The Morning Paper

MAY 23, 2019

Compress objects, not cache lines: an object-based compressed memory hierarchy Tsai & Sanchez, ASPLOS’19. Existing cache and main memory compression techniques compress data in small fixed-size blocks, typically cache lines. ” The big idea. Implications. This is where Hotpads comes in.

Cache 61

Cache Benchmarking Hardware Java 61

n0derunner

JULY 23, 2019

Effect of removing CPU constraints and maintaining data locality on a running DB instance. In this video I migrate a Postgres DB running PGbench benchmark. As the DB continues to run on the new host – the Nutanix storage detects the access patterns and “localizes” the data that the DB is accessing.

Benchmarking 76

Benchmarking Storage Tuning Cache 76

Percona

JULY 25, 2023

When a new node joins the cluster, SST is performed to receive the data from DONOR to the JOINER. JOINER uses PXB to stream the data directory from DONOR. Percona XtraBackup copies the InnoDB data files. Percona XtraBackup copies the InnoDB data files. ibd2sdi data/test/t1.ibd ibd2sdi data/test/t1.ibd

Cache 83

Cache Benchmarking Servers Design 83

Percona

MARCH 27, 2023

Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. having to open each table.frm (and in which my test runs, I have purposely read a very high number of tables compared to “Table-open-cache” variable). Results for Percona Server for MySQL 8.0 While you are on 5.7,

Cache 98

Cache Hardware Servers Benchmarking 98

HammerDB

APRIL 19, 2023

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.

Performance 54

Performance Benchmarking Cache Storage 54

Percona

MAY 1, 2023

Schema design: Evaluating the database schema design and making adjustments such as partitioning large tables, eliminating redundant data, and denormalizing tables for frequently accessed information can improve performance. Slow queries and data retrieval can lead to frustrating delays that impact the user experience.

Tuning 52

Tuning Efficiency Database Performance 52

Percona

JUNE 22, 2023

Database uptime and availability Monitoring database uptime and availability is crucial as it directly impacts the availability of critical data and the performance of applications or websites that rely on the MySQL database. Disk space usage Monitor the disk space usage of MySQL data files, log files, and temporary files.

Performance 102

Performance Monitoring Traffic Database 102

Percona

DECEMBER 23, 2022

The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes. If you wonder what is the difference between MyRocks and RocksDB, consider MyRocks as the piece of code, or the glue, that allows MySQL to store data in RocksDB.

Storage 55

Storage Cache C++ Virtualization 55

Percona

MARCH 17, 2023

For example, a higher number of data samples ingested per second or a monitoring database with a huge number of tables (1000+) can affect performance; similarly, the configuration for exporters or a custom metric resolution can also have an impact on the performance of a PMM server host. Virtual Memory utilization was averaging 48 GB of RAM.

Monitoring 95

Monitoring Scalability Cache Database 95

SQL Performance

NOVEMBER 18, 2019

Memory optimized – High memory-to-CPU ratio, relational database servers, medium to large caches, and in-memory analytics. The sizes offer you options for the number of vCPUs, RAM, and data disks. The number of data disks will determine maximum IOPS (IOPS stands for input/output operations per second.) Benchmark Test.

Azure 76

Azure Benchmarking Storage Virtualization 76

Percona

SEPTEMBER 1, 2023

Scalability As your data volume and user base expand, a finely tuned database can seamlessly accommodate increased workloads without compromising performance. An unoptimized indexing strategy can impede data insertion and retrieval operations. This can significantly elevate user satisfaction and engagement.

Tuning 52

Tuning Database Performance Hardware 52

n0derunner

MAY 6, 2019

A 2007 paper, that still has lots to say on the subject of benchmarking storage and filesystems. Primarily aimed at researchers and developers, but is relevant to anyone about to embark on a benchmarking effort. A Nine year study of filesystem and storage benchmarking Download. The post New (Old) Paper.

Benchmarking 40

Benchmarking Storage Cache Testing 40

The Morning Paper

AUGUST 29, 2019

There’s a broad set of choices including where you store the data, whether you run your own DBMS nodes or use a service, the kinds of instance types to go for if you do run your own, and so forth. We focused on OLAP-oriented parallel data warehouse products available for AWS and restricted our attention to commercially available systems.

Architecture 76

Architecture Cloud Storage Serverless 76

Dotcom-Montior

AUGUST 5, 2020

Browser Caching: Although it may seem commonplace, caching is sometimes overlooked. Depending on how often you change content, you may want to set a long expiration time for your cache. Caching can ensure your browser doesn’t have to load all those elements if a visitor returns to your pages.

Website 92

Website Speed Cache Traffic 92

Abhishek Tiwari

DECEMBER 13, 2017

Can machine learning-based data structures i.e. learned data structures replace traditional data structures? The initial results show that learned data structures can outperform existing data structures. This has far-reaching implications how future data systems and algorithms will be designed. p = F(Key) ?

Artificial Intelligence 40

Artificial Intelligence Hardware Google Benchmarking 40

KeyCDN

DECEMBER 8, 2022

Many factors affect the speed of your WordPress website; some of them are: Your web host Server-side optimizations (PHP version, compression, caching, etc.) Configure cache to optimize your website Caching is a complex technology with many layers. Traditionally, most WordPress hosts manage the caching.

Cache 52

Cache Website Speed Website Performance 52

MachMetrics

DECEMBER 14, 2019

By analyzing the data from Backlinko.com and their Page Speed Stats article, we’ll look to answer these questions: What size should be a website be? Unfortunately, the data from Backlinko paints a bleak picture when it comes to mobile internet browsing. It’s still a drain on the visitor’s device battery and data plan.

Best Practices 105

Best Practices Speed Mobile Google 105

The Morning Paper

MAY 14, 2019

Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., For the services under study, Seer has a sweet spot when trained with around 100GB of data and a 100ms sampling interval for measuring queue depths. ASPLOS’19. Distributed tracing and instrumentation. Seer in action.

Big Data 45

Big Data Cloud Performance Hardware 45

Percona

AUGUST 31, 2018

That means data is stored in memory twice, first in PostgreSQL buffer and then kernel buffer. This parameter sets how much dedicated memory will be used by PostgreSQL for cache. The configuration really depends on your machine and the working data set. It is just a guideline, not the exact allocated memory or cache size.

Tuning 54

Tuning Database Performance Benchmarking 54

Percona

JANUARY 9, 2023

NOTE : All tests were applied for MySQL version 8.0.30, and in the background, I ran every query three to five times to make sure that all of them were fully cached in the buffer pool (for InnoDB) or by the filesystem (for MyISAM). But why we can’t just cache the actual number of the rows? sec) What flash speed we saw there!

Cache 74

Cache Engineering Storage Speed 74

The Morning Paper

JUNE 16, 2019

A typical backing store for a web application contains data for many users. The application makes queries on behalf of an authenticated user, but it is up to the application itself to make sure that the user only sees data they are entitled to see. Towards multiverse databases Marzoev et al., HotOS’19.

Database 90

Database Cache Benchmarking Efficiency 90

Scalegrid

MARCH 28, 2024

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Redis is better suited for complex data models, and Memcached is better suited for high-throughput, string-based caching scenarios.

Cache 130

Cache Storage Scalability Architecture 130

Rigor

DECEMBER 19, 2019

Synthetic monitoring vendors provide a remote (often global) infrastructure that visits a website periodically and records the performance data for each run. The measured traffic is not of your actual users; it is synthetically generated to collect data on page performance. Benchmark Against Competitors.

Monitoring 40

Monitoring Benchmarking Website Traffic 40

Brendan Gregg

MARCH 16, 2024

It fails because of a compiler optimization where the frame pointer register is used to store data instead of the frame pointer, but it's just a number so the profiler is unaware this happened and tries to match that address to a function symbol and fails (it is therefore an unknown symbol). You usually get an extra junk frame.

Java 145

Java Cache Google Hardware 145

Brendan Gregg

JUNE 30, 2018

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

Benchmarking 54

Benchmarking Latency Cache Network 54

HammerDB

JUNE 27, 2022

HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Percona

APRIL 7, 2023

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. In PostgreSQL, it is called shared buffers.

Tuning 133

Tuning Cache Servers Benchmarking 133

The Morning Paper

SEPTEMBER 24, 2020

Static analysis of Java enterprise applications: frameworks and caches, the elephants in the room , Antoniadis et al., All that framework and configuration code makes for very heavy use of generic, heterogeneous data structures! PLDI’20. Static analysis is a key component of many quality and security analysis tools.

Java 80

Java Cache Benchmarking Programming 80

Percona

APRIL 6, 2023

PostgreSQL is a popular open source relational database management system many organizations use to store and manage their data. Query caching Pgpool-II can cache frequently used queries in memory, reducing the load on your PostgreSQL servers and improving response times. Two benchmarks from users can be found here: [1] [2] 4.

Cache 111

Cache Open Source Benchmarking Database 111

Brendan Gregg

JUNE 29, 2018

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

Benchmarking 40

Benchmarking Latency Cache Network 40

Percona

SEPTEMBER 1, 2023

MySQL triggers are a powerful tool for database administrators and developers, enabling them to automate tasks, enforce data consistency, and respond to events within the database seamlessly. The significance of triggers lies in their ability to enforce data integrity and automate various database-related tasks.

Cache 59

Cache Database Games Healthcare 59

Scalegrid

JULY 29, 2020

So, we pitted the two connection poolers head-to-head, using the standard pgbench tool, to see which one provides better transactions per second throughput through a benchmark test. All of the PostgreSQL benchmark tests were run under the following conditions: Initialized pgbench using a scale factor of 100. Throughput Benchmark.

Benchmarking 246

Benchmarking Database Performance Testing Availability 246

CSS - Tricks

APRIL 1, 2021

Google’s industry benchmarks from 2018 also provide a striking breakdown of how each second of loading affects bounce rates. You can even consider a large payload as an expense to the end user, as large downloads may require larger data plans that cost more money. Compressing, minifying and caching assets. Let’s trim that down.

Cache 92

Cache Social Media Media Website 92

Percona

MARCH 23, 2023

By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way. Benchmark before you decide. As datasets continue to grow in size, the amount of RAM required to store and process these datasets also increases. Transparent huge pages (THP) disabled.

Performance 123

Performance Hardware Tuning Storage 123

HammerDB

NOVEMBER 5, 2018

This post at an entry-level discusses the options you have to improve log throughput in your benchmark environment. . Before the database is started your data should be in a consistent state on disk. When the database is started a component of the in-memory database instance is the data buffer.

Benchmarking 40

Benchmarking Database C++ Virtualization 40

Brendan Gregg

FEBRUARY 9, 2018

. - **Page fault rate:** adds a little more overhead as well, for high rates. - **Working set size (hot data)**: more than 10 Mbytes will cost additional overhead due to TLB flushing. I then analyzed performance during the benchmark ([active benchmarking]), and used other benchmarks to confirm findings.

Performance 75

Performance Benchmarking Cache Tuning 75

ACM Sigarch

OCTOBER 12, 2020

An inte ger in Python consumes 24 bytes instead of 4 bytes (because every object carries around type information, reference counts, and more), while the overhead for data structures like lists or dictionaries can be 4x that of their C++ counterparts. Are caches large enough for this code? Consider Python. . As Leiserson et al.

C++ 108

C++ Benchmarking Hardware Architecture 108