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How to Assess MySQL Performance

HammerDB

GHz 4th Generation Intel Xeon Scalable processors (code-named Sapphire Rapids) Up to 20% higher compute performance than z1d instances Up to 50 Gbps of networking speed Up to 40 Gbps of bandwidth to the Amazon Elastic Block Store (EBS) We can also verify these capabilities by running some simple benchmarks on the different subsystems.

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A MyRocks Use Case

Percona

The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes. If you wonder what is the difference between MyRocks and RocksDB, consider MyRocks as the piece of code, or the glue, that allows MySQL to store data in RocksDB.

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Why Tcl is 700% faster than Python for database benchmarking

HammerDB

Python is a popular programming language, especially for beginners, and consequently we see it occurring in places where it just shouldn’t be used, such as database benchmarking. We use stored procedures because, as the introductory post shows, using single SQL statements turns our database benchmark into a network test).

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HammerDB for Managers

HammerDB

HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.

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From Heavy Metal to Irrational Exuberance

ACM Sigarch

These, let’s call them metal languages , include FORTRAN (introduced in 1957), C (1972), and C++ (1985). Programmers continue to write applications in them, and they continue to evolve: the just approved C++20 standard is the latest example. Despite their age, these languages are far from dead! As Leiserson et al.

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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., A typical architecture diagram for one of these services looks like this: Suitably armed with a set of benchmark microservices applications, the investigation can begin! ASPLOS’19.

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KPTI/KAISER Meltdown Initial Performance Regressions

Brendan Gregg

This overhead can be reduced by A) pcid, fully available in Linux 4.14, and B) Huge pages. - **Cache access pattern**: the overheads are exacerbated by certain access patterns that switch from caching well to caching a little less well. This can turn a 1% overhead (syscall cycles alone) into a 7% overhead. In more detail: ## 1.