Best Practices for Running PostgreSQL on AWS - DAT314 - re:Invent 2017Amazon Web Services
PostgreSQL is an open source database growing in popularity because of its rich features, vibrant community, and compatibility with commercial databases. Learn about ways to run PostgreSQL on AWS including self-managed, and the managed database services from AWS: Amazon Relational Database Service (Amazon RDS) and the Amazon Aurora PostgreSQL-compatible Edition. This talk covers key Amazon RDS for PostgreSQL functionality, availability, and management. We also review general guidelines for common user operations and activities such as migration, tuning, and monitoring for their RDS for PostgreSQL instances.
Natural Language Search with Knowledge Graphs (Activate 2019)Trey Grainger
To optimally interpret most natural language queries, its important to understand a highly-nuanced, contextual interpretation of the domain-specific phrases, entities, commands, and relationships represented or implied within the search and within your domain.
In this talk, we'll walk through such a search system powered by Solr's Text Tagger and Semantic Knowledge graph. We'll have fun with some of the more search-centric use cases of knowledge graphs, such as entity extraction, query expansion, disambiguation, and pattern identification within our queries: for example, transforming the query "best bbq near activate" into:
{!func}mul(min(popularity,1),100) bbq^0.91032 ribs^0.65674 brisket^0.63386 doc_type:"restaurant" {!geofilt d=50 sfield="coordinates_pt" pt="38.916120,-77.045220"}
We'll see a live demo with real world data demonstrating how you can build and apply your own knowledge graphs to power much more relevant query understanding like this within your search engine.
Best Practices for Running PostgreSQL on AWS - DAT314 - re:Invent 2017Amazon Web Services
PostgreSQL is an open source database growing in popularity because of its rich features, vibrant community, and compatibility with commercial databases. Learn about ways to run PostgreSQL on AWS including self-managed, and the managed database services from AWS: Amazon Relational Database Service (Amazon RDS) and the Amazon Aurora PostgreSQL-compatible Edition. This talk covers key Amazon RDS for PostgreSQL functionality, availability, and management. We also review general guidelines for common user operations and activities such as migration, tuning, and monitoring for their RDS for PostgreSQL instances.
Natural Language Search with Knowledge Graphs (Activate 2019)Trey Grainger
To optimally interpret most natural language queries, its important to understand a highly-nuanced, contextual interpretation of the domain-specific phrases, entities, commands, and relationships represented or implied within the search and within your domain.
In this talk, we'll walk through such a search system powered by Solr's Text Tagger and Semantic Knowledge graph. We'll have fun with some of the more search-centric use cases of knowledge graphs, such as entity extraction, query expansion, disambiguation, and pattern identification within our queries: for example, transforming the query "best bbq near activate" into:
{!func}mul(min(popularity,1),100) bbq^0.91032 ribs^0.65674 brisket^0.63386 doc_type:"restaurant" {!geofilt d=50 sfield="coordinates_pt" pt="38.916120,-77.045220"}
We'll see a live demo with real world data demonstrating how you can build and apply your own knowledge graphs to power much more relevant query understanding like this within your search engine.
29回勉強会資料「PostgreSQLのリカバリ超入門」
See also http://www.interdb.jp/pgsql (Coming soon!)
初心者向け。PostgreSQLのWAL、CHECKPOINT、 オンラインバックアップの仕組み解説。
これを見たら、次は→ http://www.slideshare.net/satock/29shikumi-backup
Presentation that I gave as a guest lecture for a summer intensive development course at nod coworking in Dallas, TX. The presentation targets beginning web developers with little, to no experience in databases, SQL, or PostgreSQL. I cover the creation of a database, creating records, reading/querying records, updating records, destroying records, joining tables, and a brief introduction to transactions.
PostgreSQL (or Postgres) began its life in 1986 as POSTGRES, a research project of the University of California at Berkeley.
PostgreSQL isn't just relational, it's object-relational.it's object-relational. This gives it some advantages over other open source SQL databases like MySQL, MariaDB and Firebird.
RDS Postgres and Aurora Postgres | AWS Public Sector Summit 2017Amazon Web Services
Attend this session for a technical deep dive about RDS Postgres and Aurora Postgres. Come hear from Mark Porter, the General Manager of Aurora PostgreSQL and RDS at AWS, as he covers service specific use cases and applications within the AWS worldwide public sector community. Learn More: https://aws.amazon.com/government-education/
Migrating Apache Spark ML Jobs to Spark + Tensorflow on KubeflowDatabricks
This talk will take an two existings Spark ML pipeline (Frank The Unicorn, for predicting PR comments (Scala) – https://github.com/franktheunicorn/predict-pr-comments & Spark ML on Spark Errors (Python)) and explore the steps involved in migrating this into a combination of Spark and Tensorflow. Using the open source Kubeflow project (now with Spark support as of 0.5), we will create an two integrated end-to-end pipelines to explore the challenges involved & look at areas of improvement (e.g. Apache Arrow, etc.).
Spark (Structured) Streaming vs. Kafka StreamsGuido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
This presentation shows how you can implement stream processing solutions with each of the two frameworks, discusses how they compare and highlights the differences and similarities.
Ilya Kosmodemiansky - An ultimate guide to upgrading your PostgreSQL installa...PostgreSQL-Consulting
Even an experienced PostgreSQL DBA can not always say that upgrading between major versions of Postgres is an easy task, especially if there are some special requirements, such as downtime limitations or if something goes wrong. For less experienced DBAs anything more complex than dump/restore can be frustrating.
In this talk I will describe why we need a special procedure to upgrade between major versions, how that can be achieved and what sort of problems can occur. I will review all possible ways to upgrade your cluster from classical pg_upgrade to old-school slony or modern methods like logical replication. For all approaches, I will give a brief explanation how it works (limited by the scope of this talk of course), examples how to perform upgrade and some advice on potentially problematic steps. Besides I will touch upon such topics as integration of upgrade tools and procedures with other software — connection brokers, operating system package managers, automation tools, etc. This talk would not be complete if I do not cover cases when something goes wrong and how to deal with such cases.
Custom DevOps Monitoring System in MelOn (with InfluxDB + Telegraf + Grafana)Seungmin Yu
2016년도 데이터야놀자에서 발표한 자료입니다.
멜론에서 InfluxDB + Telegraf + Grafana 조합으로 모니터링 시스템을 구축하고 활용한 사례를 발표한 내용입니다. 다양한 메트릭데이터와 DevOps 측면의 활용 가치에 대해서도 생각해 볼 수 있을 것 같습니다.
Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DBYugabyteDB
Slides for Amey Banarse's, Principal Data Architect at Yugabyte, "Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DB" webinar recorded on Oct 30, 2019 at 11 AM Pacific.
Playback here: https://vimeo.com/369929255
Are you ready for the next attack? reviewing the sp security checklist (apnic...Barry Greene
Rethinking Security and how you can Act on Meaningful Change
What the industry recommends to protect your network is NOT working! The industry is stuck in a dysfunctional ecosystem that encourages the cyber-criminal innovation at the cost to business and individual loss throughout the world. We do not need a “Manhattan Project” for the security of the Internet. What we need are tools to help operators throughout the world ask the right question that would lead them to meaningful action. Security empowerment must empower the grassroots and provide the tools to push back on the root cause. This talk will explore these issues, highlight the dysfunction in our “security” economy, and present “take home” tools that would facilitate immediate action.
29回勉強会資料「PostgreSQLのリカバリ超入門」
See also http://www.interdb.jp/pgsql (Coming soon!)
初心者向け。PostgreSQLのWAL、CHECKPOINT、 オンラインバックアップの仕組み解説。
これを見たら、次は→ http://www.slideshare.net/satock/29shikumi-backup
Presentation that I gave as a guest lecture for a summer intensive development course at nod coworking in Dallas, TX. The presentation targets beginning web developers with little, to no experience in databases, SQL, or PostgreSQL. I cover the creation of a database, creating records, reading/querying records, updating records, destroying records, joining tables, and a brief introduction to transactions.
PostgreSQL (or Postgres) began its life in 1986 as POSTGRES, a research project of the University of California at Berkeley.
PostgreSQL isn't just relational, it's object-relational.it's object-relational. This gives it some advantages over other open source SQL databases like MySQL, MariaDB and Firebird.
RDS Postgres and Aurora Postgres | AWS Public Sector Summit 2017Amazon Web Services
Attend this session for a technical deep dive about RDS Postgres and Aurora Postgres. Come hear from Mark Porter, the General Manager of Aurora PostgreSQL and RDS at AWS, as he covers service specific use cases and applications within the AWS worldwide public sector community. Learn More: https://aws.amazon.com/government-education/
Migrating Apache Spark ML Jobs to Spark + Tensorflow on KubeflowDatabricks
This talk will take an two existings Spark ML pipeline (Frank The Unicorn, for predicting PR comments (Scala) – https://github.com/franktheunicorn/predict-pr-comments & Spark ML on Spark Errors (Python)) and explore the steps involved in migrating this into a combination of Spark and Tensorflow. Using the open source Kubeflow project (now with Spark support as of 0.5), we will create an two integrated end-to-end pipelines to explore the challenges involved & look at areas of improvement (e.g. Apache Arrow, etc.).
Spark (Structured) Streaming vs. Kafka StreamsGuido Schmutz
Independent of the source of data, the integration and analysis of event streams gets more important in the world of sensors, social media streams and Internet of Things. Events have to be accepted quickly and reliably, they have to be distributed and analyzed, often with many consumers or systems interested in all or part of the events. In this session we compare two popular Streaming Analytics solutions: Spark Streaming and Kafka Streams.
Spark is fast and general engine for large-scale data processing and has been designed to provide a more efficient alternative to Hadoop MapReduce. Spark Streaming brings Spark's language-integrated API to stream processing, letting you write streaming applications the same way you write batch jobs. It supports both Java and Scala.
Kafka Streams is the stream processing solution which is part of Kafka. It is provided as a Java library and by that can be easily integrated with any Java application.
This presentation shows how you can implement stream processing solutions with each of the two frameworks, discusses how they compare and highlights the differences and similarities.
Ilya Kosmodemiansky - An ultimate guide to upgrading your PostgreSQL installa...PostgreSQL-Consulting
Even an experienced PostgreSQL DBA can not always say that upgrading between major versions of Postgres is an easy task, especially if there are some special requirements, such as downtime limitations or if something goes wrong. For less experienced DBAs anything more complex than dump/restore can be frustrating.
In this talk I will describe why we need a special procedure to upgrade between major versions, how that can be achieved and what sort of problems can occur. I will review all possible ways to upgrade your cluster from classical pg_upgrade to old-school slony or modern methods like logical replication. For all approaches, I will give a brief explanation how it works (limited by the scope of this talk of course), examples how to perform upgrade and some advice on potentially problematic steps. Besides I will touch upon such topics as integration of upgrade tools and procedures with other software — connection brokers, operating system package managers, automation tools, etc. This talk would not be complete if I do not cover cases when something goes wrong and how to deal with such cases.
Custom DevOps Monitoring System in MelOn (with InfluxDB + Telegraf + Grafana)Seungmin Yu
2016년도 데이터야놀자에서 발표한 자료입니다.
멜론에서 InfluxDB + Telegraf + Grafana 조합으로 모니터링 시스템을 구축하고 활용한 사례를 발표한 내용입니다. 다양한 메트릭데이터와 DevOps 측면의 활용 가치에 대해서도 생각해 볼 수 있을 것 같습니다.
Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DBYugabyteDB
Slides for Amey Banarse's, Principal Data Architect at Yugabyte, "Distributed Databases Deconstructed: CockroachDB, TiDB and YugaByte DB" webinar recorded on Oct 30, 2019 at 11 AM Pacific.
Playback here: https://vimeo.com/369929255
Are you ready for the next attack? reviewing the sp security checklist (apnic...Barry Greene
Rethinking Security and how you can Act on Meaningful Change
What the industry recommends to protect your network is NOT working! The industry is stuck in a dysfunctional ecosystem that encourages the cyber-criminal innovation at the cost to business and individual loss throughout the world. We do not need a “Manhattan Project” for the security of the Internet. What we need are tools to help operators throughout the world ask the right question that would lead them to meaningful action. Security empowerment must empower the grassroots and provide the tools to push back on the root cause. This talk will explore these issues, highlight the dysfunction in our “security” economy, and present “take home” tools that would facilitate immediate action.
OpenDNS Enterprise Web Filtering allows organizations of all sizes to block websites at work. Choose from over 50 customizable categories. Use block page bypass to grant exceptions to your Web filtering policy. OpenDNS Enterprise offers web filtering without an appliance, can be deployed nearly instantly, and can be managed anywhere you have an Internet connection.
We browse the Internet. We host our applications on a server or a cloud that is hooked up with a nice domain name. That’s all there is to know about DNS, right? This talk is a refresher about how DNS works. How we can use it and how it can affect availability of our applications. How we can use it as a means of configuring our application components. How this old geezer protocol is a resilient, distributed system that is used by every Internet user in the world. How we can use it for things that it wasn’t built for. Come join me on this journey through the innards of the web!
BIND’s New Security Feature: DNSRPZ - the "DNS Firewall"Barry Greene
Learn how to turn your network’s DNS into a Security Tool! Webinar-Oct 12th
What do you do if the security tools are not protecting your network? Cyber-criminals are constantly finding ways to bypass your security tools and own your network. When the threat changes, you should grow with the threat - think out of the box – using tools that the criminals have not yet considered; the DNS.
ISC’s Internet Critical Open Source DNS software BIND has a new feature that would turn a DNS Caching Resolver into a tool to help protect your network from malware. All the computers in your network must contact your DNS Resolvers to get to the outside world. Your DNS Resolvers are critical “choke-point” for which all devices in your network must interact to get to the outside world. This "choke-point" is a logical choice to put security capabilities to check if a domain is "clean" or "dirty."
How can you have your DNS Resolver check if a domain is clean or dirty? Use BIND’s new feature – the DNS Response Policy Zone (DNSRPZ). DNSRPZ uses secure and fast zone transfer technologies to pull down black list of bad domains and put them into your DNS resolver.
The archived recording of the Webinar is here: www.isc.org/webinars
Who should watch this Webinar?
E-mail Administrators: Find out how DNSRPZ offers more effective way to work with the Anti-Spam black list.
Network Operators: Learn how DNSRPZ can be used inside your network to keep your users from being in-inadvertently infected by malware, zero-days, and malvertisements.
Security Engineers: Discover how DNSRPZ is a tool to help contain infections that get into your network and try to “call home” to a BOTNET controller.
Hosting Providers: By default, most of your hosting customers are using your DNS resolvers. Learn how DNSRPZ can help prevent and contain the threat of your customers getting infected.
Service Providers: Learn how to turn your DNS services into a tool to help protect all your customers from infection.
Mobile Telecoms Operators: Find a new tool that would prevent miscreant smart phone applications from calling home with DNS and infecting your customer’s phones.
SCADA and Critical Industrial System Operators: Learn how DNSRPZ is a tool to help protect legacy control systems that need DNS to work.
Speaking from experience building MyGet.org: users are insane. If you are lucky, they use your service, but in reality, they probably abuse. Crazy usage patterns resulting in more requests than expected, request bursts when users come back to the office after the weekend, and more! These all pose a potential threat to the health of our web application and may impact other users or the service as a whole. Ideally, we can apply some filtering at the front door: limit the number of requests over a given timespan, limiting bandwidth, ...
In this talk, we’ll explore the simple yet complex realm of rate limiting. We’ll go over how to decide on which resources to limit, what the limits should be and where to enforce these limits – in our app, on the server, using a reverse proxy like Nginx or even an external service like CloudFlare or Azure API management. The takeaway? Know when and where to enforce rate limits so you can have both a happy application as well as happy customers.
Karabük Üniversitesi Programlama Günleri - PostgreSQL Sunumuatifceylan
Karabük Üniversitesi Programlama Günleri'nin düzenlediği etkinlikte PostgreSQL Kullanıcıları ve Geliştiricileri Derneği adına Atıf Ceylan ve Hüseyin Mert'in ortaklaşa gerçekleştirdiği PostgreSQL Sunumu
Pig ve Hive ile Hadoop üzerinde Veri AnaliziHakan Ilter
Hadoop üzerinde Map Reduce programları yazmayı kolaylaştıran Pig ve Hive projesi ile ilgili Özgür Yazılım ve Linux Günleri 2013 organizasyonunda yaptığım sunum.
2. Select * from me ;Select * from me ;
'nde
okudu, algoritmalar ve veri tabanları ile
orada tanıştı.
ile karşılaşana dek birçok
veri tabanı ile çalıştı ama artık pek
tercih etmiyor.
Açık kaynak kod ve özgür yazılım seven
bir DBA. Çok az şey biliyor ve çok şey
öğrenmek istiyor, şu an 'de
çalışıyor.
Twitter :
Blog :
YTÜ Matematik Mühendisliği
PostgreSQL
Markafoni
@apatheticmagpie
kadinyazilimci.com
3. Neden PostgreSQL ÇokNeden PostgreSQL Çok
Güzel?Güzel?
(Atomicity, Consistency, Isolation, Durability)
Hot Standby
Streaming replication
/
ACID
MVCC Multi Version Concurrency Control
WAL Write-Ahead Logging
Point-in-Time Recovery
Standby server and high availability
Procedural languages
Partitioning Inheritance
Cost based optimiser
Multi platform support
Tablespaces
4. Neden PostgreSQL ÇokNeden PostgreSQL Çok
Güzel?Güzel?
( / )
: check constraints, unique
constraints, foreign keys, primary keys...
: , , ...
: MongoDB, Hadoop, Redis , MySQL
Triggers
Functions
Views Materialized Updatable
Constraint enforcement
Extension system hstore pg_stat_statements pg_trgm
Temporary tables
Unlogged tables
Foreign Data Wrappers
5. Postgres Yönetmek Çok Kolay!Postgres Yönetmek Çok Kolay!
pgAdminpgAdmin
Postgres'in grafik arayüzüdür. Sorgu analiz etme, çalışan sorguları
gözlemleme özellikleri mevcuttur. Kullandığınız özelliklerin kodlarını
görebilir, değiştirebilir ve düzenleyebilirsiniz.
7. Terminal ve psqlTerminal ve psql
psql Postgres'in etkileşimli (interaktif) terminalidir.
Komutlar size çok hız kazandıracaktır.
psql -h 127.0.0.1 -U gulcin -d pgday
l ve l+
c
dt ve dt+
di ve di+
d ve d+
du
dp
df
db
x
q
?
11. OS ConfigurationOS Configuration
Backup Logical&PhysicalBackup Logical&Physical
HA SetupHA Setup
MonitoringMonitoring
Log AnalyzingLog Analyzing
Bloat ManagementBloat Management
Anahtar GörevlerAnahtar Görevler
12. Yedekleme PolitikasıYedekleme Politikası
Tavsiye:Tavsiye: Backup and Recovery ManagerBackup and Recovery Manager
for PostgreSQLfor PostgreSQL
BarmanBarman
“ A good backup tool is not for keeping
backups, it's for keeping your job.
Simon Riggs
13. Optimizasyon YapmaOptimizasyon Yapma
System TuningSystem Tuning
OS TuningOS Tuning
Hardware TuningHardware Tuning
Performance TuningPerformance Tuning
Query TuningQuery Tuning
Index ManagementIndex Management
Software ConfigurationSoftware Configuration
15. Upgrade PlanlamaUpgrade Planlama
Versiyonlar arasındaki farkları listelemeVersiyonlar arasındaki farkları listeleme
Mevcut yapıya nasıl etkisi olacaMevcut yapıya nasıl etkisi olacağğını araını araşştırmatırma
Neler kazandıracaNeler kazandıracağğını hesaplama / öngörmeını hesaplama / öngörme
GeçiGeçişşi planlamai planlama
Kaynakları doKaynakları doğğru kullanmaru kullanma
Yenilikleri incelemeYenilikleri inceleme
pg_upgradepg_upgrade
16. SistemiSistemi İİzlemezleme
, , , gibi yazılımlarla veri tabanı
sunucularımızı ve veri tabanlarımızı kontrol edebilirsiniz.
Tavsiye: bir projesidir.
check_postgres veri tabanımızın çeşitli özelliklerini izleyip kontrol
edebilmemize yarayan bir betiktir. Nagios gibi yazılımlarla veya
bağımsız betiklerle çalışabilecek şekilde tasarlanmıştır.
Nagios PRTG New Relic Cacti
check_postgres bucardo
17. Sistemi Analiz EtmeSistemi Analiz Etme
Logları toplayıp analiz edersek çok daha iyi anlamış oluruz. Bunun
için aşağıdaki araçları kullanabilirsiniz.
Log analiz etmek üzere tasarlanmış bu araçlar log incelemenizi ve
bunlardan yola çıkarak kararlar almanızı sağlayacaktır.
pg_fouine
pgbadger
pgCluu
19. Postgres ve DBA HayatıPostgres ve DBA Hayatı
İşleri olabildiğince otomatize edin.
Bir yedekleme politikanız olsun.
Yedekleriniz güvenli ve kullanılabilir olsun.
Tablo ve dizin (index) boyutlarının artışını kontrol edin.
Uzun süren sorguları loglayın ve bu sorguları düzenli aralıklarla
iyileştirin.
Loglara düşen hataları inceleyin ve nasıl bir soruna işaret
ettiklerini anlamaya çalışın, araştırın.
Vacuum analyze, autovacuum, full vacuum işlerini planlayın.
Veri tabanı kilitleri hakkında fikir edinin ve nasıl izleyip kontrol
edeceğinizi bilin.
20. Postgres ve DBA HayatıPostgres ve DBA Hayatı
İşleri otomatize etmek için 'crontab' komutu çok faydalı olacaktır.
Yedekleme, vacuum yapma gibi rutinler her DBA'in hayatını kurtaran
faydalı alışkanlıklardır.
gulcin# crontab -l
00 02 * * * sh /home/postgres/scripts/getbackup.sh
0 05 * * * sh /home/postgres/scripts/restore_test_db.sh
#WAL Archive CleanUp
0 02 * * * sh /var/lib/pgsql/removewal_archive.sh
crontab -e // crontab dosyasını düzenlemeye yarar.
# * * * * * çalıştırılacak komut
# ! ! ! ! !
# " " " " "
# " " " " "
# " " " " #$$$$$ haftanın günü (0 - 7) (0'dan 6'ya Pazar'dan Cumartesi'ye demektir; 7 Pazar, 0
da Pazar.)
# " " " #$$$$$$$$$$ ay (1 - 12)
# " " #$$$$$$$$$$$$$$$ ayın günü (1 - 31)
# " #$$$$$$$$$$$$$$$$$$$$ saat (0 - 23)
# #$$$$$$$$$$$$$$$$$$$$$$$$$ dakika (0 - 59)
21. Git kullanın!Git kullanın!
çok güzel. ile hemen öğren.
apt-get install git // Debian tabanlı dağıtım Ubuntu gibi.
yum install git // RHEL
yum install git-core // Fedora vs.
Gitlab Demo
ssh-keygen -t rsa -C "yildirim.gulcin88@gmail.com"
cat ~/.ssh/id_rsa.pub
git config --global user.name "Gulcin Yildirim"
git config --global user.email "yildirim.gulcin88@gmail.com"
mkdir pgday
cd pgday
git init
touch README
git add README
git commit -m 'Welcome to PGDay İstanbul 2015!'
git remote add origin git@demo.gitlab.com:gitlab/pgday.git
git push -u origin master
22. Nereden BaNereden Başşlayayım?layayım?
Postgres kaydolun.
Günde 1 mail ile ne kadar çok şey öğrenebileceğinize inanamazsınız.
: PostgreSQL yönetimi
: Kullanıcılar için genel bir tartışma alanı
: Postgres ve ona bağlı servis duyuruları
: Postgres performansına ilişkin konular
blogunu takip edin.
( , , , , ,
, , , , )
mail listelerine
pgsql-admin
pgsql-general
psql-announce
psql-performance
Planet PostgreSQL
2ndQuadrant pgExperts VMware OmniTI EnterpriseDB
EndPoint credativ Cybertec CommandPrompt OpenSCG
23. Postgres ÖPostgres Öğğrenmenin ilkrenmenin ilk
yolu: Oku!yolu: Oku!
Karşılaştığınız her konsept için yazılmış
bulup okuyun.
Postgres belgeleme konusunda en zengin açık kaynak
kodlu projelerden biridir.
Çok sık kullandığınız özellikleri bile okuyun çünkü ufak bir
detay hayat kurtarıcı olabilir.
"Why do I love Postgres?
- Because I'm not a DBA.
PostgreSQL
belgesini
