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Search Results for: mysql insert replace

Side load may massively impact your MySQL Performance

When we’re looking at benchmarks we typically run some stable workload and we run it in isolation – nothing else is happening on the system. This is not however how things happen in real world …

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MySQL caching methods and tips

“The least expensive query is the query you never run.” Data access is expensive for your application. It often requires CPU, network and disk access, all of which can take a lot of time. Using …

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MySQL on Amazon RDS part 1: insert performance

Amazon’s Relational Database Service (RDS) is a cloud-hosted MySQL solution. I’ve had some clients hitting performance limitations on standard EC2 servers with EBS volumes (see SSD versus EBS death match), and one of them wanted …

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Ultimate MySQL variable and status reference list

I am constantly referring to the amazing MySQL manual, especially the option and variable reference table. But just as frequently, I want to look up blog posts on variables, or look for content in the …

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On “Replace Into”, “Insert Ignore”, Triggers, and Row Based Replication

In posts on June 30 and July 6, I explained how implementing the commands “replace into” and “insert ignore” with TokuDB’s fractal trees data structures can be two orders of magnitude faster than implementing them …

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TokuDB speeds up “replace” and “insert ignore” operations by relaxing the affected rows constraint

In posts on June 30 and July 6, we explained how implementing the commands “replace into” and “insert ignore” with TokuDB’s fractal trees data structures can be two orders of magnitude faster than implementing them …

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On “Replace Into”, “Insert Ignore”, and Secondary Keys

In posts on June 30 and July 6, I explained how implementing the commands “replace into” and “insert ignore” with TokuDB’s fractal trees data structures can be two orders of magnitude faster than implementing them …

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Why “insert … on duplicate key update” May Be Slow, by Incurring Disk Seeks

In my post on June 18th, I explained why the semantics of normal ad-hoc insertions with a primary key are expensive because they require disk seeks on large data sets. I previously explained why it …

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Making “Insert Ignore” Fast, by Avoiding Disk Seeks

In my post from three weeks ago, I explained why the semantics of normal ad-hoc insertions with a primary key are expensive because they require disk seeks on large data sets. Towards the end of …

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Making “Replace Into” Fast, by Avoiding Disk Seeks

In this post two weeks ago, I explained why the semantics of normal ad-hoc insertions with a primary key are expensive because they require disk seeks on large data sets. Towards the end of the …

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