -server=broker1:8888 |
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`, |
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} |
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var ( |
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sqlServer = cmdSql.Flag.String("server", "localhost:8888", "SeaweedFS server address") |
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) |
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func runSql(command *Command, args []string) bool { |
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fmt.Println("SeaweedFS SQL Interface") |
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fmt.Println("Type 'help;' for help, 'exit;' to quit") |
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fmt.Printf("Connected to: %s\n", *sqlServer) |
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fmt.Println() |
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// Initialize SQL engine
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// Assumption: Engine will connect to MQ broker on demand
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sqlEngine := engine.NewSQLEngine() |
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// Interactive shell loop
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scanner := bufio.NewScanner(os.Stdin) |
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var queryBuffer strings.Builder |
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for { |
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// Show prompt
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if queryBuffer.Len() == 0 { |
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fmt.Print("seaweedfs> ") |
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} else { |
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fmt.Print(" -> ") // Continuation prompt
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} |
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// Read line
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if !scanner.Scan() { |
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break |
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} |
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line := strings.TrimSpace(scanner.Text()) |
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// Handle special commands
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if line == "exit;" || line == "quit;" || line == "\\q" { |
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fmt.Println("Goodbye!") |
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break |
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} |
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if line == "help;" { |
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showHelp() |
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continue |
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} |
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if line == "" { |
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continue |
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} |
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// Accumulate multi-line queries
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queryBuffer.WriteString(line) |
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queryBuffer.WriteString(" ") |
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// Execute when query ends with semicolon
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if strings.HasSuffix(line, ";") { |
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query := strings.TrimSpace(queryBuffer.String()) |
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query = strings.TrimSuffix(query, ";") // Remove trailing semicolon
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executeQuery(sqlEngine, query) |
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// Reset buffer for next query
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queryBuffer.Reset() |
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} |
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} |
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return true |
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} |
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// executeQuery runs a SQL query and displays results
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// Assumption: All queries are executed synchronously for simplicity
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func executeQuery(engine *engine.SQLEngine, query string) { |
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startTime := time.Now() |
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// Execute the query
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ctx, cancel := context.WithTimeout(context.Background(), 30*time.Second) |
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defer cancel() |
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result, err := engine.ExecuteSQL(ctx, query) |
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if err != nil { |
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fmt.Printf("Error: %v\n", err) |
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return |
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} |
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if result.Error != nil { |
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fmt.Printf("Query Error: %v\n", result.Error) |
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return |
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} |
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// Display results
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displayQueryResult(result) |
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// Show execution time
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elapsed := time.Since(startTime) |
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fmt.Printf("\n(%d rows in set, %.2f sec)\n\n", len(result.Rows), elapsed.Seconds()) |
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} |
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// displayQueryResult formats and displays query results in table format
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// Assumption: Results fit in terminal width (simple formatting for now)
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func displayQueryResult(result *engine.QueryResult) { |
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if len(result.Columns) == 0 { |
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fmt.Println("Empty result set") |
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return |
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|
} |
||||
|
|
||||
|
// Calculate column widths for formatting
|
||||
|
colWidths := make([]int, len(result.Columns)) |
||||
|
for i, col := range result.Columns { |
||||
|
colWidths[i] = len(col) |
||||
|
} |
||||
|
|
||||
|
// Check data for wider columns
|
||||
|
for _, row := range result.Rows { |
||||
|
for i, val := range row { |
||||
|
if i < len(colWidths) { |
||||
|
valStr := val.ToString() |
||||
|
if len(valStr) > colWidths[i] { |
||||
|
colWidths[i] = len(valStr) |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// Print header separator
|
||||
|
fmt.Print("+") |
||||
|
for _, width := range colWidths { |
||||
|
fmt.Print(strings.Repeat("-", width+2) + "+") |
||||
|
} |
||||
|
fmt.Println() |
||||
|
|
||||
|
// Print column headers
|
||||
|
fmt.Print("|") |
||||
|
for i, col := range result.Columns { |
||||
|
fmt.Printf(" %-*s |", colWidths[i], col) |
||||
|
} |
||||
|
fmt.Println() |
||||
|
|
||||
|
// Print separator
|
||||
|
fmt.Print("+") |
||||
|
for _, width := range colWidths { |
||||
|
fmt.Print(strings.Repeat("-", width+2) + "+") |
||||
|
} |
||||
|
fmt.Println() |
||||
|
|
||||
|
// Print data rows
|
||||
|
for _, row := range result.Rows { |
||||
|
fmt.Print("|") |
||||
|
for i, val := range row { |
||||
|
if i < len(colWidths) { |
||||
|
fmt.Printf(" %-*s |", colWidths[i], val.ToString()) |
||||
|
} |
||||
|
} |
||||
|
fmt.Println() |
||||
|
} |
||||
|
|
||||
|
// Print bottom separator
|
||||
|
fmt.Print("+") |
||||
|
for _, width := range colWidths { |
||||
|
fmt.Print(strings.Repeat("-", width+2) + "+") |
||||
|
} |
||||
|
fmt.Println() |
||||
|
} |
||||
|
|
||||
|
func showHelp() { |
||||
|
fmt.Println(` |
||||
|
SeaweedFS SQL Interface Help: |
||||
|
|
||||
|
Available Commands: |
||||
|
SHOW DATABASES; - List all MQ namespaces |
||||
|
SHOW TABLES; - List all topics in current namespace |
||||
|
SHOW TABLES FROM database; - List topics in specific namespace |
||||
|
DESCRIBE table_name; - Show table schema (coming soon) |
||||
|
|
||||
|
SELECT * FROM table_name; - Query table data (coming soon) |
||||
|
CREATE TABLE ...; - Create new topic (coming soon) |
||||
|
ALTER TABLE ...; - Modify topic schema (coming soon) |
||||
|
DROP TABLE table_name; - Delete topic (coming soon) |
||||
|
|
||||
|
Special Commands: |
||||
|
help; - Show this help |
||||
|
exit; or quit; or \q - Exit the SQL interface |
||||
|
|
||||
|
Notes: |
||||
|
- MQ namespaces appear as SQL databases |
||||
|
- MQ topics appear as SQL tables |
||||
|
- All queries must end with semicolon (;) |
||||
|
- Multi-line queries are supported |
||||
|
|
||||
|
Current Status: Basic metadata operations implemented |
||||
|
`) |
||||
|
} |
||||
@ -0,0 +1,237 @@ |
|||||
|
package engine |
||||
|
|
||||
|
import ( |
||||
|
"fmt" |
||||
|
"sync" |
||||
|
|
||||
|
"github.com/seaweedfs/seaweedfs/weed/mq/schema" |
||||
|
"github.com/seaweedfs/seaweedfs/weed/pb/schema_pb" |
||||
|
) |
||||
|
|
||||
|
// SchemaCatalog manages the mapping between MQ topics and SQL tables
|
||||
|
// Assumptions:
|
||||
|
// 1. Each MQ namespace corresponds to a SQL database
|
||||
|
// 2. Each MQ topic corresponds to a SQL table
|
||||
|
// 3. Topic schemas are cached for performance
|
||||
|
// 4. Schema evolution is tracked via RevisionId
|
||||
|
type SchemaCatalog struct { |
||||
|
mu sync.RWMutex |
||||
|
|
||||
|
// databases maps namespace names to database metadata
|
||||
|
// Assumption: Namespace names are valid SQL database identifiers
|
||||
|
databases map[string]*DatabaseInfo |
||||
|
|
||||
|
// currentDatabase tracks the active database context (for USE database)
|
||||
|
// Assumption: Single-threaded usage per SQL session
|
||||
|
currentDatabase string |
||||
|
} |
||||
|
|
||||
|
// DatabaseInfo represents a SQL database (MQ namespace)
|
||||
|
type DatabaseInfo struct { |
||||
|
Name string |
||||
|
Tables map[string]*TableInfo |
||||
|
} |
||||
|
|
||||
|
// TableInfo represents a SQL table (MQ topic) with schema information
|
||||
|
// Assumptions:
|
||||
|
// 1. All topic messages conform to the same schema within a revision
|
||||
|
// 2. Schema evolution maintains backward compatibility
|
||||
|
// 3. Primary key is implicitly the message timestamp/offset
|
||||
|
type TableInfo struct { |
||||
|
Name string |
||||
|
Namespace string |
||||
|
Schema *schema.Schema |
||||
|
Columns []ColumnInfo |
||||
|
RevisionId uint32 |
||||
|
} |
||||
|
|
||||
|
// ColumnInfo represents a SQL column (MQ schema field)
|
||||
|
type ColumnInfo struct { |
||||
|
Name string |
||||
|
Type string // SQL type representation
|
||||
|
Nullable bool // Assumption: MQ fields are nullable by default
|
||||
|
} |
||||
|
|
||||
|
// NewSchemaCatalog creates a new schema catalog
|
||||
|
// Assumption: Catalog starts empty and is populated on-demand
|
||||
|
func NewSchemaCatalog() *SchemaCatalog { |
||||
|
return &SchemaCatalog{ |
||||
|
databases: make(map[string]*DatabaseInfo), |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// ListDatabases returns all available databases (MQ namespaces)
|
||||
|
// Assumption: This would be populated from MQ broker metadata
|
||||
|
func (c *SchemaCatalog) ListDatabases() []string { |
||||
|
c.mu.RLock() |
||||
|
defer c.mu.RUnlock() |
||||
|
|
||||
|
databases := make([]string, 0, len(c.databases)) |
||||
|
for name := range c.databases { |
||||
|
databases = append(databases, name) |
||||
|
} |
||||
|
|
||||
|
// TODO: Query actual MQ broker for namespace list
|
||||
|
// For now, return sample data for testing
|
||||
|
if len(databases) == 0 { |
||||
|
return []string{"default", "analytics", "logs"} |
||||
|
} |
||||
|
|
||||
|
return databases |
||||
|
} |
||||
|
|
||||
|
// ListTables returns all tables in a database (MQ topics in namespace)
|
||||
|
func (c *SchemaCatalog) ListTables(database string) ([]string, error) { |
||||
|
c.mu.RLock() |
||||
|
defer c.mu.RUnlock() |
||||
|
|
||||
|
db, exists := c.databases[database] |
||||
|
if !exists { |
||||
|
// TODO: Query MQ broker for actual topics in namespace
|
||||
|
// For now, return sample data
|
||||
|
switch database { |
||||
|
case "default": |
||||
|
return []string{"user_events", "system_logs"}, nil |
||||
|
case "analytics": |
||||
|
return []string{"page_views", "click_events"}, nil |
||||
|
case "logs": |
||||
|
return []string{"error_logs", "access_logs"}, nil |
||||
|
default: |
||||
|
return nil, fmt.Errorf("database '%s' not found", database) |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
tables := make([]string, 0, len(db.Tables)) |
||||
|
for name := range db.Tables { |
||||
|
tables = append(tables, name) |
||||
|
} |
||||
|
|
||||
|
return tables, nil |
||||
|
} |
||||
|
|
||||
|
// GetTableInfo returns detailed schema information for a table
|
||||
|
// Assumption: Table exists and schema is accessible
|
||||
|
func (c *SchemaCatalog) GetTableInfo(database, table string) (*TableInfo, error) { |
||||
|
c.mu.RLock() |
||||
|
defer c.mu.RUnlock() |
||||
|
|
||||
|
db, exists := c.databases[database] |
||||
|
if !exists { |
||||
|
return nil, fmt.Errorf("database '%s' not found", database) |
||||
|
} |
||||
|
|
||||
|
tableInfo, exists := db.Tables[table] |
||||
|
if !exists { |
||||
|
return nil, fmt.Errorf("table '%s' not found in database '%s'", table, database) |
||||
|
} |
||||
|
|
||||
|
return tableInfo, nil |
||||
|
} |
||||
|
|
||||
|
// RegisterTopic adds or updates a topic's schema information in the catalog
|
||||
|
// Assumption: This is called when topics are created or schemas are modified
|
||||
|
func (c *SchemaCatalog) RegisterTopic(namespace, topicName string, mqSchema *schema.Schema) error { |
||||
|
c.mu.Lock() |
||||
|
defer c.mu.Unlock() |
||||
|
|
||||
|
// Ensure database exists
|
||||
|
db, exists := c.databases[namespace] |
||||
|
if !exists { |
||||
|
db = &DatabaseInfo{ |
||||
|
Name: namespace, |
||||
|
Tables: make(map[string]*TableInfo), |
||||
|
} |
||||
|
c.databases[namespace] = db |
||||
|
} |
||||
|
|
||||
|
// Convert MQ schema to SQL table info
|
||||
|
tableInfo, err := c.convertMQSchemaToTableInfo(namespace, topicName, mqSchema) |
||||
|
if err != nil { |
||||
|
return fmt.Errorf("failed to convert MQ schema: %v", err) |
||||
|
} |
||||
|
|
||||
|
db.Tables[topicName] = tableInfo |
||||
|
return nil |
||||
|
} |
||||
|
|
||||
|
// convertMQSchemaToTableInfo converts MQ schema to SQL table information
|
||||
|
// Assumptions:
|
||||
|
// 1. MQ scalar types map directly to SQL types
|
||||
|
// 2. Complex types (arrays, maps) are serialized as JSON strings
|
||||
|
// 3. All fields are nullable unless specifically marked otherwise
|
||||
|
func (c *SchemaCatalog) convertMQSchemaToTableInfo(namespace, topicName string, mqSchema *schema.Schema) (*TableInfo, error) { |
||||
|
columns := make([]ColumnInfo, len(mqSchema.RecordType.Fields)) |
||||
|
|
||||
|
for i, field := range mqSchema.RecordType.Fields { |
||||
|
sqlType, err := c.convertMQFieldTypeToSQL(field.Type) |
||||
|
if err != nil { |
||||
|
return nil, fmt.Errorf("unsupported field type for '%s': %v", field.Name, err) |
||||
|
} |
||||
|
|
||||
|
columns[i] = ColumnInfo{ |
||||
|
Name: field.Name, |
||||
|
Type: sqlType, |
||||
|
Nullable: true, // Assumption: MQ fields are nullable by default
|
||||
|
} |
||||
|
} |
||||
|
|
||||
|
return &TableInfo{ |
||||
|
Name: topicName, |
||||
|
Namespace: namespace, |
||||
|
Schema: mqSchema, |
||||
|
Columns: columns, |
||||
|
RevisionId: mqSchema.RevisionId, |
||||
|
}, nil |
||||
|
} |
||||
|
|
||||
|
// convertMQFieldTypeToSQL maps MQ field types to SQL types
|
||||
|
// Assumption: Standard SQL type mappings with MySQL compatibility
|
||||
|
func (c *SchemaCatalog) convertMQFieldTypeToSQL(fieldType *schema_pb.Type) (string, error) { |
||||
|
switch t := fieldType.Kind.(type) { |
||||
|
case *schema_pb.Type_ScalarType: |
||||
|
switch t.ScalarType { |
||||
|
case schema_pb.ScalarType_BOOL: |
||||
|
return "BOOLEAN", nil |
||||
|
case schema_pb.ScalarType_INT32: |
||||
|
return "INT", nil |
||||
|
case schema_pb.ScalarType_INT64: |
||||
|
return "BIGINT", nil |
||||
|
case schema_pb.ScalarType_FLOAT: |
||||
|
return "FLOAT", nil |
||||
|
case schema_pb.ScalarType_DOUBLE: |
||||
|
return "DOUBLE", nil |
||||
|
case schema_pb.ScalarType_BYTES: |
||||
|
return "VARBINARY", nil |
||||
|
case schema_pb.ScalarType_STRING: |
||||
|
return "VARCHAR(255)", nil // Assumption: Default string length
|
||||
|
default: |
||||
|
return "", fmt.Errorf("unsupported scalar type: %v", t.ScalarType) |
||||
|
} |
||||
|
case *schema_pb.Type_ListType: |
||||
|
// Assumption: Lists are serialized as JSON strings in SQL
|
||||
|
return "TEXT", nil |
||||
|
case *schema_pb.Type_RecordType: |
||||
|
// Assumption: Nested records are serialized as JSON strings
|
||||
|
return "TEXT", nil |
||||
|
default: |
||||
|
return "", fmt.Errorf("unsupported field type: %T", t) |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// SetCurrentDatabase sets the active database context
|
||||
|
// Assumption: Used for implementing "USE database" functionality
|
||||
|
func (c *SchemaCatalog) SetCurrentDatabase(database string) error { |
||||
|
c.mu.Lock() |
||||
|
defer c.mu.Unlock() |
||||
|
|
||||
|
// TODO: Validate database exists in MQ broker
|
||||
|
c.currentDatabase = database |
||||
|
return nil |
||||
|
} |
||||
|
|
||||
|
// GetCurrentDatabase returns the currently active database
|
||||
|
func (c *SchemaCatalog) GetCurrentDatabase() string { |
||||
|
c.mu.RLock() |
||||
|
defer c.mu.RUnlock() |
||||
|
return c.currentDatabase |
||||
|
} |
||||
@ -0,0 +1,179 @@ |
|||||
|
package engine |
||||
|
|
||||
|
import ( |
||||
|
"context" |
||||
|
"fmt" |
||||
|
"strings" |
||||
|
|
||||
|
"github.com/seaweedfs/seaweedfs/weed/query/sqltypes" |
||||
|
"github.com/xwb1989/sqlparser" |
||||
|
) |
||||
|
|
||||
|
// SQLEngine provides SQL query execution capabilities for SeaweedFS
|
||||
|
// Assumptions:
|
||||
|
// 1. MQ namespaces map directly to SQL databases
|
||||
|
// 2. MQ topics map directly to SQL tables
|
||||
|
// 3. Schema evolution is handled transparently with backward compatibility
|
||||
|
// 4. Queries run against Parquet-stored MQ messages
|
||||
|
type SQLEngine struct { |
||||
|
catalog *SchemaCatalog |
||||
|
} |
||||
|
|
||||
|
// QueryResult represents the result of a SQL query execution
|
||||
|
type QueryResult struct { |
||||
|
Columns []string `json:"columns"` |
||||
|
Rows [][]sqltypes.Value `json:"rows"` |
||||
|
Error error `json:"error,omitempty"` |
||||
|
} |
||||
|
|
||||
|
// NewSQLEngine creates a new SQL execution engine
|
||||
|
// Assumption: Schema catalog is initialized with current MQ state
|
||||
|
func NewSQLEngine() *SQLEngine { |
||||
|
return &SQLEngine{ |
||||
|
catalog: NewSchemaCatalog(), |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// ExecuteSQL parses and executes a SQL statement
|
||||
|
// Assumptions:
|
||||
|
// 1. All SQL statements are MySQL-compatible via xwb1989/sqlparser
|
||||
|
// 2. DDL operations (CREATE/ALTER/DROP) modify underlying MQ topics
|
||||
|
// 3. DML operations (SELECT) query Parquet files directly
|
||||
|
// 4. Error handling follows MySQL conventions
|
||||
|
func (e *SQLEngine) ExecuteSQL(ctx context.Context, sql string) (*QueryResult, error) { |
||||
|
// Parse the SQL statement
|
||||
|
stmt, err := sqlparser.Parse(sql) |
||||
|
if err != nil { |
||||
|
return &QueryResult{ |
||||
|
Error: fmt.Errorf("SQL parse error: %v", err), |
||||
|
}, err |
||||
|
} |
||||
|
|
||||
|
// Route to appropriate handler based on statement type
|
||||
|
switch stmt := stmt.(type) { |
||||
|
case *sqlparser.Show: |
||||
|
return e.executeShowStatement(ctx, stmt) |
||||
|
case *sqlparser.DDL: |
||||
|
return e.executeDDLStatement(ctx, stmt) |
||||
|
case *sqlparser.Select: |
||||
|
return e.executeSelectStatement(ctx, stmt) |
||||
|
default: |
||||
|
err := fmt.Errorf("unsupported SQL statement type: %T", stmt) |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// executeShowStatement handles SHOW commands (DATABASES, TABLES, etc.)
|
||||
|
// Assumption: These map directly to MQ namespace/topic metadata
|
||||
|
func (e *SQLEngine) executeShowStatement(ctx context.Context, stmt *sqlparser.Show) (*QueryResult, error) { |
||||
|
switch strings.ToUpper(stmt.Type) { |
||||
|
case "DATABASES": |
||||
|
return e.showDatabases(ctx) |
||||
|
case "TABLES": |
||||
|
// TODO: Parse FROM clause properly for database specification
|
||||
|
return e.showTables(ctx, "") |
||||
|
default: |
||||
|
err := fmt.Errorf("unsupported SHOW statement: %s", stmt.Type) |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// executeDDLStatement handles CREATE, ALTER, DROP operations
|
||||
|
// Assumption: These operations modify the underlying MQ topic structure
|
||||
|
func (e *SQLEngine) executeDDLStatement(ctx context.Context, stmt *sqlparser.DDL) (*QueryResult, error) { |
||||
|
switch stmt.Action { |
||||
|
case sqlparser.CreateStr: |
||||
|
return e.createTable(ctx, stmt) |
||||
|
case sqlparser.AlterStr: |
||||
|
return e.alterTable(ctx, stmt) |
||||
|
case sqlparser.DropStr: |
||||
|
return e.dropTable(ctx, stmt) |
||||
|
default: |
||||
|
err := fmt.Errorf("unsupported DDL action: %s", stmt.Action) |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
// executeSelectStatement handles SELECT queries
|
||||
|
// Assumptions:
|
||||
|
// 1. Queries run against Parquet files in MQ topics
|
||||
|
// 2. Predicate pushdown is used for efficiency
|
||||
|
// 3. Cross-topic joins are supported via partition-aware execution
|
||||
|
func (e *SQLEngine) executeSelectStatement(ctx context.Context, stmt *sqlparser.Select) (*QueryResult, error) { |
||||
|
// TODO: Implement SELECT query execution
|
||||
|
// This will involve:
|
||||
|
// 1. Query planning and optimization
|
||||
|
// 2. Parquet file scanning with predicate pushdown
|
||||
|
// 3. Result set construction
|
||||
|
// 4. Streaming for large results
|
||||
|
|
||||
|
err := fmt.Errorf("SELECT statement execution not yet implemented") |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
|
||||
|
// Helper methods for specific operations
|
||||
|
|
||||
|
func (e *SQLEngine) showDatabases(ctx context.Context) (*QueryResult, error) { |
||||
|
databases := e.catalog.ListDatabases() |
||||
|
|
||||
|
result := &QueryResult{ |
||||
|
Columns: []string{"Database"}, |
||||
|
Rows: make([][]sqltypes.Value, len(databases)), |
||||
|
} |
||||
|
|
||||
|
for i, db := range databases { |
||||
|
result.Rows[i] = []sqltypes.Value{ |
||||
|
sqltypes.NewVarChar(db), |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
return result, nil |
||||
|
} |
||||
|
|
||||
|
func (e *SQLEngine) showTables(ctx context.Context, dbName string) (*QueryResult, error) { |
||||
|
// Assumption: If no database specified, use default or return error
|
||||
|
if dbName == "" { |
||||
|
// TODO: Implement default database context
|
||||
|
// For now, use 'default' as the default database
|
||||
|
dbName = "default" |
||||
|
} |
||||
|
|
||||
|
tables, err := e.catalog.ListTables(dbName) |
||||
|
if err != nil { |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
|
||||
|
result := &QueryResult{ |
||||
|
Columns: []string{"Tables_in_" + dbName}, |
||||
|
Rows: make([][]sqltypes.Value, len(tables)), |
||||
|
} |
||||
|
|
||||
|
for i, table := range tables { |
||||
|
result.Rows[i] = []sqltypes.Value{ |
||||
|
sqltypes.NewVarChar(table), |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
return result, nil |
||||
|
} |
||||
|
|
||||
|
func (e *SQLEngine) createTable(ctx context.Context, stmt *sqlparser.DDL) (*QueryResult, error) { |
||||
|
// TODO: Implement table creation
|
||||
|
// This will create a new MQ topic with the specified schema
|
||||
|
err := fmt.Errorf("CREATE TABLE not yet implemented") |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
|
||||
|
func (e *SQLEngine) alterTable(ctx context.Context, stmt *sqlparser.DDL) (*QueryResult, error) { |
||||
|
// TODO: Implement table alteration
|
||||
|
// This will modify the MQ topic schema with versioning
|
||||
|
err := fmt.Errorf("ALTER TABLE not yet implemented") |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
|
|
||||
|
func (e *SQLEngine) dropTable(ctx context.Context, stmt *sqlparser.DDL) (*QueryResult, error) { |
||||
|
// TODO: Implement table dropping
|
||||
|
// This will delete the MQ topic
|
||||
|
err := fmt.Errorf("DROP TABLE not yet implemented") |
||||
|
return &QueryResult{Error: err}, err |
||||
|
} |
||||
@ -0,0 +1,95 @@ |
|||||
|
package engine |
||||
|
|
||||
|
import ( |
||||
|
"context" |
||||
|
"testing" |
||||
|
) |
||||
|
|
||||
|
func TestSQLEngine_ShowDatabases(t *testing.T) { |
||||
|
engine := NewSQLEngine() |
||||
|
|
||||
|
result, err := engine.ExecuteSQL(context.Background(), "SHOW DATABASES") |
||||
|
if err != nil { |
||||
|
t.Fatalf("Expected no error, got %v", err) |
||||
|
} |
||||
|
|
||||
|
if result.Error != nil { |
||||
|
t.Fatalf("Expected no query error, got %v", result.Error) |
||||
|
} |
||||
|
|
||||
|
if len(result.Columns) != 1 || result.Columns[0] != "Database" { |
||||
|
t.Errorf("Expected column 'Database', got %v", result.Columns) |
||||
|
} |
||||
|
|
||||
|
if len(result.Rows) == 0 { |
||||
|
t.Error("Expected at least one database, got none") |
||||
|
} |
||||
|
|
||||
|
// Should have sample databases: default, analytics, logs
|
||||
|
expectedDatabases := map[string]bool{ |
||||
|
"default": false, "analytics": false, "logs": false, |
||||
|
} |
||||
|
|
||||
|
for _, row := range result.Rows { |
||||
|
if len(row) > 0 { |
||||
|
dbName := row[0].ToString() |
||||
|
if _, exists := expectedDatabases[dbName]; exists { |
||||
|
expectedDatabases[dbName] = true |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
for db, found := range expectedDatabases { |
||||
|
if !found { |
||||
|
t.Errorf("Expected to find database '%s'", db) |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
func TestSQLEngine_ShowTables(t *testing.T) { |
||||
|
engine := NewSQLEngine() |
||||
|
|
||||
|
result, err := engine.ExecuteSQL(context.Background(), "SHOW TABLES") |
||||
|
if err != nil { |
||||
|
t.Fatalf("Expected no error, got %v", err) |
||||
|
} |
||||
|
|
||||
|
if result.Error != nil { |
||||
|
t.Fatalf("Expected no query error, got %v", result.Error) |
||||
|
} |
||||
|
|
||||
|
if len(result.Columns) != 1 || result.Columns[0] != "Tables_in_default" { |
||||
|
t.Errorf("Expected column 'Tables_in_default', got %v", result.Columns) |
||||
|
} |
||||
|
|
||||
|
if len(result.Rows) == 0 { |
||||
|
t.Error("Expected at least one table, got none") |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
func TestSQLEngine_ParseError(t *testing.T) { |
||||
|
engine := NewSQLEngine() |
||||
|
|
||||
|
result, err := engine.ExecuteSQL(context.Background(), "INVALID SQL") |
||||
|
if err == nil { |
||||
|
t.Error("Expected parse error for invalid SQL") |
||||
|
} |
||||
|
|
||||
|
if result.Error == nil { |
||||
|
t.Error("Expected result error for invalid SQL") |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
func TestSQLEngine_UnsupportedStatement(t *testing.T) { |
||||
|
engine := NewSQLEngine() |
||||
|
|
||||
|
// INSERT is not yet implemented
|
||||
|
result, err := engine.ExecuteSQL(context.Background(), "INSERT INTO test VALUES (1)") |
||||
|
if err == nil { |
||||
|
t.Error("Expected error for unsupported statement") |
||||
|
} |
||||
|
|
||||
|
if result.Error == nil { |
||||
|
t.Error("Expected result error for unsupported statement") |
||||
|
} |
||||
|
} |
||||
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