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Qbeast for Spark

Qbeast-Spark is a core technology for Qbeast. It enhances the performance of your data lakehouse by optimizing Spark. Qbeast-Spark integrates with your existing setup, improving data access and usage.

Key features​

  • Multi-column indexing. Qbeast-Spark indexes multiple columns based on your specifications. This drastically reduces query times, especially for complex queries involving joins or filters. Think of it as a highly efficient catalog system for your data.
  • Efficient data sampling. When you need quick insights, Qbeast-Spark’s data sampling feature delivers fast, approximate results. This is ideal for preliminary exploration of large datasets, saving time and resources by avoiding full scans.

Benefits of Qbeast-Spark​

  • Accelerated query execution. With multi-column indexing and efficient data sampling, Qbeast-Spark speeds up query execution, making data analysis and reporting faster.
  • Reduced data transfer. Intelligent data access minimizes the amount of data transferred during queries, boosting overall performance and resource efficiency in your data lakehouse.
  • Cost efficiency. Faster query processing and optimized resource utilization lead to significant cost savings in data management operations.
  • Enhanced data exploration. Quick and efficient data sampling allows for rapid analysis of large datasets, facilitating swift data discovery and informed decision-making.
  • An open-source community. As an open-source project, Qbeast-Spark fosters a collaborative community where users can connect, contribute, and stay ahead of the latest developments in data management.

Qbeast-Spark enhances your data lakehouse by accelerating queries, reducing data transfer, and lowering operational costs. Its robust features, including multi-column indexing and data sampling, unlock the full potential of your data, enabling faster and more insightful decision-making.