license:mit size_categories:n<1K format:csv modality:text library:datasets library:pandas library:mlcroissant library:polars region:us infinite-dataset-hub synthetic
---
license: mit
tags:
- infinite-dataset-hub
- synthetic
---

# ShardDistributions

tags: data_science, sharding_optimization, data_volume

_Note: This is an AI-generated dataset so its content may be inaccurate or false_

**Dataset Description:**

The 'ShardDistributions' dataset provides a snapshot of various shard distributions across multiple databases, highlighting the challenges and strategies in sharding for optimization of data volume management. Each entry captures the schema complexity, data volume, shard key selection criteria, and performance metrics that inform the sharding optimization process. This dataset can be instrumental for data scientists and engineers working on database sharding strategies to ensure scalability and efficient data access.

**CSV Content Preview:**

```csv
database_id, schema_complexity, data_volume, shard_key, performance_metric, label
DB01, high, 10TB, user_id, 99.5%, optimal
DB02, medium, 2TB, timestamp, 95.0%, good
DB03, low, 1TB, user_id_and_timestamp, 98.0%, optimal
DB04, high, 15TB, product_id, 94.5%, needs_review
DB05, medium, 3TB, location, 97.0%, good
```

**Source of the data:**

The dataset was generated using the [Infinite Dataset Hub](https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub) and microsoft/Phi-3-mini-4k-instruct using the query 'Database Sharding':

- **Dataset Generation Page**: https://huggingface.co/spaces/infinite-dataset-hub/infinite-dataset-hub?q=Database+Sharding&dataset=ShardDistributions&tags=data_science,+sharding_optimization,+data_volume
- **Model**: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct
- **More Datasets**: https://huggingface.co/datasets?other=infinite-dataset-hub
