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How to improve performance of mongoDB aggregation query?
To improve the efficiency of query execution, the order of aggregation stages matters a lot.
- $match stage: The matching stage is used to select the required documents only.
- $sort stage: $sort is used to sort the documents in ascending or descending order of value.
- $limit stage:
- $skip stage:
- $project stage:
How fast is mongoDB aggregation?
600MB/s maximum instantaneous data transfers. 7200 RPM spindle. Average latency = 4.16ms.
When should I use aggregate in MongoDB?
Aggregation operations process data records and return computed results. Aggregation operations group values from multiple documents together, and can perform a variety of operations on the grouped data to return a single result.
Which is the best way to improve query performance?
See Manage the Query Log . Aggregate tables: It’s extremely important to use aggregate tables to improve query performance. Aggregate tables contain precalculated summarizations of data. It’s much faster to retrieve an answer from an aggregate table than to recompute the answer from thousands of rows of detail.
How to improve query performance in Oracle BI server?
The following list summarizes methods that you can use to improve query performance: Tuning and indexing underlying databases: For Oracle BI Server database queries to return quickly, the underlying databases must be configured, tuned, and indexed correctly. Note that different database products have different tuning considerations.
How does Oracle BI server use aggregate tables?
The Oracle BI Server uses aggregate tables automatically, if they’ve been properly specified in the repository. See Managing Metadata Repositories for Oracle Analytics Server for examples of setting up aggregate navigation. Query caching: The Oracle BI Server can store query results for reuse by subsequent queries.
How does query caching improve the performance of Oracle?
Query caching: The Oracle BI Server can store query results for reuse by subsequent queries. Query caching can dramatically improve the apparent performance of the system for users, particularly for commonly used dashboards, but it doesn’t improve performance for most ad-hoc analysis.