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432 lines
15 KiB
Markdown
432 lines
15 KiB
Markdown
---
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name: event-store-design
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description: Design and implement event stores for event-sourced systems. Use when building event sourcing infrastructure, choosing event store technologies, or implementing event persistence patterns.
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---
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# Event Store Design
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Comprehensive guide to designing event stores for event-sourced applications.
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## When to Use This Skill
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- Designing event sourcing infrastructure
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- Choosing between event store technologies
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- Implementing custom event stores
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- Optimizing event storage and retrieval
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- Setting up event store schemas
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- Planning for event store scaling
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## Core Concepts
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### 1. Event Store Architecture
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```
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┌─────────────────────────────────────────────────────┐
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│ Event Store │
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├─────────────────────────────────────────────────────┤
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│ ┌─────────────┐ ┌─────────────┐ ┌─────────────┐ │
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│ │ Stream 1 │ │ Stream 2 │ │ Stream 3 │ │
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│ │ (Aggregate) │ │ (Aggregate) │ │ (Aggregate) │ │
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│ ├─────────────┤ ├─────────────┤ ├─────────────┤ │
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│ │ Event 1 │ │ Event 1 │ │ Event 1 │ │
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│ │ Event 2 │ │ Event 2 │ │ Event 2 │ │
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│ │ Event 3 │ │ ... │ │ Event 3 │ │
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│ │ ... │ │ │ │ Event 4 │ │
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│ └─────────────┘ └─────────────┘ └─────────────┘ │
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├─────────────────────────────────────────────────────┤
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│ Global Position: 1 → 2 → 3 → 4 → 5 → 6 → ... │
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└─────────────────────────────────────────────────────┘
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```
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### 2. Event Store Requirements
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| Requirement | Description |
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| ----------------- | ---------------------------------- |
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| **Append-only** | Events are immutable, only appends |
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| **Ordered** | Per-stream and global ordering |
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| **Versioned** | Optimistic concurrency control |
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| **Subscriptions** | Real-time event notifications |
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| **Idempotent** | Handle duplicate writes safely |
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## Technology Comparison
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| Technology | Best For | Limitations |
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| ---------------- | ------------------------- | -------------------------------- |
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| **EventStoreDB** | Pure event sourcing | Single-purpose |
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| **PostgreSQL** | Existing Postgres stack | Manual implementation |
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| **Kafka** | High-throughput streaming | Not ideal for per-stream queries |
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| **DynamoDB** | Serverless, AWS-native | Query limitations |
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| **Marten** | .NET ecosystems | .NET specific |
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## Templates
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### Template 1: PostgreSQL Event Store Schema
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```sql
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-- Events table
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CREATE TABLE events (
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id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
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stream_id VARCHAR(255) NOT NULL,
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stream_type VARCHAR(255) NOT NULL,
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event_type VARCHAR(255) NOT NULL,
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event_data JSONB NOT NULL,
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metadata JSONB DEFAULT '{}',
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version BIGINT NOT NULL,
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global_position BIGSERIAL,
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created_at TIMESTAMPTZ DEFAULT NOW(),
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CONSTRAINT unique_stream_version UNIQUE (stream_id, version)
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);
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-- Index for stream queries
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CREATE INDEX idx_events_stream_id ON events(stream_id, version);
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-- Index for global subscription
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CREATE INDEX idx_events_global_position ON events(global_position);
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-- Index for event type queries
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CREATE INDEX idx_events_event_type ON events(event_type);
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-- Index for time-based queries
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CREATE INDEX idx_events_created_at ON events(created_at);
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-- Snapshots table
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CREATE TABLE snapshots (
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stream_id VARCHAR(255) PRIMARY KEY,
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stream_type VARCHAR(255) NOT NULL,
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snapshot_data JSONB NOT NULL,
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version BIGINT NOT NULL,
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created_at TIMESTAMPTZ DEFAULT NOW()
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);
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-- Subscriptions checkpoint table
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CREATE TABLE subscription_checkpoints (
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subscription_id VARCHAR(255) PRIMARY KEY,
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last_position BIGINT NOT NULL DEFAULT 0,
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updated_at TIMESTAMPTZ DEFAULT NOW()
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);
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```
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### Template 2: Python Event Store Implementation
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```python
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from dataclasses import dataclass, field
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from datetime import datetime
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from typing import Any, Optional, List
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from uuid import UUID, uuid4
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import json
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import asyncpg
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@dataclass
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class Event:
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stream_id: str
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event_type: str
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data: dict
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metadata: dict = field(default_factory=dict)
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event_id: UUID = field(default_factory=uuid4)
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version: Optional[int] = None
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global_position: Optional[int] = None
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created_at: datetime = field(default_factory=datetime.utcnow)
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class EventStore:
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def __init__(self, pool: asyncpg.Pool):
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self.pool = pool
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async def append_events(
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self,
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stream_id: str,
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stream_type: str,
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events: List[Event],
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expected_version: Optional[int] = None
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) -> List[Event]:
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"""Append events to a stream with optimistic concurrency."""
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async with self.pool.acquire() as conn:
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async with conn.transaction():
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# Check expected version
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if expected_version is not None:
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current = await conn.fetchval(
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"SELECT MAX(version) FROM events WHERE stream_id = $1",
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stream_id
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)
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current = current or 0
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if current != expected_version:
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raise ConcurrencyError(
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f"Expected version {expected_version}, got {current}"
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)
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# Get starting version
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start_version = await conn.fetchval(
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"SELECT COALESCE(MAX(version), 0) + 1 FROM events WHERE stream_id = $1",
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stream_id
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)
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# Insert events
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saved_events = []
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for i, event in enumerate(events):
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event.version = start_version + i
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row = await conn.fetchrow(
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"""
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INSERT INTO events (id, stream_id, stream_type, event_type,
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event_data, metadata, version, created_at)
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VALUES ($1, $2, $3, $4, $5, $6, $7, $8)
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RETURNING global_position
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""",
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event.event_id,
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stream_id,
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stream_type,
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event.event_type,
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json.dumps(event.data),
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json.dumps(event.metadata),
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event.version,
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event.created_at
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)
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event.global_position = row['global_position']
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saved_events.append(event)
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return saved_events
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async def read_stream(
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self,
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stream_id: str,
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from_version: int = 0,
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limit: int = 1000
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) -> List[Event]:
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"""Read events from a stream."""
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async with self.pool.acquire() as conn:
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rows = await conn.fetch(
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"""
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SELECT id, stream_id, event_type, event_data, metadata,
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version, global_position, created_at
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FROM events
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WHERE stream_id = $1 AND version >= $2
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ORDER BY version
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LIMIT $3
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""",
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stream_id, from_version, limit
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)
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return [self._row_to_event(row) for row in rows]
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async def read_all(
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self,
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from_position: int = 0,
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limit: int = 1000
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) -> List[Event]:
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"""Read all events globally."""
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async with self.pool.acquire() as conn:
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rows = await conn.fetch(
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"""
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SELECT id, stream_id, event_type, event_data, metadata,
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version, global_position, created_at
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FROM events
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WHERE global_position > $1
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ORDER BY global_position
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LIMIT $2
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""",
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from_position, limit
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)
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return [self._row_to_event(row) for row in rows]
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async def subscribe(
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self,
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subscription_id: str,
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handler,
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from_position: int = 0,
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batch_size: int = 100
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):
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"""Subscribe to all events from a position."""
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# Get checkpoint
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async with self.pool.acquire() as conn:
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checkpoint = await conn.fetchval(
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"""
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SELECT last_position FROM subscription_checkpoints
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WHERE subscription_id = $1
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""",
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subscription_id
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)
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position = checkpoint or from_position
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while True:
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events = await self.read_all(position, batch_size)
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if not events:
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await asyncio.sleep(1) # Poll interval
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continue
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for event in events:
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await handler(event)
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position = event.global_position
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# Save checkpoint
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async with self.pool.acquire() as conn:
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await conn.execute(
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"""
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INSERT INTO subscription_checkpoints (subscription_id, last_position)
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VALUES ($1, $2)
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ON CONFLICT (subscription_id)
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DO UPDATE SET last_position = $2, updated_at = NOW()
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""",
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subscription_id, position
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)
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def _row_to_event(self, row) -> Event:
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return Event(
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event_id=row['id'],
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stream_id=row['stream_id'],
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event_type=row['event_type'],
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data=json.loads(row['event_data']),
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metadata=json.loads(row['metadata']),
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version=row['version'],
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global_position=row['global_position'],
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created_at=row['created_at']
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)
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class ConcurrencyError(Exception):
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"""Raised when optimistic concurrency check fails."""
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pass
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```
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### Template 3: EventStoreDB Usage
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```python
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from esdbclient import EventStoreDBClient, NewEvent, StreamState
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import json
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# Connect
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client = EventStoreDBClient(uri="esdb://localhost:2113?tls=false")
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# Append events
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def append_events(stream_name: str, events: list, expected_revision=None):
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new_events = [
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NewEvent(
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type=event['type'],
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data=json.dumps(event['data']).encode(),
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metadata=json.dumps(event.get('metadata', {})).encode()
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)
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for event in events
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]
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if expected_revision is None:
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state = StreamState.ANY
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elif expected_revision == -1:
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state = StreamState.NO_STREAM
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else:
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state = expected_revision
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return client.append_to_stream(
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stream_name=stream_name,
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events=new_events,
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current_version=state
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)
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# Read stream
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def read_stream(stream_name: str, from_revision: int = 0):
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events = client.get_stream(
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stream_name=stream_name,
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stream_position=from_revision
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)
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return [
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{
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'type': event.type,
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'data': json.loads(event.data),
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'metadata': json.loads(event.metadata) if event.metadata else {},
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'stream_position': event.stream_position,
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'commit_position': event.commit_position
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}
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for event in events
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]
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# Subscribe to all
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async def subscribe_to_all(handler, from_position: int = 0):
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subscription = client.subscribe_to_all(commit_position=from_position)
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async for event in subscription:
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await handler({
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'type': event.type,
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'data': json.loads(event.data),
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'stream_id': event.stream_name,
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'position': event.commit_position
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})
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# Category projection ($ce-Category)
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def read_category(category: str):
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"""Read all events for a category using system projection."""
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return read_stream(f"$ce-{category}")
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```
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### Template 4: DynamoDB Event Store
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```python
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import boto3
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from boto3.dynamodb.conditions import Key
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from datetime import datetime
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import json
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import uuid
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class DynamoEventStore:
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def __init__(self, table_name: str):
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self.dynamodb = boto3.resource('dynamodb')
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self.table = self.dynamodb.Table(table_name)
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def append_events(self, stream_id: str, events: list, expected_version: int = None):
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"""Append events with conditional write for concurrency."""
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with self.table.batch_writer() as batch:
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for i, event in enumerate(events):
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version = (expected_version or 0) + i + 1
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item = {
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'PK': f"STREAM#{stream_id}",
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'SK': f"VERSION#{version:020d}",
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'GSI1PK': 'EVENTS',
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'GSI1SK': datetime.utcnow().isoformat(),
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'event_id': str(uuid.uuid4()),
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'stream_id': stream_id,
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'event_type': event['type'],
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'event_data': json.dumps(event['data']),
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'version': version,
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'created_at': datetime.utcnow().isoformat()
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}
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batch.put_item(Item=item)
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return events
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def read_stream(self, stream_id: str, from_version: int = 0):
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"""Read events from a stream."""
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response = self.table.query(
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KeyConditionExpression=Key('PK').eq(f"STREAM#{stream_id}") &
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Key('SK').gte(f"VERSION#{from_version:020d}")
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)
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return [
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{
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'event_type': item['event_type'],
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'data': json.loads(item['event_data']),
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'version': item['version']
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}
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for item in response['Items']
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]
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# Table definition (CloudFormation/Terraform)
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"""
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DynamoDB Table:
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- PK (Partition Key): String
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- SK (Sort Key): String
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- GSI1PK, GSI1SK for global ordering
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Capacity: On-demand or provisioned based on throughput needs
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"""
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```
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## Best Practices
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### Do's
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- **Use stream IDs that include aggregate type** - `Order-{uuid}`
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- **Include correlation/causation IDs** - For tracing
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- **Version events from day one** - Plan for schema evolution
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- **Implement idempotency** - Use event IDs for deduplication
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- **Index appropriately** - For your query patterns
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### Don'ts
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- **Don't update or delete events** - They're immutable facts
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- **Don't store large payloads** - Keep events small
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- **Don't skip optimistic concurrency** - Prevents data corruption
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- **Don't ignore backpressure** - Handle slow consumers
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