HammerDB

APRIL 19, 2023

For example, if you are buying the latest Amazon memory-optimized EC2 instance (R7iz), the AWS page ( [link] ) tells us the following: Up to 3.9 This all sounded very similar to HammerDB TPROC-C workload (we will look at HammerDB TPROC-H (OLAP) another time), so it is easy for any reader to think both workloads are about the same.

Performance 54

Performance Benchmarking Cache Storage 54

Brendan Gregg

AUGUST 18, 2019

For example, iostat(1), or a monitoring agent, may tell you your average disk latency, but not the distribution of this latency. This example instrumented one of many thousands of available events. Now a real example: # bpftrace -e 'kretprobe:sys_read /pid == 181/ { @bytes = hist(retval); }'. Attaching 2 probes. ^C bashreadline.bt

Latency 68

Latency C++ Cache Programming 68

The Morning Paper

NOVEMBER 5, 2019

It’s also a fabulous example of recognising and challenging implicit assumptions. Breaking that assumption allowed Ceph to introduce a new storage backend called BlueStore with much better performance and predictability, and the ability to support the changing storage hardware landscape. The first implementation (c.

Storage 64

Storage Systems Hardware Efficiency 64

Smashing Magazine

JANUARY 11, 2021

Build Optimizations JavaScript modules, module/nomodule pattern, tree-shaking, code-splitting, scope-hoisting, Webpack, differential serving, web worker, WebAssembly, JavaScript bundles, React, SPA, partial hydration, import on interaction, 3rd-parties, cache. Adjust the argument depending on the group of stakeholders you are speaking to.

Performance 145

Performance Cache Media Metrics 145

ScaleOut Software

JULY 27, 2018

Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities. This model works well for storing large, object-oriented collections of business-logic state, such as the examples listed above. That’s where performance problems can begin.

Scalability 40

Scalability Cache Airlines Healthcare 40

ScaleOut Software

JULY 27, 2018

Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities. This model works well for storing large, object-oriented collections of business-logic state, such as the examples listed above. That’s where performance problems can begin.

Scalability 40

Scalability Cache Airlines Healthcare 40

The Morning Paper

DECEMBER 8, 2019

Byte-addressable non-volatile memory,) NVM will fundamentally change the way hardware interacts, the way operating systems are designed, and the way applications operate on data. The beauty of persistent memory is that we can use memory layouts for persistent data (with some considerations for volatile caches etc. What about security?

Hardware 56

Hardware Programming Media Storage 56

Smashing Magazine

JANUARY 6, 2020

Run performance experiments and measure outcomes — both on mobile and on desktop (for example, with Google Analytics ). Rather than focusing on full page loading time (via onLoad and DOMContentLoaded timings, for example), prioritize page loading as perceived by your customers. What does it mean? Large preview ).

Performance 145

Performance Cache Network Metrics 145

SQL Server According to Bob

DECEMBER 18, 2018

For example, if a flight booking reports that a seat has successfully been booked, then the seat will remain booked even if the system crashes.” – [link]. Device level flushing may have an impact on your I/O caching, read ahead or other behaviors of the storage system. Linux open command flag used to bypass file system cache.

Servers 90

Servers Media Cache Storage 90

Smashing Magazine

JUNE 18, 2020

Flutter isn’t that, though: it runs natively on each platform, and it means each app runs just like it would run if it were written in Java/Kotlin or Objective-C/Swift on Android and iOS, pretty much. Example 1: Storage. Example 2: Differences In How The Same Widget Is Displayed.

Storage 93

Storage Mobile Website Java 93

Smashing Magazine

JANUARY 7, 2019

One way or another, rather than focusing on full page loading time (via onLoad and DOMContentLoaded timings, for example), prioritize page loading as perceived by your customers. On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later).

Performance 104

Performance Cache Network Metrics 104

John McCalpin

NOVEMBER 5, 2016

So consider the dense matrix multiplication operation C += A*B, where A, B, and C are dense square matrices of order N, and the matrix multiplication operation is equivalent to the pseudo-code: for (i=0; i<N; i++) { for (j=0; j<N; j++) { for (k=0; k<N; k++) { C[i][j] += A[i][k] * B[k][j]; } } }.

Cache 40

Cache C++ Latency Hardware 40

Percona

JANUARY 17, 2019

On multi-core machines – which is the majority of the hardware nowadays – and in the cloud, we have multiple cores available for use. Aurora Parallel Query response time (for queries which can not use indexes) can be 5x-10x better compared to the non-parallel fully cached operations. The second and third run used the cached data.

Cache 46

Cache C++ AWS Airlines 46

Highly Scalable

SEPTEMBER 18, 2012

A database should accommodate itself to different data distributions, cluster topologies and hardware configurations. This approach is used for example in Cassandra. This behavior can be semantically inappropriate (for example, if both clients add a value to a list). In this example R=2, W=2, N=3. Data Placement.

Database 213

Database Latency C++ Scalability 213

Randon ASCII

FEBRUARY 25, 2018

In this particular investigation, which spanned twenty months, we suspected hardware failure, compiler bugs, linker bugs, and other possibilities. Jumping too quickly to blaming hardware or build tools is a classic mistake, but in this case the mistake was that we weren’t thinking big enough. failure rate. Play along at home.

Programming 79

Programming Hardware Cache Code 79

The Morning Paper

APRIL 2, 2019

In this context it means there are no external dependencies on e.g. secrets, trusted hardware modules, or special instructions (e.g. TPMs, SGX, …), and no polynomial bounds on an adversaries computing power (so for example they still work even in a post-quantum world). Putting it all together. Implementation.

Software 40

Software Software Programming Hardware 40

SQL Server According to Bob

JANUARY 11, 2020

As ​​ a ​​ simple ​​ example, ​​ take the following ​​ 2-byte string value of “AB” and apply a formula to it (Value = Position + ASCII value). ​​ Checksum ​​ is ​​ the sum of the values.

Servers 40

Servers Cache Database Media 40

The Morning Paper

SEPTEMBER 12, 2019

SQL provides a declarative programming interface, below which the system itself can figure out the most effective execution plans based on data size and statistics, layout, compute hardware etc. The authors introduce the notion of multiple versions of a table accessed via array-style indices, using Pascal’s triangle as an example.

Network 44

Network Database Programming Hardware 44

Smashing Magazine

AUGUST 22, 2021

This is a bit more difficult to explain, because it depends on the physical properties of the medium (for example, the used frequency of radio waves), the number of users on the network, and also the devices that interconnect different subnetworks (because they typically can only process a certain number of packets per second). Did You Know?

Performance 106

Performance Network Latency Servers 106

High Scalability

NOVEMBER 25, 2019

Edge caching. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. Nginx for disk based caching. We use different types of caching techniques depending on the problem statements. Disk based caching. Hybrid Sync. On prem data processing. Offline access.

Architecture 52

Architecture Cache Azure Storage 52