Posts Tagged ‘Best Practices’

Building a high-performance platform – Key points

Posted: June 28, 2023 by Virendra Yaduvanshi in Database Administrator
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Building a high-performance platform requires careful planning, efficient architecture, and optimization techniques. Below are some key considerations and best practices to keep in mind during building a high-performance platform,

Define Performance Goals: Need to clearly define expected performance goals and metrics early on. Need to work hard on to understand the expected load, response times, and user expectations from platform.

Scalable Architecture: Design a scalable architecture that can handle increasing loads without compromising performance. Consider using distributed systems, load balancers, and caching mechanisms to distribute the workload efficiently.

Efficient Database Design: It’s a continuous process to Optimize your database design and queries to ensure fast and efficient data retrieval. Use indexing, query optimization techniques, and denormalization when appropriate.

Caching: Implement caching mechanisms to reduce the load on backend systems. Utilize in-memory caches, content delivery networks (CDNs), and caching proxies to serve frequently accessed data quickly.

Asynchronous Processing: Offload time-consuming and non-blocking tasks to asynchronous processes or background jobs. This allows the platform to handle concurrent requests efficiently and improve responsiveness.

Code Optimization: Write efficient and optimized code. Minimize resource-intensive operations, avoid unnecessary loops or recursion, and use algorithms and data structures that offer better performance.

Performance Testing: Regularly perform load testing and performance profiling to identify bottlenecks, scalability issues, and areas for improvement. Tools like JMeter or Gatling can help simulate high user loads and measure performance.

Monitoring and Logging: Implement robust monitoring and logging solutions to track the performance of your platform in real-time. Use metrics and logs to identify issues, analyze trends, and make data-driven optimizations.

Continuous Optimization: Continuously analyze performance data and user feedback to identify areas for optimization. Apply iterative improvements to enhance your platform’s performance over time.

Cloud Infrastructure: Consider leveraging cloud-based infrastructure services, such as AWS, Azure, or Google Cloud, to benefit from their scalability, reliability, and performance optimization features.

Building a high-performance platform is an ongoing process. It requires a combination of careful planning, architectural considerations, optimization techniques, and continuous monitoring and improvement.

Best Practices for Bulk Importing Data

Posted: December 24, 2012 by Virendra Yaduvanshi in Database Administrator
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  • Using INSERT INTO…SELECT to Bulk Import Data with Minimal Logging

INSERT INTO <target_table> SELECT <columns> FROM <source_table> is the best way to efficiently transfer a large number of rows from one table, such as a staging table, to another table with minimal logging. Minimal logging can improve the performance and will fill the minimum amount of available transaction log space during the transaction. Minimal logging for this statement has the following requirements:
• The recovery model of the database is set to simple or bulk-logged.
• The target table is an empty or nonempty heap.
• The target table is not used in replication.
• The TABLOCK hint is specified for the target table.

Rows that are inserted into a heap as the result of an insert action in a MERGE statement may also be minimally logged. Unlike the BULK INSERT statement, which holds a less restrictive Bulk Update lock, INSERT INTO…SELECT with the TABLOCK hint holds an exclusive (X) lock on the table. This means that we cannot insert rows using parallel insert operations.

  • Using OPENROWSET and BULK to Bulk Import Data

The OPENROWSET function can accept the following table hints, which provide bulk-load optimizations with the INSERT statement:
• The TABLOCK hint can minimize the number of log records for the insert operation. The recovery model of the database must be
set to simple or bulk-logged and the target table cannot be used in replication.
•The IGNORE_CONSTRAINTS hint can temporarily disable FOREIGN KEY and CHECK constraint checking.
• The IGNORE_TRIGGERS hint can temporarily disable trigger execution.
• The KEEPDEFAULTS hint allows the insertion of a table column’s default value, if any, instead of NULL when the data record
lacks a value for the column.
• The KEEPIDENTITY hint allows the identity values in the imported data file to be used for the identity column in the target table.