DOC-2487-Added a new page for Query Plan Caching #274
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victorleeTG
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Apr 2, 2025
| This page covers how TigerGraph handles query execution and optimization through query plan caching. | ||
| When a query is executed, the system parses, transforms, and optimizes it before generating a query plan in JSON format to guide its execution. | ||
| While these steps are essential for processing the query, they can introduce significant overhead, especially when the same query is executed multiple times. | ||
| To mitigate this, TigerGraph caches the generated query plan in memory, ensuring faster execution on subsequent queries. |
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| To mitigate this, TigerGraph caches the generated query plan in memory, ensuring faster execution on subsequent queries. | |
| To mitigate this, TigerGraph caches the generated query plan in memory, ensuring faster execution on subsequent executions of a query. |
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| In many cases, users may frequently change constants in their queries. These changes can invalidate the cached query plan, making it necessary to re-interpret the query. | ||
| To handle this issue, TigerGraph employs a process known as *query normalization*. |
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| In many cases, users may frequently change constants in their queries. These changes can invalidate the cached query plan, making it necessary to re-interpret the query. | |
| To handle this issue, TigerGraph employs a process known as *query normalization*. | |
| In many cases, users may frequently change constants in their queries. These changes would invalidate the cached query plan, making it necessary to re-interpret the query. | |
| To avoid the reinterpretation, TigerGraph employs a process known as *query normalization*. |
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