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Great insights. This approach of optimization will definitely come in handy particularly in data-driven PHP applications that implements big data processing and ETL operations.
A classical example is in the case of receiving seller data from Amazon Seller central, knowing that one seller/user could have millions of records which Amazon will forward to the PHP application.
It becomes a wild goose chase when the server has to process these millions of records for ~25mins. The result is often server time-outs or crash in execution.
With this approach, I see that there's refinement in performance to serve resources at improved speed.
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Great insights. This approach of optimization will definitely come in handy particularly in data-driven PHP applications that implements big data processing and ETL operations.
A classical example is in the case of receiving seller data from Amazon Seller central, knowing that one seller/user could have millions of records which Amazon will forward to the PHP application.
It becomes a wild goose chase when the server has to process these millions of records for ~25mins. The result is often server time-outs or crash in execution.
With this approach, I see that there's refinement in performance to serve resources at improved speed.