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Virtual consensus in Delos

The Morning Paper

Virtual consensus in Delos , Balakrishnan et al. If you think of this a bit like mapping memory addresses to data in memory, then another parallel comes to mind: the virtual address space. We propose the novel abstraction of a virtual shared log (or VirtualLog). Facebook, Inc. ), OSDI’2020. What does the VirtualLog give us?

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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. Storage is a critical aspect to consider when working with cloud workloads.

Cloud 130
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AMD EPYC Processors in Azure Virtual Machines

SQL Performance

Back on December 5, 2017, Microsoft announced that they were using AMD EPYC 7551 processors in their storage-optimized Lv2-Series virtual machines. I wrote about using CPU-Z to benchmark the Intel Xeon E5-2673 v3 processor in an Azure VM in this article. Figure 1: CPU-Z Benchmark Results for LS16v2. SQL Server Impact.

Azure 42
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The Most Important MySQL Setting

Percona

To illustrate this, I ran the Sysbench-TPCC synthetic benchmark against two different GCP instances running a freshly installed Percona Server for MySQL version 8.0.31 In MySQL, considering the standard storage engine, InnoDB , the data cache is called Buffer Pool. We have long been surfing the virtualization wave (to keep it broad).

Tuning 133
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How to improve Redo, Transaction Log and WAL throughput for HammerDB benchmarks

HammerDB

This post at an entry-level discusses the options you have to improve log throughput in your benchmark environment. . Additionally for the log disk component it is latency for an individual write that is crucial rather than the total I/O bandwidth. innodb_flush_log_at_trx_commit=0. PostgreSQL.

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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.

C++ 40
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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. faster access to external storage and data locality (I/O, bandwidth). Storage provisioning. But Kubernetes storage is evolving quite quickly.