RedisKVStore request size

[anirbanbasu]

If the underlying Redis server has restrictions on the request size, such as the Vercel KV store, is there any way to specify the RedisKVStore in Llamaindex to do what Vercel suggests?

You can split your data into smaller chunks and send them in separate commands

Looking at the implementation of RedisKVStore in llama_index.storage.kvstore.redis, I think batch_size is for a different purpose.

[dosubot[bot]]

Hey @anirbanbasu, great to see you back! Hope you're doing well. 😄

Based on the information you've provided and the context from similar issues, it appears that the RedisKVStore component in LlamaIndex does not currently have a built-in feature for automatically handling large data sizes by splitting them into smaller chunks for transmission. The batch_size parameter in the put_all method is primarily designed to improve the efficiency of transmitting multiple operations in a single network call, rather than chunking individual large data items into smaller parts for storage and retrieval.

To handle large data sizes by splitting them into smaller chunks, you would need to implement a custom solution. This could involve creating a wrapper around the put and get methods to automatically chunk and reassemble large data items based on a specified chunk size. Here's a conceptual approach:

1. Chunking on put: When storing a large value, split it into smaller chunks. Store each chunk under a unique key derived from the original key (e.g., {original_key}_chunk_{chunk_number}), and keep track of the total number of chunks.

2. Reassembling on get: When retrieving the value, first retrieve the metadata to determine the number of chunks, then fetch each chunk and reassemble the original value.

Here's a simplified example of how you might start implementing chunking for the put method:

def put_with_chunking(self, key: str, val: dict, collection: str = DEFAULT_COLLECTION, chunk_size: int = 1024 * 1024):
    """Put a key-value pair into the store, with chunking for large values."""
    serialized_val = json.dumps(val)
    chunks = [serialized_val[i:i+chunk_size] for i in range(0, len(serialized_val), chunk_size)]
    for i, chunk in enumerate(chunks):
        chunk_key = f"{key}_chunk_{i}"
        self._redis_client.hset(name=collection, key=chunk_key, value=chunk)
    # Store metadata about the number of chunks
    self._redis_client.hset(name=collection, key=f"{key}_metadata", value=json.dumps({"chunks": len(chunks)}))

This example demonstrates the concept of chunking large values for storage. A similar approach would be needed for the get method to retrieve and reassemble the chunks. Please note that this is a simplified example and does not include error handling or optimizations that might be necessary for a production implementation.

As for the maximum data size that the RedisKVStore component in LlamaIndex can handle without encountering issues, it's generally aligned with Redis's inherent limitations. Redis, the underlying database used by RedisKVStore, has a maximum allowed size for a single value of 512 MB. This means any individual key-value pair stored in RedisKVStore must not exceed this size. It's important to note that this limit is for the value part of a key-value pair in Redis. You can refer to the Redis Protocol specification for more details.

I hope this information helps. If you have further questions or need more clarification, feel free to ask.

Sources

• [Question]: How to split or seperate nodes Doucment data?
• llama-index-integrations/storage/kvstore/llama-index-storage-kvstore-redis/llama_index/storage/kvstore/redis/base.py
• llama-index-legacy/llama_index/legacy/storage/kvstore/redis_kvstore.py

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[anirbanbasu]

Okay, thanks very much.