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Storage Sharding and Data Indexing
Problem this solves: Apps slow down because they lump too much into single large objects.
What you’ll learn:
How to shard storage
Dynamic fields as scalable indexes
Trade-offs of fine vs coarse objects
Step-by-step: Sharding NFT collections
Root Collection object (shared).
Dynamic fields for each NFT.
Retrieval by ID → no scanning large lists.
- NFT Ecosystem
Storage sharding and indexing help avoid bottlenecks by splitting large objects into smaller, more manageable ones. Instead of cramming everything into a single shared object (which forces consensus overhead), you shard storage into multiple objects. For example, in an NFT collection, a **Root Collection** acts as the anchor, while each NFT is stored as its own object via **dynamic fields**. This way, retrieving an NFT by ID is direct and efficient, without scanning a huge list. **Trade-offs:** * **Fine-grained objects** = better scalability, but more objects to manage. * **Coarse-grained objects** = simpler design, but slower as they grow. In practice, sharding ensures apps stay fast even with thousands or millions of entries.
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