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Why you should benchmark your database using stored procedures

HammerDB

HammerDB uses stored procedures to achieve maximum throughput when benchmarking your database. HammerDB has always used stored procedures as a design decision because the original benchmark was implemented as close as possible to the example workload in the TPC-C specification that uses stored procedures. On MySQL, we saw a 1.5X

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HammerDB v4.0 New Features Pt1: TPROC-C & TPROC-H

HammerDB

The HammerDB TPROC-C workload by design intended as CPU and memory intensive workload derived from TPC-C – so that we get to benchmark at maximum CPU performance at a much smaller database footprint. For TPC-C this meant enough available spindles to reduce I/O latency and for TPC-H enough bandwidth for data throughput.

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Virtual consensus in Delos

The Morning Paper

Virtual consensus in Delos , Balakrishnan et al. USENIX is a nonprofit organisation committed to making content and research freely available – both conference proceedings and the recorded presentations of their events. We propose the novel abstraction of a virtual shared log (or VirtualLog). Facebook, Inc. ), OSDI’2020.

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Kubernetes for Big Data Workloads

Abhishek Tiwari

Containerized data workloads running on Kubernetes offer several advantages over traditional virtual machine/bare metal based data workloads including but not limited to. Kubernetes has all necessary primitives available to make it happen. better cluster resource utilization. portability between cloud and on-premises. Performance.

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PostgreSQL Connection Pooling: Part 4 – PgBouncer vs. Pgpool-II

Scalegrid

This is shared between all clients, so a pooled connection is available to all clients. High availability. PostgreSQL high availability is supported through Pgpool-II in-built watcher processes. Not supported – PgBouncer recommends use of HAProxy for high availability and load balancing. When are connections reused?

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What Is a Workload in Cloud Computing

Scalegrid

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. This applies to both virtual machines and container-based deployments.

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The Speed of Time

Brendan Gregg

A Cassandra database cluster had switched to Ubuntu and noticed write latency increased by over 30%. CLI tools The Cassandra systems were EC2 virtual machine (Xen) instances. Note that Ubuntu also has a frame to show entry into vDSO (virtual dynamic shared object). Running this on the two systems saw similar results.

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