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Awesome GitHub RepositoriesCross-Table Optimizations
Techniques for pruning and optimizing queries that span multiple physical tables.
Distinct from Virtual Table Querying: Distinct from Virtual Table Querying: focuses on performance optimization (pruning) across tables rather than the query interface itself.
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Awesome Cross-Table Optimizations GitHub Repositories
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- apache/pinot
apache/pinot
6,098Voir sur GitHubPinot is a distributed, columnar analytical database designed for high-concurrency, low-latency query processing. It functions as a real-time OLAP datastore, enabling interactive, user-facing analytics by ingesting and querying massive datasets from both streaming and batch sources. The system architecture relies on a centralized controller for cluster coordination and a distributed segment-based storage model to ensure horizontal scalability. The platform distinguishes itself through a hybrid ingestion pipeline that unifies real-time event streams and historical batch data into a single quer
Provides cross-table segment pruning to reduce data processing requirements for complex analytical queries.
Java
