Problems with Poor GSQL Queries:
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Slow Query Performance: If your queries aren’t well-optimized, they might take a long time to execute. This can frustrate users and create performance bottlenecks within your system.
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High Memory Usage: Inefficient queries can consume excessive memory. This can lead to memory shortages and performance issues within your system.
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Inaccurate Results: Poorly written queries may not return correct results. This can introduce errors in your applications and compromise your data integrity.
Best Practices for Writing GSQL Queries in TigerGraph:
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Optimize Traversal Plan Complexity: Craft a traversal plan that minimizes unnecessary steps and operations. Carefully select vertices and edges to traverse, considering their order. This well-designed plan enhances query performance by reducing computational overhead.
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Prioritize Memory Efficiency: Write queries that use memory efficiently, avoiding data duplication and choosing appropriate data types. Memory-efficient queries run faster and consume fewer system resources.
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Choose Appropriate Accumulators: Select the right accumulator to store intermediate results in your queries. Well-chosen accumulators improve performance by reducing unnecessary data manipulation.
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Follow Clear Coding Conventions: Adhere to consistent coding practices and use comments to enhance query readability. Clear code promotes collaboration and makes queries easier to understand and maintain.
I hope this will help the community