79 lines
2.9 KiB
Markdown
79 lines
2.9 KiB
Markdown
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---
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title: Choose the Right Data Structure
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impact: HIGH
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impactDescription: Optimal memory usage and operation performance
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tags: data-structures, strings, hashes, sets, lists, sorted-sets, json, streams, vector-sets
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description: Choose the Right Data Structure
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alwaysApply: true
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---
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## Choose the Right Data Structure
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Selecting the appropriate Redis data type for your use case is fundamental to performance and memory efficiency.
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| Use Case | Recommended Type | Why |
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|----------|------------------|-----|
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| Simple values, counters | String | Fast, atomic operations |
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| Object with fields | Hash | Memory efficient, partial updates, field-level expiration |
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| Queue, recent items | List | O(1) push/pop at ends |
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| Unique items, membership | Set | O(1) add/remove/check |
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| Rankings, ranges | Sorted Set | Score-based ordering |
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| Nested/hierarchical data | JSON | Path queries, nested structures, geospatial indexing with RQE |
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| Event logs, messaging | Stream | Persistent, consumer groups |
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| Similarity search | Redis Query Engine / RedisVL or Vector Set | RedisVL is best for document retrieval with filters and full-text search; vector sets are simpler native similarity search |
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**Note:** Vector sets are a Redis 8+ capability introduced in Redis 8.0 and documented there as beta. Prefer Redis Query Engine / RedisVL when you need document-oriented retrieval, structured filters, or full-text + vector workflows.
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**Incorrect:** Using strings for everything.
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**Python** (redis-py):
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```python
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# Storing object as JSON string loses atomic field updates
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redis.set("user:1001", json.dumps({"name": "Alice", "email": "alice@example.com"}))
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# To update email, must fetch, parse, modify, and rewrite entire object
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user = json.loads(redis.get("user:1001"))
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user["email"] = "new@example.com"
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redis.set("user:1001", json.dumps(user))
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```
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**Java** (Jedis):
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```java
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// Bad: Storing as delimited string requires manual parsing
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jedis.set("bicycle", "Deimos;Ergonom;Enduro bikes;4972");
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String bike = jedis.get("bicycle");
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String[] fields = bike.split(";");
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String model = fields[0]; // Fragile and error-prone
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```
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**Correct:** Use Hash for objects with fields.
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**Python** (redis-py):
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```python
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# Hash allows atomic field updates
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redis.hset("user:1001", mapping={"name": "Alice", "email": "alice@example.com"})
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# Update single field without touching others
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redis.hset("user:1001", "email", "new@example.com")
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```
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**Java** (Jedis):
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```java
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import java.util.Map;
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import java.util.HashMap;
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// Good: Hash models properties naturally
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Map<String, String> hashFields = new HashMap<>();
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hashFields.put("model", "Deimos");
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hashFields.put("brand", "Ergonom");
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hashFields.put("type", "Enduro bikes");
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hashFields.put("price", "4972");
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jedis.hset("bicycle", hashFields);
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// Read individual field
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String model = jedis.hget("bicycle", "model");
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```
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Reference: [Choosing the Right Data Type](https://redis.io/docs/latest/develop/data-types/compare-data-types/)
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