Just some things

This is a blog about some interesting things for me

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Нашел для себя классный подкаст канал Podlodka.

Ребята делают классный канал на околоайтишные темы.

Главной фишкой их является освещение интересных тем, в доброжелательном и комфортном формате, приглашение для этого экспертов в этих вопросах. 

ЗЫ. Правильное утверждение: “о понятиях не спорят, о них договариваются”

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AWS Outposts или Облака приходят к нам домой

Сегодня с удивлением узнал, что оказывается можно разворачивать сервисы AWS на своем частном облаке, локальном оборудовании.

Кажется это прикольная тема

Вот анонс - https://aws.amazon.com/ru/about-aws/whats-new/2018/11/announcing-aws-outposts/

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Недавно увидел в одном паблике в телеграмме. Отличная задачка для собеса :D

“Сколько жителей за МКАДОМ обожают авокадо.“

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/usr

it stands for “Unix System Resources”

not related to user... strangely enouch

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RabbitMQ

AMQP

AMQP connections: 7 TCP packages

AMQP channel: 2 TCP packages

AMQP publish: 1 TCP package (more for larger messages)

AMQP close channel: 2 TCP packages

AMQP close connection: 2 TCP packages

Total 14-19 packages (+ Acks)

RabbitMQ queue uses single thread and it could handle up to 50k messages

Plugins to bypass limits is using plugins:

a. consistent hash exchange plugin

b. RabbitMq sharding

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I Docker on MacOS for PHP projects such as based on Symfony etc

is big pain...

The same for Docker on Ubuntu:

Docker version 19.03

Average response time in dev mode:

Mac: ~30-40sec, memory: ~13Mb

Ubuntu: 1sec, memory: ~13Mb

Average response time in prod mode:

Mac: ~9-13sec, CPU time: 1.2sec, memory: ~6Mb

Ubuntu: 0.23sec, CPU time: 0.22sec, memory: ~6Mb

As it follows from profiler main problem come from IO. Even in prod mode it consume ~90% time for Mac. And it is correct due to there is huge difference between Docker FS and MacOS FS and it is not natively supported on Mac but use kind of abstraction layer. 

It is possible to improve response via docker-machine-nfs or docker-sync or any other similar solution. But it looks like it is not stable - one request it is faster(not like on Ubuntu but better) another one again slow. Therefore for me actually faster to run my dockerized project on another Linux machine in network without such hacks.

At meantime Mem topic is similar therefore I could say that even if it is abstraction solution for Docker for Mac - it is good

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Хорошая возможность отлаживать приложение и SQL запросы в MySQL

SET global general_log = 1; SET global log_output = 'table';

И потом чтоб посмотреть все запросы 

SELECT * FROM general_log

Это гораздо быстрее локально чем, например, включить профайлер

в приложении, разбираться с его форматом. А тут пожалуйста все запросы

Полезно для числа записей в таблицах

SELECT table_name, TABLE_ROWS FROM INFORMATION_SCHEMA.TABLES WHERE TABLE_SCHEMA = 'xxx' ORDER BY TABLE_ROWS DESC;

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Сontainerization

Сontainerization(Docker, LXC etc) is virtualization on process level

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Странности со скачками потребления RAM при рестарте контейнера

На днях стали происходить странные вещи, а именно при рестарте контейнера работающего на одном из дроплетов DigitalOcean стали прилетать алерты мол памяти потребляется более 70%, тогда как до деплоя было 50%. Это было очень странным так как контейнер в реальности потреблял меньше 1%. Проверка потребления памяти *free -m* показывала, что ничего не меняется, тогда как алерты все равно летели. 

Невероятно, но все решилось простым обновлением агента-сборщика метрик на дроплете. Вот так он успел устареть за 1 год, что начал глючить на +/- 20%

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Summary for how databases handle storage and retrieval.

On a high level, we saw that storage engines fall into two broad categories: those opti‐ mized for transaction processing (OLTP), and those optimized for analytics (OLAP). There are big differences between the access patterns in those use cases:

OLTP systems are typically user-facing, which means that they may see a huge volume of requests. In order to handle the load, applications usually only touch a small number of records in each query. The application requests records using some kind of key, and the storage engine uses an index to find the data for the requested key. Disk seek time is often the bottleneck here.

Data warehouses and similar analytic systems are less well known, because they are primarily used by business analysts, not by end users. They handle a much lower volume of queries than OLTP systems, but each query is typically very demanding, requiring many millions of records to be scanned in a short time. Disk bandwidth (not seek time) is often the bottleneck here, and column- oriented storage is an increasingly popular solution for this kind of workload.

On the OLTP side, we saw storage engines from two main schools of thought:

The log-structured school, which only permits appending to files and deleting obsolete files, but never updates a file that has been written. Bitcask, SSTables, LSM-trees, LevelDB, Cassandra, HBase, Lucene, and others belong to this group.

The update-in-place school, which treats the disk as a set of fixed-size pages that can be overwritten. B-trees are the biggest example of this philosophy, being used in all major relational databases and also many nonrelational ones.

Log-structured storage engines are a comparatively recent development. Their key idea is that they systematically turn random-access writes into sequential writes on disk, which enables higher write throughput due to the performance characteristics of hard drives and SSDs.

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Good to great: про дисциплину

Когда у вас работают дисциплинированные люди, вам не нужна иерархия. Когда у вас дисциплинированное мышление, вам не нужна бюрократия. Когда у вас дисциплинированные действия, вам не нужен избыточный контроль

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Lessons from Deep Work

Be valued for yourself and do effectively valued things

The batching of hard but important intellectual work into long, uninterrupted stretches is key to high productivity. 

When you switch tasks, your attention doesn’t immediately follow – a residue of your attention remains stuck thinking about the original task.

High-Quality Work Produced = (Time Spent) x (Intensity of Focus)

How to Perform Deep Work

To achieve deep work, you will need to follow four principles:

You must engage in deep work itself

Learn how to embrace, rather than avoid “boredom”

Have a plan to “quit social media”

You should definitely have a plan to “drain the shallows”

Transition to Deep Work

Use rituals and set routines to minimize friction in your transition to depth

“The key to developing a deep work habit is to move beyond good intentions and add routines and rituals to your working life designed to minimize the amount of your limited willpower necessary to transition into and maintain a state of unbroken concentration.”

Embrace Boredom

“To succeed with deep work you must rewire your brain to be comfortable resisting distracting stimuli.”

“The goal of productive meditation is to take a period in which you’re occupied physically but not mentally – walking, jogging, driving, showering – and focus your attention on a single well-defined professional problem.”

The key to successful productive meditation is repeatedly returning your attention to the problem at hand and doing this whenever your mind wanders. 

Quit Social Media

Sounds self-explained

Drain the Shallows

“Treat shallow work with suspicion because its damage is often vastly underestimated and its importance vastly overestimated. This type of work is inevitable, but you must keep it confined to a point where it doesn’t impede your ability to take full advantage of the deeper efforts that ultimately determine your impact.”

Schedule every minute of your day by using time blocking.

Batch tasks together into a specific synergistic time block – such as emailing, printing, ticket booking, etc.

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PHP doesn’t validate key lenght when do encryption by openssl_encrypt

It is easy to make mistake/misprint with PHP when do encryption.

Here is an example

$data = 12345; $mySecretCode = "AAAABBBBCCCCDDDD12345"; $iv = substr(sha1(mt_rand()), 0, 16); $salt = sha1(mt_rand()); $encrypted = openssl_encrypt(    "$data", 'aes-128-cbc', "$mySecretCode", null, $iv ); $token = "$salt:$iv:$encrypted"; var_dump($token); $mySecretCode = "AAAABBBBCCCCDDDD78910"; var_dump(openssl_decrypt($encrypted, 'aes-128-cbc', $mySecretCode, null, $iv));

For AES-128 secret key length should have lenght 16. As you see secrets are different but encryption still is working correctly.

Outh

php -f test.php string(82) "3136916d451c14ccda56b863425fe4e339d585cb:3109e6933a761a33:4MYdzv61OeOCbEmd81yHrw==" string(5) "12345"

 Explanation could be found in PHP-internals

https://github.com/php/php-src/blob/master/ext/openssl/openssl.c

You could see that here just substring of key is used.

Very strange that there is no at least any warnings for wrong key length case

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Тони Шэй, Zappos. Доставляя счастье. Очень здорово, что такого масштаба человек написал книгу о том, как он всего этого достиг. Читается на одном дыхании. 

Далее на почитать из нетехнической литературы:

- Яндекс.Книга

- Джим Коллинг “От хорошего к великому”

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heap in Go

Решая задачку по кучам на го, решил посмотреть как сделано в пакете container. Так вот там так же container/heap container/heap/heap.go:91 обычные двоичные кучи ;)

func up(h Interface, j int) {   for {      i := (j - 1) / 2 // parent      if i == j || !h.Less(j, i) {         break      }      h.Swap(i, j)      j = i   } } func down(h Interface, i0, n int) bool {   i := i0   for {      j1 := 2*i + 1      if j1 >= n || j1 < 0 { // j1 < 0 after int overflow         break      }      j := j1 // left child      if j2 := j1 + 1; j2 < n && h.Less(j2, j1) {         j = j2 // = 2*i + 2  // right child      }      if !h.Less(j, i) {         break      }      h.Swap(i, j)      i = j   }   return i > i0 }

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About pointer to pointer

Just find out nice explanation about pointer to pointer :)

If you want to have a list of characters (a word), you can use char *word

If you want a list of words (a sentence), you can use char **sentence

If you want a list of sentences (a monologue), you can use char ***monologue

If you want a list of monologues (a biography), you can use char ****biography

If you want a list of biographies (a bio-library), you can use char *****biolibrary

If you want a list of bio-libraries (a ??lol), you can use char ******lol

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Хорошее видео Simon Simek, мотивирующее, говорит о том как успешные (в разных направлениях) лидеры ведут за собой других и у кого это совершенно не получается