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Trip report: Autumn ISO C++ standards meeting (Kona, HI, USA)

Sutter's Mill

Today, the ISO C++ committee completed its second meeting of C++26, held in Kona, HI, USA. Our hosts, Standard C++ Foundation and WorldQuant, arranged for high-quality facilities for our six-day meeting from Monday through Saturday. This time, the committee adopted the next set of features for C++26. This is that library.

C++ 107
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PostgreSQL Performance Tuning: Optimizing Database Parameters for Maximum Efficiency

Percona

Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. What is PostgreSQL performance tuning? Why is PostgreSQL performance tuning important?

Tuning 52
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The Speed of Time

Brendan Gregg

As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. As (C) looked like a kernel rebuild, I started with (D) and (E). ## 5. Measuring the speed of time Is there already a microbenchmark for os::javaTimeMillis()? But I'm not completely sure.

Speed 126
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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

PostgreSQL Cluster One coordinator node citus-coord-01 Three worker nodes citus1 citus2 citus3 Hardware AWS Instance Ubuntu Server 20.04, SSD volume type 64-bit (x86) c5.xlarge And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

Database 107
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The Speed of Time

Brendan Gregg

As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. As (C) looked like a kernel rebuild, I started with (D) and (E). ## 6. Measuring the speed of time Is there already a microbenchmark for os::javaTimeMillis()? But I'm not completely sure.

Speed 40
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Data Redundancy With the PostgreSQL Citus Extension

Percona

Columnar storage of tables can compress data, speeding up scans and supporting fast projections, both on regular and distributed tables. Depending on the configuration, one can tune a hardware RAID for either performance or redundancy. The same can be said for Citus data sharding. citus_columnar | 11.1-1 1 citus | 11.1-1

C++ 81
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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.