Copying Features from Data Warehouse to Redis
In the world of Machine Learning, there are scenarios where we need to move data from one storage system to another. One such use case is copying features from a Warehouse table to a Redis key-value store for low latency access.
Redis is an in-memory data structure store, supporting data structures such as strings, hashes, lists, sets, and sorted sets. It offers high-performance data access with optional durability and is commonly used as a cache, message broker, and task queue.
JSON (JavaScript Object Notation) is a lightweight data-interchange format that is easy to read and write for humans and easy to parse and generate for machines.
First, we need to extract the required data from our Warehouse table. Let’s assume we have a table named device_features with columns device_id as keyand features_json.
Interoperability: Supported by many programming languages.
Structure: Supports structured data with arrays and nested objects.
Extensible: Can easily add new features without affecting existing ones.
Self-Describing: Keys in JSON provide context, making it self-descriptive.
Stateless: Each request from a client to a server contains all the information needed to understand and process the request.
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