The document discusses deploying a Citus high availability environment using Patroni. It begins with an introduction and agenda. It then covers service discovery with Consul, dynamic configuration using ConfD and Consul templates, high availability with Patroni, and distributed PostgreSQL with Citus. Key points include that Patroni allows customized PostgreSQL high availability solutions, Citus enables scaling out PostgreSQL across nodes, and the demo would show integrating these for a production-ready scalable and highly available database cluster.
Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure.
There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul.
Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes.
Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
How to do a LIVE-demo with minikube:
1. git clone https://github.com/zalando/patroni
2. cd patroni
3. git checkout feature/demo
4. cd kubernetes
5. open demo.sh and edit line #4 (specify the minikube context )
6. docker build -t patroni .
7. may be docker push patroni
8. may be edit patroni_k8s.yaml line #22 and put the name of patroni image you build there
9. install tmux
10. run tmux in one terminal
11. run bash demo.sh in another terminal and press Enter from time to time
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
In 40 minutes the audience will learn a variety of ways to make postgresql database suddenly go out of memory on a box with half a terabyte of RAM.
Developer's and DBA's best practices for preventing this will also be discussed, as well as a bit of Postgres and Linux memory management internals.
Kubernetes is a solid leader among different cloud orchestration engines and its adoption rate is growing on a daily basis. Naturally people want to run both their applications and databases on the same infrastructure.
There are a lot of ways to deploy and run PostgreSQL on Kubernetes, but most of them are not cloud-native. Around one year ago Zalando started to run HA setup of PostgreSQL on Kubernetes managed by Patroni. Those experiments were quite successful and produced a Helm chart for Patroni. That chart was useful, albeit a single problem: Patroni depended on Etcd, ZooKeeper or Consul.
Few people look forward to deploy two applications instead of one and support them later on. In this talk I would like to introduce Kubernetes-native Patroni. I will explain how Patroni uses Kubernetes API to run a leader election and store the cluster state. I’m going to live-demo a deployment of HA PostgreSQL cluster on Minikube and share our own experience of running more than 130 clusters on Kubernetes.
Patroni is a Python open-source project developed by Zalando in cooperation with other contributors on GitHub: https://github.com/zalando/patroni
How to do a LIVE-demo with minikube:
1. git clone https://github.com/zalando/patroni
2. cd patroni
3. git checkout feature/demo
4. cd kubernetes
5. open demo.sh and edit line #4 (specify the minikube context )
6. docker build -t patroni .
7. may be docker push patroni
8. may be edit patroni_k8s.yaml line #22 and put the name of patroni image you build there
9. install tmux
10. run tmux in one terminal
11. run bash demo.sh in another terminal and press Enter from time to time
This ppt was used by Devrim at pgDay Asia 2017. He talked about some important facts about WAL - Transaction Logs or xlogs in PostgreSQL. Some of these can really come handy on a bad day
In 40 minutes the audience will learn a variety of ways to make postgresql database suddenly go out of memory on a box with half a terabyte of RAM.
Developer's and DBA's best practices for preventing this will also be discussed, as well as a bit of Postgres and Linux memory management internals.
There are many ways to run high availability with PostgreSQL. Here, we present a template for you to create your own customized, high-availability solution using Python and for maximum accessibility, a distributed configuration store like ZooKeeper or etcd.
Introduction to Vacuum Freezing and XIDPGConf APAC
These are slides which were used by Masahiko Sawada of NTT, Japan for his presentation at pgDay Asia. He spoke about internals of VACCUM and XID Wraparound issue of PosgreSQL.
Spencer Christensen
There are many aspects to managing an RDBMS. Some of these are handled by an experienced DBA, but there are a good many things that any sys admin should be able to take care of if they know what to look for.
This presentation will cover basics of managing Postgres, including creating database clusters, overview of configuration, and logging. We will also look at tools to help monitor Postgres and keep an eye on what is going on. Some of the tools we will review are:
* pgtop
* pg_top
* pgfouine
* check_postgres.pl.
Check_postgres.pl is a great tool that can plug into your Nagios or Cacti monitoring systems, giving you even better visibility into your databases.
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.
In recent years Zalando has adopted a decentralized setup for applications and databases. This has impacted our database engineers by transferring responsibility to small teams, each of which manages its own infrastructure. Decentralization is great for team autonomy, but can present challenges in terms of how to easily manage lots of PostgreSQL clusters. That’s why our team created Spilo: an open source HA-cluster (highly available PostgreSQL cluster). This talk will show how Spilo simplifies Postgres cluster management while preserving team autonomy. By building upon streaming replication, Spilo provides a set of clusters that require no human interaction for many administration tasks and most failure scenarios; takes care of managing the number of servers (adding and removing them); and creates backups. It implements our own version of Patroni (https://github.com/zalando/patroni): a process, derived from Compose’s Governor, that governs the Postgres cluster (promoting and demoting) and updates information in etcd (the distributed consensus key/value store created by CoreOS). I’ll explore the architecture of Patroni implemented with Spilo; a live demo will show some failovers as they occur. Finally, I’ll show how Spilo combines Patroni with cloud infrastructure architecture components (for example, AWS), adding autoscaling to run a HA-cluster and allowing AWS power users to create a new HA-cluster with very little effort. Spilo relies upon STUPS, Zalando’s open-source platform as a service (PaaS) for enabling multiple, autonomous teams to use AWS while remaining audit-compliant. By using Spilo and STUPS together, our engineers can create a new HA-cluster with just a few commands. After attending this talk the audience will understand how they can also use Spilo, Patroni and STUPS to manage their Postgres clusters more efficiently while working autonomously.
This technical presentation shows you the best practices with EDB Postgres tools, that are designed to make database administration easier and more efficient:
● Tune a new database using Postgres Expert
● Set up streaming replication in EDB Postgres Enterprise Manager (PEM)
● Create a backup schedule in EDB Postgres Backup and Recovery
● Automatically failover with EDB Postgres Failover Manager
● Use SQL Profiler and Index Advisor to add indexes
The presentation also included a demonstration. To access the recording visit www.enterprisedb.com and access the webcast recordings section or email info@enterprisedb.com.
PostgreSQL Tutorial for Beginners | EdurekaEdureka!
YouTube Link: https://youtu.be/-VO7YjQeG6Y
** MYSQL DBA Certification Training https://www.edureka.co/mysql-dba **
This Edureka PPT on PostgreSQL Tutorial For Beginners (blog: http://bit.ly/33GN7jQ) will help you learn PostgreSQL in depth.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
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Operating PostgreSQL at Scale with KubernetesJonathan Katz
The maturation of containerization platforms has changed how people think about creating development environments and has eliminated many inefficiencies for deploying applications. These concept and technologies have made its way into the PostgreSQL ecosystem as well, and tools such as Docker and Kubernetes have enabled teams to run their own “database-as-a-service” on the infrastructure of their choosing.
All this sounds great, but if you are new to the world of containers, it can be very overwhelming to find a place to start. In this talk, which centers around demos, we will see how you can get PostgreSQL up and running in a containerized environment with some advanced sidecars in only a few steps! We will also see how it extends to a larger production environment with Kubernetes, and what the future holds for PostgreSQL in a containerized world.
We will cover the following:
* Why containers are important and what they mean for PostgreSQL
* Create a development environment with PostgreSQL, pgadmin4, monitoring, and more
* How to use Kubernetes to create your own "database-as-a-service"-like PostgreSQL environment
* Trends in the container world and how it will affect PostgreSQL
At the conclusion of the talk, you will understand the fundamentals of how to use container technologies with PostgreSQL and be on your way to running a containerized PostgreSQL environment at scale!
There are many ways to run high availability with PostgreSQL. Here, we present a template for you to create your own customized, high-availability solution using Python and for maximum accessibility, a distributed configuration store like ZooKeeper or etcd.
Introduction to Vacuum Freezing and XIDPGConf APAC
These are slides which were used by Masahiko Sawada of NTT, Japan for his presentation at pgDay Asia. He spoke about internals of VACCUM and XID Wraparound issue of PosgreSQL.
Spencer Christensen
There are many aspects to managing an RDBMS. Some of these are handled by an experienced DBA, but there are a good many things that any sys admin should be able to take care of if they know what to look for.
This presentation will cover basics of managing Postgres, including creating database clusters, overview of configuration, and logging. We will also look at tools to help monitor Postgres and keep an eye on what is going on. Some of the tools we will review are:
* pgtop
* pg_top
* pgfouine
* check_postgres.pl.
Check_postgres.pl is a great tool that can plug into your Nagios or Cacti monitoring systems, giving you even better visibility into your databases.
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.
In recent years Zalando has adopted a decentralized setup for applications and databases. This has impacted our database engineers by transferring responsibility to small teams, each of which manages its own infrastructure. Decentralization is great for team autonomy, but can present challenges in terms of how to easily manage lots of PostgreSQL clusters. That’s why our team created Spilo: an open source HA-cluster (highly available PostgreSQL cluster). This talk will show how Spilo simplifies Postgres cluster management while preserving team autonomy. By building upon streaming replication, Spilo provides a set of clusters that require no human interaction for many administration tasks and most failure scenarios; takes care of managing the number of servers (adding and removing them); and creates backups. It implements our own version of Patroni (https://github.com/zalando/patroni): a process, derived from Compose’s Governor, that governs the Postgres cluster (promoting and demoting) and updates information in etcd (the distributed consensus key/value store created by CoreOS). I’ll explore the architecture of Patroni implemented with Spilo; a live demo will show some failovers as they occur. Finally, I’ll show how Spilo combines Patroni with cloud infrastructure architecture components (for example, AWS), adding autoscaling to run a HA-cluster and allowing AWS power users to create a new HA-cluster with very little effort. Spilo relies upon STUPS, Zalando’s open-source platform as a service (PaaS) for enabling multiple, autonomous teams to use AWS while remaining audit-compliant. By using Spilo and STUPS together, our engineers can create a new HA-cluster with just a few commands. After attending this talk the audience will understand how they can also use Spilo, Patroni and STUPS to manage their Postgres clusters more efficiently while working autonomously.
This technical presentation shows you the best practices with EDB Postgres tools, that are designed to make database administration easier and more efficient:
● Tune a new database using Postgres Expert
● Set up streaming replication in EDB Postgres Enterprise Manager (PEM)
● Create a backup schedule in EDB Postgres Backup and Recovery
● Automatically failover with EDB Postgres Failover Manager
● Use SQL Profiler and Index Advisor to add indexes
The presentation also included a demonstration. To access the recording visit www.enterprisedb.com and access the webcast recordings section or email info@enterprisedb.com.
PostgreSQL Tutorial for Beginners | EdurekaEdureka!
YouTube Link: https://youtu.be/-VO7YjQeG6Y
** MYSQL DBA Certification Training https://www.edureka.co/mysql-dba **
This Edureka PPT on PostgreSQL Tutorial For Beginners (blog: http://bit.ly/33GN7jQ) will help you learn PostgreSQL in depth.
Follow us to never miss an update in the future.
YouTube: https://www.youtube.com/user/edurekaIN
Instagram: https://www.instagram.com/edureka_learning/
Facebook: https://www.facebook.com/edurekaIN/
Twitter: https://twitter.com/edurekain
LinkedIn: https://www.linkedin.com/company/edureka
Castbox: https://castbox.fm/networks/505?country=in
Operating PostgreSQL at Scale with KubernetesJonathan Katz
The maturation of containerization platforms has changed how people think about creating development environments and has eliminated many inefficiencies for deploying applications. These concept and technologies have made its way into the PostgreSQL ecosystem as well, and tools such as Docker and Kubernetes have enabled teams to run their own “database-as-a-service” on the infrastructure of their choosing.
All this sounds great, but if you are new to the world of containers, it can be very overwhelming to find a place to start. In this talk, which centers around demos, we will see how you can get PostgreSQL up and running in a containerized environment with some advanced sidecars in only a few steps! We will also see how it extends to a larger production environment with Kubernetes, and what the future holds for PostgreSQL in a containerized world.
We will cover the following:
* Why containers are important and what they mean for PostgreSQL
* Create a development environment with PostgreSQL, pgadmin4, monitoring, and more
* How to use Kubernetes to create your own "database-as-a-service"-like PostgreSQL environment
* Trends in the container world and how it will affect PostgreSQL
At the conclusion of the talk, you will understand the fundamentals of how to use container technologies with PostgreSQL and be on your way to running a containerized PostgreSQL environment at scale!
Lightning Talk: Why and How to Integrate MongoDB and NoSQL into Hadoop Big Da...MongoDB
Drawn from Think Big's experience on real-world client projects, Think Big Academy Director and Principal Architect Jeffrey Breen will review specific ways to integrate NoSQL databases into Hadoop-based Big Data systems: preserving state in otherwise stateless processes; storing pre-computed metrics and aggregates to enable interactive analytics and reporting; and building a secondary index to provide low latency, random access to data stored stored on the high latency HDFS. A working example of secondary indexing is presented in which MongoDB is used to index web site visitor locations from Omniture clickstream data stored on HDFS.
Time series Analytics - a deep dive into ADX Azure Data Explorer @Data Saturd...Riccardo Zamana
Time series Analytics - a deep dive into ADX Azure Data Explorer. Let’s discover with a step-by-step approach the entire ecosystem of features driven by Azure Data eXplorer.
Lightning Talk: Why and How to Integrate MongoDB and NoSQL into Hadoop Big Da...MongoDB
Drawn from Think Big's experience on real-world client projects, Think Big Academy Director and Principal Architect Jeffrey Breen will review specific ways to integrate NoSQL databases into Hadoop-based Big Data systems: preserving state in otherwise stateless processes; storing pre-computed metrics and aggregates to enable interactive analytics and reporting; and building a secondary index to provide low latency, random access to data stored stored on the high latency HDFS. A working example of secondary indexing is presented in which MongoDB is used to index web site visitor locations from Omniture clickstream data stored on HDFS.
Using PostgreSQL With Docker & Kubernetes - July 2018Jonathan Katz
The maturation of containerization platforms has changed how people think about creating development environments and has eliminated many inefficiencies for deploying applications. These concept and technologies have made its way into the PostgreSQL ecosystem as well, and tools such as Docker and Kubernetes have enabled teams to run their own “database-as-a-service” on the infrastructure of their choosing.
In this talk, we will cover the following:
- Why containers are important and what they mean for PostgreSQL
- Setting up and managing a PostgreSQL along with pgadmin4 and monitoring
- Running PostgreSQL on Kubernetes with a Demo
- Trends in the container world and how it will affect PostgreSQL
Enterprise guide to building a Data MeshSion Smith
Making Data Mesh simple, Open Source and available to all; without vendor lock-in, without complex tooling and to use an approach centered around ‘specifications’, existing tools and baking in a ‘domain’ model.
Apache Druid Auto Scale-out/in for Streaming Data Ingestion on KubernetesDataWorks Summit
The importance of ingestion and processing streaming data in telecommunication industry is ever increasing. We, SK Telecom which is Korea's number-one telecommunications provider, encounter how to use infra resources more efficiently. Apache Druid supports auto scaling feature for data ingestion, but it is only available on AWS EC2. We cannot rely on the feature on our private cloud.
In this talk, we are going to introduce auto scale-out/in on Kubernetes. This approach is more outstanding than Druid's scaling implementation. Here are the benefits. The first is our approach can be used anywhere on private cloud or (managed) Kubernetes in Azure, AWS and GKE. The second is AWS EC2's startup and termination requires a few minutes, but our approach requires a few seconds. The last is the scaling mechanism is decoupled from Druid's source code. We will also share development of Druid Helm chart, rolling update, custom metric usage for horizontal auto scaling.
The below is about detailed benefit compared with Druid's auto scaling approach:
1. Druid's auto scaling is only available in AWS, but our approach does not have the obstacle. It can be used in Private cloud(on-premise) are (managed) Kubernetes in Azure, AWS and GKE.
2. AWS EC2 is an instance of virtual machine, so the startup is slower than docker container. A few minutes are required for startup or termination of EC2. Docker container is very lightweight, so it requires a few seconds.
3. Druid's auto scaling is tightly coupled with AWS API because Druid engine code uses AWS API. Our scale-out/in algorithm is conceptually equal to Druid's auto scaling approach, but we decoupled the dependency because Kubernetes communicate with one of dispatcher nodes(i.e. Overlord node) using REST API.
Qu'elles soient, big ou small, structurées ou semi structurées, relationnelles ou pas, nous vous proposons un tour des solutions data dans Azure.
Vidéo disponible ici : https://youtu.be/6D4jAcxfWCQ.
Having used Jenkins with more than 30 projects during 8 years, it was time to switch to another build manager. Written in Ada, Porion is a new build manager intended to replace Jenkins by providing more security, safety and performance.
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GlobusWorld 2021 Tutorial: Globus for System AdministratorsGlobus
An overview of installing and configuring a Globus endpoints on your storage system. This tutorial was presented at the GlobusWorld 2021 conference in Chicago, IL by Vas Vasiliadis.
Access Data from XPages with the Relational ControlsTeamstudio
Did you know that Domino and XPages allows for the easy access of relational data? These exciting capabilities in the Extension Library can greatly enhance the capability of your applications and allow access to information beyond Domino. Howard and Paul will discuss what you need to get started, what controls allow access to relational data, and the new @Functions available to incorporate relational data in your Server Side JavaScript programming.
MySQL 5.7 New Features for Developers session for DOAG (Oracle user group conference) in 2016. A similar version was also presented in Israel MySQL User Group on November 2016.
This presentation review new features in MySQL 5.7: Optimizer, InnoDB engine, JSON native data type, performance and sys schemas
Robert Bates, SVP Sales Engineering of Crunchy Data explains how you can tackle Data Gravity, Kubernetes, and strategies/best practices to run, scale, and leverage stateful containers in production.
Geek Sync | Deployment and Management of Complex Azure EnvironmentsIDERA Software
You can watch the replay of this Geek Sync webinar in the IDERA Resource Center: http://ow.ly/pg7N50A4svf.
Today's data management professional is finding their landscape changing. They have multiple database platforms to manage, multi-OS environments and everyone wants it now.
Join IDERA and Kellyn Pot’Vin-Gorman as she discusses the power of auto deployment in Azure when faced with complex environments and tips to increase the knowledge you need at the speed of light. Kellyn will cover scripting basics, advanced Portal features, opportunities to lessen the learning curve and how multi-platform and tier doesn't have to mean multi-cloud.
Attendees can expect to learn how to build automation scripts efficiently, even if you have little scripting experience, and how to work with Azure automation deployments. This session will allow you to begin building a repository of multi-platform development scripts to use as needed.
About Kellyn: Kellyn Pot’Vin-Gorman is a member of the Oak Table Network and an IDERA ACE and Oracle ACE Director alumnus. She is the newest Technical Solution Professional in Power BI with AI in the EdTech group at Microsoft. Kellyn is known for her extensive work with multi-database platforms, DevOps, cloud migrations, virtualization, visualizations, scripting, environment optimization tuning, automation, and architecture design. She has spoken at numerous technical conferences for Oracle, Big Data, DevOps, Testing and SQL Server. Her blog, http://dbakevlar.com and social media activity under her handle, DBAKevlar is well respected for her insight and content.
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Do you want Software for your Business? Visit Deuglo
Deuglo has top Software Developers in India. They are experts in software development and help design and create custom Software solutions.
Deuglo follows seven steps methods for delivering their services to their customers. They called it the Software development life cycle process (SDLC).
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AI Fusion Buddy Review: Key Features
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patroni-based citrus high availability environment deployment
1. Patroni-based citus high availability
environment deployment
( 基于Patroni的Citus高可用环境部署 )
PGDay.Seoul & PGConf.Asia 2021
Daniel Lee
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 1
2. About Me
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 2
• Dainel lee ( 李炯彩 )
• Community
• MySQL Korea User Group
• facebook.com/groups/mysqlko
• PostgreSQL Korea
• facebook.com/groups/130019777169719
• Github
• github.com/dbdbdeep-git/pgday-seoul-2021-demo
3. Agenda
1. Service Discovery ( *Service Mesh )
• CoreOS’s ETCD
• Hashicorp’s Consul
2. Dynamic Configuration Management
• ConfD
• Hashicorp’s Consul-Template
3. High-Availability
• Zalando’s Patroni
4. Distributed PostgreSQL as an extension
• Citusdata’s Citus
5. Demo
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 3
6. What is …
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 6
Lock
Service
(chubby)
Coordination
Service
(zookeeper,eureka,etcd)
Service Discovery
(surf,skydns,consul)
Service Mesh
(lstio,linkerd2)
7. What can you do with Consul?
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 7
Service Discovery
for connectivity
Service Registry enables services to
register and discover each other.
Service Segmentation
for security
Secure service-to-service communication
with automatic TLS encryption and
identity-based authorization.
Service Configuration
for runtime configuration
Feature rich Key/Value store to easily
configure services.
8. What can you do with Consul?
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Consul-Kubernetes Deployments
Use Consul service discovery and
service mesh features with Kubernetes.
Secure Service Communication
Secure and observe communication between
your services without modifying their code.
Dynamic Load Balancing
Automate load balancer configuration with
Consul and HAProxy, Nginx, or F5.
9. 3 Marine Admirals
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 9
Properties Consul Etcd Zookeeper
User Interface Available X X
RPC Available Available
Health Check HTTP API HTTP API TCP
Key Value
3 Consistency modes
(sync)
Good Consistency
(semi)
Strong Consistency
Token System Available X X
Language Golang Golang Java
Security ACL / HTTPS HTTPS ACL
Spring Cloud O O O
Multi
Datacenter(gossip)
O X X
11. ConfD
• http://www.confd.io
• Manage local application configuration files using templates and
data from etcd or consul
• A lightweight configuration management tool focused on:
• keeping local configuration files up-to-date using data stored in etcd,
consul, dynamodb, redis, vault, zookeeper, aws ssm parameter store or
env vars and processing template resources.
• reloading applications to pick up new config file changes
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 11
12. ConfD or Consul-template Architecture
2021-11-24 PGDay.Seoul & PGConf.Asia 2021 12
ETCD or Consul
Server
Confd or
Consul-template
Service
Application
(HAproxy, PostgreSQL)
Configuration
Template
File
Application
Configuration
File
listen
generate
haproxy.cfg.tmpl haproxy.cfg
reload
check
reload
update
13. PostgreSQL Client authentication
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Consul Server
Consul-template
Service
Postgres Server
Configuration
Template
File
Application
Configuration
File
listen
generate
pg_hba.conf.tmpl pg_hba.conf
reload
check
reload
update
$ consul kv put
service/database/primary/auth/client
“host all haproxy 10.0.1.0/24 reject”
16. ’s Patroni
• Patroni is a template for you to create your own customized, high-availability solution using
Python and - for maximum accessibility - a DCS (Distributed Configuration Store)
like ZooKeeper, etcd, Consul or Kubernetes.
• Currently supported PostgreSQL versions: 9.3 to 14.
• Release lastest 2.1.1 ( 09.11.21 )
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17. ’s Spilo
• Spilo is a Docker image that provides PostgreSQL and Patroni bundled
together. Patroni is a template for PostgreSQL HA. Multiple Spilos can create
a resilient High Available PostgreSQL cluster. For this, you'll need to start all
participating Spilos with identical etcd addresses and cluster names.
• https://github.com/zalando/spilo
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24. Citus 란?
• PostgreSQL로 스케일 아웃 환경 실현
• 다중 노드에 걸친 병렬 쿼리 및 파티셔닝 기능
• 처리량 확대를 목표로
• PostgreSQL 확장(EXTENSION)으로 구현
• PostgreSQL 본체 변경 없음
• Citus Data (https://www.citusdata.com/) 개발
• 2019년 1월 Microsoft에서 인수
• Azure Database for PostgreSQL - Hyperscale (Citus)의 핵심 기술입니다.
• 오픈 소스 버전도 제공 (https://github.com/citusdata/citus)
• 다음 기능은 포함되지 않음
• 자동 장애 조치
• 자동 데이터 재조정
• 백업 등의 운용 기능
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25. What is Citus ?
• Achieve a scale-out environment with PostgreSQL
• Parallel query and partitioning capabilities across multiple nodes
• Aim to increase throughput
• Implemented as an extension of PostgreSQL (EXTENSION)
• No changes to PostgreSQL itself
• Developed by Citus Data (https://www.citusdata.com/)
• Acquired by Microsoft in January 2019
• Azure Database for PostgreSQL-is the core technology of Hyperscale (Citus)
• Open source version is also available (https://github.com/citusdata/citus)
• The following functions are not included
• Automatic failover
• Automatic data rebalancing
• Operational functions such as backup
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26. What is Citus ? by Noriyoshi Shinoda
Instance configuration
• Coordinator Node
• A PostgreSQL instance that accepts connections from clients
• Manage metadata
• Worker Node
• PostgreSQL instance that actually stores the data
• No communication between Worker Nodes
• Install citus EXTENSION on all nodes
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27. What is Citus ? by Noriyoshi Shinoda
Instance configuration
• Processing performed by Coordinator Node
• Accepting connections from clients
• Final sort (ORDER BY)
• Sequence processing (including SERIAL column and GENERATED AS
IDENTITY column)
• Handling objects other than tables and indexes
• Processing executed by Worker Node
• Processing SQL statements requested by Coordinator Node
• Execution of ANALYZE statement
• Execution of VACUUM statement
• Retaining table data
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28. CREATE EXTENSION citus;
• Add nodes:
postgres=> SELECT master_add_node(‘worker-01_ip_or_dns’, 5432);
Postgres=> SELECT master_add_node(’worker-02_ip_or_dns’, 5432);
• Create distributed table:
postgres=> CREATE TABLE events ( orders_id int, ... );
postgres=> SELECT create_distributed_table( ‘orders', ‘orders_id’ );
• Events is now distributed across shards on the nodes
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30. Table structure by Noriyoshi Shinoda
Distributed table
• A table that distributes and stores data
• Suitable for fact tables
• Specify a column as the distribution key
(default determines the distribution destination table by the hash value range)
• The number of divisions can be specified
• citus.shard_count (default value 32)
• Replicas can be created on different Worker Nodes
• citus.shard_replication_factor (default value 1 = no replica)
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31. Table structure by Noriyoshi Shinoda
Distributed table
• Table created in worker Node
• For the table name, ShardID is added to the original table name.
• If a replica is specified, a table with the same name will be created in a different Worker Node.
• Same data is stored in the table with the same name
• Search the citus_shards catalog to see the table names created by the Worker Node
postgres=> SET citus.shard_count = 6 ;
postgres=> SET citus.shard_replication_factor = 2 ;
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Coordinator Worker#1 Worker#2 Worker#3
Dist1
dist1_102046 dist1_102046
dist1_102047 dist1_102047
dist1_102048 dist1_102048
dist1_102049 dist1_102049
dist1_102050 dist1_102050
dist1_102051 dist1_102051