Remove 2003 Remove Benchmarking Remove Systems
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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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How to build HammerDB from source

HammerDB

If you are not already familiar with the programming languages that HammerDB uses, then this earlier post serves as an ideal introduction to what makes up the highest performing GIL free database benchmarking application. Copyright (C) 2003-2022 Steve Shaw Type "help" for a list of commands hammerdb>librarycheck. HammerDB-4.4-Linux.tar.gz

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HammerDB v4.7 New Features Pt 2: Example CLI Scripts

HammerDB

Note that by default the build script will query the number of CPUs on the system that HammerDB is running and configure 5X this number for the number of warehouses to build. If HammerDB is running on a separate system from the database under test then you should modify this value accordingly. scripts/tcl/maria/tprocc/maria_tprocc.sh

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HammerDB v4.8 New Features : Viewing your Benchmark results with the HammerDB Web Service

HammerDB

Copyright (C) 2003-2023 Steve Shaw Type "help" for a list of commands Initialized new Jobs on-disk database /opt/HammerDB-4.8/DATA/hammer.db Copyright (C) 2003-2023 Steve Shaw Type "help" for a list of commands Initialized new Jobs on-disk database /opt/HammerDB-4.8/TMP/hammer.DB So for example to change this to hammer.db DATA/hammer.db

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How to deploy HammerDB CLI fast with Docker

HammerDB

Our Linux test system is running a MariaDB 10.10 On a system with docker installed, use docker pull tpcorg/hammerdb to pull the latest image. Copyright (C) 2003-2022 Steve Shaw Type "help" for a list of commands Initialized new SQLite on-disk database /tmp/hammer.DB Copyright (C) 2003-2022 Steve Shaw. Docker Hub.

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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

on Myths and Legends of High Performance Computing  — it’s a somewhat light-hearted look at some of the same issues by the leader of the team that built the Fugaku system I mention below. HPCG is led by Japan’s RIKEN Fugaku system at 16 petaflops, which is 3% of it’s peak capacity. Next generation architectures will use CXL3.0

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HammerDB v4.7 New Features Pt 3: Lightweight Docker Images for rapid testing

HammerDB

introduces more lightweight database specific Docker Images, so if you only want to run benchmarks against a specific database you can go from having no benchmarking environment to reviewing your results in as little as 3 commands. How to deploy HammerDB CLI fast with Docker HammerDB v4.7 scripts/tcl/postgres/tprocc/pg_tprocc.sh