ºÝºÝߣshows by User: vyruss000 / http://www.slideshare.net/images/logo.gif ºÝºÝߣshows by User: vyruss000 / Thu, 09 Feb 2023 11:01:36 GMT ºÝºÝߣShare feed for ºÝºÝߣshows by User: vyruss000 Don't Do This [FOSDEM 2023] /vyruss000/dont-do-this-fosdem-2023 dontdothis-230209110136-5b79c747
Based on the legendary "Don't Do This" PostgreSQL wiki page, this talk explores some of the common pitfalls and misconceptions that Postgres users can face - and shows possible ways to undo them or workarounds. Some of the things discussed: - Bad SQL habits - Correct types for data storage - (Sub-)Partitioning (and how to get it wrong) - Table inheritance (and how to undo it) - Connections (number of, and properly handling) - Security issues (unsafe configurations and usage) Talk given at FOSDEM 2023]]>
Based on the legendary "Don't Do This" PostgreSQL wiki page, this talk explores some of the common pitfalls and misconceptions that Postgres users can face - and shows possible ways to undo them or workarounds. Some of the things discussed: - Bad SQL habits - Correct types for data storage - (Sub-)Partitioning (and how to get it wrong) - Table inheritance (and how to undo it) - Connections (number of, and properly handling) - Security issues (unsafe configurations and usage) Talk given at FOSDEM 2023]]> Thu, 09 Feb 2023 11:01:36 GMT /vyruss000/dont-do-this-fosdem-2023 vyruss000@slideshare.net(vyruss000) Don't Do This [FOSDEM 2023] vyruss000 Based on the legendary "Don't Do This" PostgreSQL wiki page, this talk explores some of the common pitfalls and misconceptions that Postgres users can face - and shows possible ways to undo them or workarounds. Some of the things discussed: - Bad SQL habits - Correct types for data storage - (Sub-)Partitioning (and how to get it wrong) - Table inheritance (and how to undo it) - Connections (number of, and properly handling) - Security issues (unsafe configurations and usage) Talk given at FOSDEM 2023 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/dontdothis-230209110136-5b79c747-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Based on the legendary &quot;Don&#39;t Do This&quot; PostgreSQL wiki page, this talk explores some of the common pitfalls and misconceptions that Postgres users can face - and shows possible ways to undo them or workarounds. Some of the things discussed: - Bad SQL habits - Correct types for data storage - (Sub-)Partitioning (and how to get it wrong) - Table inheritance (and how to undo it) - Connections (number of, and properly handling) - Security issues (unsafe configurations and usage) Talk given at FOSDEM 2023
Don't Do This [FOSDEM 2023] from Jimmy Angelakos
]]> 16 0 https://cdn.slidesharecdn.com/ss_thumbnails/dontdothis-230209110136-5b79c747-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Slow things down to make them go faster [FOSDEM 2022] /slideshow/slow-things-down-to-make-them-go-faster-fosdem-2022/251118836 slowthingsdownfosdem-220206162647
Talk from FOSDEM 2022 It's easy to get misled into overconfidence based on the performance of powerful servers, given today's monster core counts and RAM sizes. However, the reality of high concurrency usage is often disappointing, with less throughput than one would expect. Because of its internals and its multi-process architecture, PostgreSQL is very particular about how it likes to deal with high concurrency and in some cases it can slow down to the point where it looks like it's not performing as it should. In this talk we'll take a look at potential pitfalls when you throw a lot of work at your database. Specifically, very high concurrency and resource contention can cause problems with lock waits in Postgres. Very high transaction rates can also cause problems of a different nature. Finally, we will be looking at ways to mitigate these by examining our queries and connection parameters, leveraging connection pooling and replication, or adapting the workload. Topics: 1. Understand what we mean by high concurrency. 2. Understand ACID & MVCC in Postgres. 3. Understand how high concurrency affects Postgres performance. 4. Understand how locks/latches affect Postgres performance. 5. Understand how high transaction rates can affect Postgres. 6. Mitigation strategies for high concurrency scenarios. ]]>
Talk from FOSDEM 2022 It's easy to get misled into overconfidence based on the performance of powerful servers, given today's monster core counts and RAM sizes. However, the reality of high concurrency usage is often disappointing, with less throughput than one would expect. Because of its internals and its multi-process architecture, PostgreSQL is very particular about how it likes to deal with high concurrency and in some cases it can slow down to the point where it looks like it's not performing as it should. In this talk we'll take a look at potential pitfalls when you throw a lot of work at your database. Specifically, very high concurrency and resource contention can cause problems with lock waits in Postgres. Very high transaction rates can also cause problems of a different nature. Finally, we will be looking at ways to mitigate these by examining our queries and connection parameters, leveraging connection pooling and replication, or adapting the workload. Topics: 1. Understand what we mean by high concurrency. 2. Understand ACID & MVCC in Postgres. 3. Understand how high concurrency affects Postgres performance. 4. Understand how locks/latches affect Postgres performance. 5. Understand how high transaction rates can affect Postgres. 6. Mitigation strategies for high concurrency scenarios. ]]> Sun, 06 Feb 2022 16:26:46 GMT /slideshow/slow-things-down-to-make-them-go-faster-fosdem-2022/251118836 vyruss000@slideshare.net(vyruss000) Slow things down to make them go faster [FOSDEM 2022] vyruss000 Talk from FOSDEM 2022 It's easy to get misled into overconfidence based on the performance of powerful servers, given today's monster core counts and RAM sizes. However, the reality of high concurrency usage is often disappointing, with less throughput than one would expect. Because of its internals and its multi-process architecture, PostgreSQL is very particular about how it likes to deal with high concurrency and in some cases it can slow down to the point where it looks like it's not performing as it should. In this talk we'll take a look at potential pitfalls when you throw a lot of work at your database. Specifically, very high concurrency and resource contention can cause problems with lock waits in Postgres. Very high transaction rates can also cause problems of a different nature. Finally, we will be looking at ways to mitigate these by examining our queries and connection parameters, leveraging connection pooling and replication, or adapting the workload. Topics: 1. Understand what we mean by high concurrency. 2. Understand ACID & MVCC in Postgres. 3. Understand how high concurrency affects Postgres performance. 4. Understand how locks/latches affect Postgres performance. 5. Understand how high transaction rates can affect Postgres. 6. Mitigation strategies for high concurrency scenarios. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/slowthingsdownfosdem-220206162647-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Talk from FOSDEM 2022 It&#39;s easy to get misled into overconfidence based on the performance of powerful servers, given today&#39;s monster core counts and RAM sizes. However, the reality of high concurrency usage is often disappointing, with less throughput than one would expect. Because of its internals and its multi-process architecture, PostgreSQL is very particular about how it likes to deal with high concurrency and in some cases it can slow down to the point where it looks like it&#39;s not performing as it should. In this talk we&#39;ll take a look at potential pitfalls when you throw a lot of work at your database. Specifically, very high concurrency and resource contention can cause problems with lock waits in Postgres. Very high transaction rates can also cause problems of a different nature. Finally, we will be looking at ways to mitigate these by examining our queries and connection parameters, leveraging connection pooling and replication, or adapting the workload. Topics: 1. Understand what we mean by high concurrency. 2. Understand ACID &amp; MVCC in Postgres. 3. Understand how high concurrency affects Postgres performance. 4. Understand how locks/latches affect Postgres performance. 5. Understand how high transaction rates can affect Postgres. 6. Mitigation strategies for high concurrency scenarios.
Slow things down to make them go faster [FOSDEM 2022] from Jimmy Angelakos
]]> 342 0 https://cdn.slidesharecdn.com/ss_thumbnails/slowthingsdownfosdem-220206162647-thumbnail.jpg?width=120&height=120&fit=bounds presentation 000000 http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Practical Partitioning in Production with Postgres /slideshow/practical-partitioning-in-production-with-postgres-postgres-vision-2021/249499102 practicalpartitioninginproductionwithpgpgvision-210626074835
Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. Talk from Postgres Vision 2021]]>
Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. Talk from Postgres Vision 2021]]> Sat, 26 Jun 2021 07:48:35 GMT /slideshow/practical-partitioning-in-production-with-postgres-postgres-vision-2021/249499102 vyruss000@slideshare.net(vyruss000) Practical Partitioning in Production with Postgres vyruss000 Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it's in constant use? An introduction to the problems that can arise and how PostgreSQL's partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. Talk from Postgres Vision 2021 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/practicalpartitioninginproductionwithpgpgvision-210626074835-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Has your table become too large to handle? Have you thought about chopping it up into smaller pieces that are easier to query and maintain? What if it&#39;s in constant use? An introduction to the problems that can arise and how PostgreSQL&#39;s partitioning features can help, followed by a real-world scenario of partitioning an existing huge table on a live system. Talk from Postgres Vision 2021
Practical Partitioning in Production with Postgres from Jimmy Angelakos
]]> 661 0 https://cdn.slidesharecdn.com/ss_thumbnails/practicalpartitioninginproductionwithpgpgvision-210626074835-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Changing your huge table's data types in production /slideshow/changing-your-huge-tables-data-types-in-production/242316896 changingdatatypes-210205124351
You have a huge table, and it is necessary to change a column's data type, but your database has to keep running with no downtime. What do you do? Here's one way to perform this change, in as unobtrusive a manner as possible while your table keeps serving users, by avoiding long DDL table locks and leveraging procedural transaction control. Talk from the PostgreSQL devroom at FOSDEM 2021]]>
You have a huge table, and it is necessary to change a column's data type, but your database has to keep running with no downtime. What do you do? Here's one way to perform this change, in as unobtrusive a manner as possible while your table keeps serving users, by avoiding long DDL table locks and leveraging procedural transaction control. Talk from the PostgreSQL devroom at FOSDEM 2021]]> Fri, 05 Feb 2021 12:43:51 GMT /slideshow/changing-your-huge-tables-data-types-in-production/242316896 vyruss000@slideshare.net(vyruss000) Changing your huge table's data types in production vyruss000 You have a huge table, and it is necessary to change a column's data type, but your database has to keep running with no downtime. What do you do? Here's one way to perform this change, in as unobtrusive a manner as possible while your table keeps serving users, by avoiding long DDL table locks and leveraging procedural transaction control. Talk from the PostgreSQL devroom at FOSDEM 2021 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/changingdatatypes-210205124351-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> You have a huge table, and it is necessary to change a column&#39;s data type, but your database has to keep running with no downtime. What do you do? Here&#39;s one way to perform this change, in as unobtrusive a manner as possible while your table keeps serving users, by avoiding long DDL table locks and leveraging procedural transaction control. Talk from the PostgreSQL devroom at FOSDEM 2021
Changing your huge table's data types in production from Jimmy Angelakos
]]> 571 0 https://cdn.slidesharecdn.com/ss_thumbnails/changingdatatypes-210205124351-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 The State of (Full) Text Search in PostgreSQL 12 /slideshow/the-state-of-full-text-search-in-postgresql-12-226820234/226820234 fts-200203211112
How to navigate the rich but confusing field of (Full) Text Search in PostgreSQL. A short introduction will explain the concepts involved, followed by a discussion of functions, operators, indexes and collation support in Postgres in relevance to searching for text. Examples of usage will be provided, along with some stats demonstrating the differences.]]>
How to navigate the rich but confusing field of (Full) Text Search in PostgreSQL. A short introduction will explain the concepts involved, followed by a discussion of functions, operators, indexes and collation support in Postgres in relevance to searching for text. Examples of usage will be provided, along with some stats demonstrating the differences.]]> Mon, 03 Feb 2020 21:11:12 GMT /slideshow/the-state-of-full-text-search-in-postgresql-12-226820234/226820234 vyruss000@slideshare.net(vyruss000) The State of (Full) Text Search in PostgreSQL 12 vyruss000 How to navigate the rich but confusing field of (Full) Text Search in PostgreSQL. A short introduction will explain the concepts involved, followed by a discussion of functions, operators, indexes and collation support in Postgres in relevance to searching for text. Examples of usage will be provided, along with some stats demonstrating the differences. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/fts-200203211112-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> How to navigate the rich but confusing field of (Full) Text Search in PostgreSQL. A short introduction will explain the concepts involved, followed by a discussion of functions, operators, indexes and collation support in Postgres in relevance to searching for text. Examples of usage will be provided, along with some stats demonstrating the differences.
The State of (Full) Text Search in PostgreSQL 12 from Jimmy Angelakos
]]> 621 1 https://cdn.slidesharecdn.com/ss_thumbnails/fts-200203211112-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Deploying PostgreSQL on Kubernetes /slideshow/deploying-postgresql-on-kubernetes/130351662 deployingpostgresqlonkubernetes-190203132109
A look at some of the ways available to deploy Postgres in a Kubernetes cloud environment, either in small scale using simple configurations, or in larger scale using tools such as Helm charts and the Crunchy PostgreSQL Operator. A short introduction to Kubernetes will be given to explain the concepts involved, followed by examples from each deployment method and observations on the key differences.]]>
A look at some of the ways available to deploy Postgres in a Kubernetes cloud environment, either in small scale using simple configurations, or in larger scale using tools such as Helm charts and the Crunchy PostgreSQL Operator. A short introduction to Kubernetes will be given to explain the concepts involved, followed by examples from each deployment method and observations on the key differences.]]> Sun, 03 Feb 2019 13:21:09 GMT /slideshow/deploying-postgresql-on-kubernetes/130351662 vyruss000@slideshare.net(vyruss000) Deploying PostgreSQL on Kubernetes vyruss000 A look at some of the ways available to deploy Postgres in a Kubernetes cloud environment, either in small scale using simple configurations, or in larger scale using tools such as Helm charts and the Crunchy PostgreSQL Operator. A short introduction to Kubernetes will be given to explain the concepts involved, followed by examples from each deployment method and observations on the key differences. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/deployingpostgresqlonkubernetes-190203132109-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> A look at some of the ways available to deploy Postgres in a Kubernetes cloud environment, either in small scale using simple configurations, or in larger scale using tools such as Helm charts and the Crunchy PostgreSQL Operator. A short introduction to Kubernetes will be given to explain the concepts involved, followed by examples from each deployment method and observations on the key differences.
Deploying PostgreSQL on Kubernetes from Jimmy Angelakos
]]> 3040 1 https://cdn.slidesharecdn.com/ss_thumbnails/deployingpostgresqlonkubernetes-190203132109-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Bringing the Semantic Web closer to reality: PostgreSQL as RDF Graph Database /slideshow/bringing-the-semantic-web-closer-to-reality-postgresql-as-rdf-graph-database/71908191 semanticweb-170208115253
Presentation of an investigation into how Python's RDFLib and SQLAlchemy can be used to leverage PostgreSQL's capabilities to provide a persistent storage back-end for Graphs, and become the elusive practical RDF triple store for the Semantic Web (or simply help you export your data to someone who's expecting RDF)! Talk presented at FOSDEM 2017 in Brussels on 04-05/02/2017. Practical & hands-on presentation with example code which is certainly not optimal ;) Video: MP4: http://video.fosdem.org/2017/H.1309/postgresql_semantic_web.mp4 WebM/VP8: http://ftp.osuosl.org/pub/fosdem/2017/H.1309/postgresql_semantic_web.vp8.webm]]>
Presentation of an investigation into how Python's RDFLib and SQLAlchemy can be used to leverage PostgreSQL's capabilities to provide a persistent storage back-end for Graphs, and become the elusive practical RDF triple store for the Semantic Web (or simply help you export your data to someone who's expecting RDF)! Talk presented at FOSDEM 2017 in Brussels on 04-05/02/2017. Practical & hands-on presentation with example code which is certainly not optimal ;) Video: MP4: http://video.fosdem.org/2017/H.1309/postgresql_semantic_web.mp4 WebM/VP8: http://ftp.osuosl.org/pub/fosdem/2017/H.1309/postgresql_semantic_web.vp8.webm]]> Wed, 08 Feb 2017 11:52:53 GMT /slideshow/bringing-the-semantic-web-closer-to-reality-postgresql-as-rdf-graph-database/71908191 vyruss000@slideshare.net(vyruss000) Bringing the Semantic Web closer to reality: PostgreSQL as RDF Graph Database vyruss000 Presentation of an investigation into how Python's RDFLib and SQLAlchemy can be used to leverage PostgreSQL's capabilities to provide a persistent storage back-end for Graphs, and become the elusive practical RDF triple store for the Semantic Web (or simply help you export your data to someone who's expecting RDF)! Talk presented at FOSDEM 2017 in Brussels on 04-05/02/2017. Practical & hands-on presentation with example code which is certainly not optimal ;) Video: MP4: http://video.fosdem.org/2017/H.1309/postgresql_semantic_web.mp4 WebM/VP8: http://ftp.osuosl.org/pub/fosdem/2017/H.1309/postgresql_semantic_web.vp8.webm <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/semanticweb-170208115253-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> Presentation of an investigation into how Python&#39;s RDFLib and SQLAlchemy can be used to leverage PostgreSQL&#39;s capabilities to provide a persistent storage back-end for Graphs, and become the elusive practical RDF triple store for the Semantic Web (or simply help you export your data to someone who&#39;s expecting RDF)! Talk presented at FOSDEM 2017 in Brussels on 04-05/02/2017. Practical &amp; hands-on presentation with example code which is certainly not optimal ;) Video: MP4: http://video.fosdem.org/2017/H.1309/postgresql_semantic_web.mp4 WebM/VP8: http://ftp.osuosl.org/pub/fosdem/2017/H.1309/postgresql_semantic_web.vp8.webm
Bringing the Semantic Web closer to reality: PostgreSQL as RDF Graph Database from Jimmy Angelakos
]]> 4891 1 https://cdn.slidesharecdn.com/ss_thumbnails/semanticweb-170208115253-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Using PostgreSQL with Bibliographic Data /vyruss000/using-postgresql-with-bibliographic-data angelakosmarcjsonb2-160202121245
An investigation of how PostgreSQL and its latest capabilities (JSONB data type, GIN indices, Full Text Search) can be used to store, index and perform queries on structured Bibliographic Data such as MARC21/MARCXML, breaking the dependence on proprietary and arcane or obsolete software products. Talk presented at FOSDEM 2016 in Brussels on 31/01/2016. This is a very practical & hands-on presentation with example code which is certainly not optimal ;)]]>
An investigation of how PostgreSQL and its latest capabilities (JSONB data type, GIN indices, Full Text Search) can be used to store, index and perform queries on structured Bibliographic Data such as MARC21/MARCXML, breaking the dependence on proprietary and arcane or obsolete software products. Talk presented at FOSDEM 2016 in Brussels on 31/01/2016. This is a very practical & hands-on presentation with example code which is certainly not optimal ;)]]> Tue, 02 Feb 2016 12:12:45 GMT /vyruss000/using-postgresql-with-bibliographic-data vyruss000@slideshare.net(vyruss000) Using PostgreSQL with Bibliographic Data vyruss000 An investigation of how PostgreSQL and its latest capabilities (JSONB data type, GIN indices, Full Text Search) can be used to store, index and perform queries on structured Bibliographic Data such as MARC21/MARCXML, breaking the dependence on proprietary and arcane or obsolete software products. Talk presented at FOSDEM 2016 in Brussels on 31/01/2016. This is a very practical & hands-on presentation with example code which is certainly not optimal ;) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/angelakosmarcjsonb2-160202121245-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> An investigation of how PostgreSQL and its latest capabilities (JSONB data type, GIN indices, Full Text Search) can be used to store, index and perform queries on structured Bibliographic Data such as MARC21/MARCXML, breaking the dependence on proprietary and arcane or obsolete software products. Talk presented at FOSDEM 2016 in Brussels on 31/01/2016. This is a very practical &amp; hands-on presentation with example code which is certainly not optimal ;)
Using PostgreSQL with Bibliographic Data from Jimmy Angelakos
]]> 2123 5 https://cdn.slidesharecdn.com/ss_thumbnails/angelakosmarcjsonb2-160202121245-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 E¦É¦Ò¦Á¦Ã¦Ø¦Ã? ¦Ò¦Ó¦Ç¦Í PostgreSQL - ¦¶¦Ñ?¦Ò¦Ç ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í /slideshow/e-postgresql/23617160 postgresql-130628080743-phpapp01
¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ç ¦Ö¦Ñ?¦Ò¦Ç ¦Ó¦Ç? ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ç? ¦Å¦Ê¦Ä?¦Ë¦Ø¦Ò¦Ç? "¦°¦Ñ¦Ï¦Ç¦Ã¦Ì?¦Í¦Å? ¦¥¦Õ¦Á¦Ñ¦Ì¦Ï¦Ã?? ¦Ó¦Ç? ¦Â?¦Ò¦Ç? ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL" ¦Ò¦Ó¦É? 26/6/2013 ¦Ò¦Ó¦Ï ¦¥¦È¦Í¦É¦Ê? ?¦Ä¦Ñ¦Ô¦Ì¦Á ¦¥¦Ñ¦Å¦Ô¦Í?¦Í.]]>
¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ç ¦Ö¦Ñ?¦Ò¦Ç ¦Ó¦Ç? ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ç? ¦Å¦Ê¦Ä?¦Ë¦Ø¦Ò¦Ç? "¦°¦Ñ¦Ï¦Ç¦Ã¦Ì?¦Í¦Å? ¦¥¦Õ¦Á¦Ñ¦Ì¦Ï¦Ã?? ¦Ó¦Ç? ¦Â?¦Ò¦Ç? ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL" ¦Ò¦Ó¦É? 26/6/2013 ¦Ò¦Ó¦Ï ¦¥¦È¦Í¦É¦Ê? ?¦Ä¦Ñ¦Ô¦Ì¦Á ¦¥¦Ñ¦Å¦Ô¦Í?¦Í.]]> Fri, 28 Jun 2013 08:07:42 GMT /slideshow/e-postgresql/23617160 vyruss000@slideshare.net(vyruss000) E¦É¦Ò¦Á¦Ã¦Ø¦Ã? ¦Ò¦Ó¦Ç¦Í PostgreSQL - ¦¶¦Ñ?¦Ò¦Ç ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í vyruss000 ¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ç ¦Ö¦Ñ?¦Ò¦Ç ¦Ó¦Ç? ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ç? ¦Å¦Ê¦Ä?¦Ë¦Ø¦Ò¦Ç? "¦°¦Ñ¦Ï¦Ç¦Ã¦Ì?¦Í¦Å? ¦¥¦Õ¦Á¦Ñ¦Ì¦Ï¦Ã?? ¦Ó¦Ç? ¦Â?¦Ò¦Ç? ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL" ¦Ò¦Ó¦É? 26/6/2013 ¦Ò¦Ó¦Ï ¦¥¦È¦Í¦É¦Ê? ?¦Ä¦Ñ¦Ô¦Ì¦Á ¦¥¦Ñ¦Å¦Ô¦Í?¦Í. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/postgresql-130628080743-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ç ¦Ö¦Ñ?¦Ò¦Ç ¦Ó¦Ç? ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ç? ¦Å¦Ê¦Ä?¦Ë¦Ø¦Ò¦Ç? &quot;¦°¦Ñ¦Ï¦Ç¦Ã¦Ì?¦Í¦Å? ¦¥¦Õ¦Á¦Ñ¦Ì¦Ï¦Ã?? ¦Ó¦Ç? ¦Â?¦Ò¦Ç? ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL&quot; ¦Ò¦Ó¦É? 26/6/2013 ¦Ò¦Ó¦Ï ¦¥¦È¦Í¦É¦Ê? ?¦Ä¦Ñ¦Ô¦Ì¦Á ¦¥¦Ñ¦Å¦Ô¦Í?¦Í.
E¦É¦Ò¦Á¦Ã¦Ø¦Ã? ¦Ò¦Ó¦Ç¦Í PostgreSQL - ¦¶¦Ñ?¦Ò¦Ç ¦Ò¦Å ¦Å¦Ð¦É¦Ö¦Å¦É¦Ñ¦Ç¦Ò¦É¦Á¦Ê? ¦Ð¦Å¦Ñ¦É¦Â?¦Ë¦Ë¦Ï¦Í from Jimmy Angelakos
]]> 830 4 https://cdn.slidesharecdn.com/ss_thumbnails/postgresql-130628080743-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 PostgreSQL: M?¦È¦Ï¦Ä¦Ï¦É ¦Ã¦É¦Á Data Replication /slideshow/postgresql-m-data-replication/19791975 datareplication-130423134220-phpapp02
¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ø¦Í ¦Ä¦Ô¦Í¦Á¦Ó¦Ï¦Ó?¦Ó¦Ø¦Í Data Replication ¦Ð¦Ï¦Ô ¦Ð¦Ñ¦Ï¦Ò¦Õ?¦Ñ¦Å¦É, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ï¦Ô 6¦Ï¦Ô ¦²¦Ô¦Í¦Å¦Ä¦Ñ?¦Ï¦Ô ¦ª¦Ï¦É¦Í¦Ï¦Ó?¦Ó¦Ø¦Í ¦¡¦Í¦Ï¦É¦Ö¦Ó¦Ï? ¦«¦Ï¦Ã¦É¦Ò¦Ì¦É¦Ê¦Ï? FOSSCOMM 2013 ¦Ò¦Ó¦É? 21/4/2013 ¦Ò¦Ó¦Ï ¦¶¦Á¦Ñ¦Ï¦Ê?¦Ð¦Å¦É¦Ï ¦°¦Á¦Í¦Å¦Ð¦É¦Ò¦Ó?¦Ì¦É¦Ï ¦¡¦È¦Ç¦Í?¦Í.]]>
¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ø¦Í ¦Ä¦Ô¦Í¦Á¦Ó¦Ï¦Ó?¦Ó¦Ø¦Í Data Replication ¦Ð¦Ï¦Ô ¦Ð¦Ñ¦Ï¦Ò¦Õ?¦Ñ¦Å¦É, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ï¦Ô 6¦Ï¦Ô ¦²¦Ô¦Í¦Å¦Ä¦Ñ?¦Ï¦Ô ¦ª¦Ï¦É¦Í¦Ï¦Ó?¦Ó¦Ø¦Í ¦¡¦Í¦Ï¦É¦Ö¦Ó¦Ï? ¦«¦Ï¦Ã¦É¦Ò¦Ì¦É¦Ê¦Ï? FOSSCOMM 2013 ¦Ò¦Ó¦É? 21/4/2013 ¦Ò¦Ó¦Ï ¦¶¦Á¦Ñ¦Ï¦Ê?¦Ð¦Å¦É¦Ï ¦°¦Á¦Í¦Å¦Ð¦É¦Ò¦Ó?¦Ì¦É¦Ï ¦¡¦È¦Ç¦Í?¦Í.]]> Tue, 23 Apr 2013 13:42:20 GMT /slideshow/postgresql-m-data-replication/19791975 vyruss000@slideshare.net(vyruss000) PostgreSQL: M?¦È¦Ï¦Ä¦Ï¦É ¦Ã¦É¦Á Data Replication vyruss000 ¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ø¦Í ¦Ä¦Ô¦Í¦Á¦Ó¦Ï¦Ó?¦Ó¦Ø¦Í Data Replication ¦Ð¦Ï¦Ô ¦Ð¦Ñ¦Ï¦Ò¦Õ?¦Ñ¦Å¦É, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ï¦Ô 6¦Ï¦Ô ¦²¦Ô¦Í¦Å¦Ä¦Ñ?¦Ï¦Ô ¦ª¦Ï¦É¦Í¦Ï¦Ó?¦Ó¦Ø¦Í ¦¡¦Í¦Ï¦É¦Ö¦Ó¦Ï? ¦«¦Ï¦Ã¦É¦Ò¦Ì¦É¦Ê¦Ï? FOSSCOMM 2013 ¦Ò¦Ó¦É? 21/4/2013 ¦Ò¦Ó¦Ï ¦¶¦Á¦Ñ¦Ï¦Ê?¦Ð¦Å¦É¦Ï ¦°¦Á¦Í¦Å¦Ð¦É¦Ò¦Ó?¦Ì¦É¦Ï ¦¡¦È¦Ç¦Í?¦Í. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/datareplication-130423134220-phpapp02-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> ¦°¦Á¦Ñ¦Ï¦Ô¦Ò?¦Á¦Ò? ¦Ì¦Ï¦Ô ¦Ã¦É¦Á ¦Ó¦Ç ¦Â?¦Ò¦Ç ¦Ä¦Å¦Ä¦Ï¦Ì?¦Í¦Ø¦Í PostgreSQL ¦Ê¦Á¦É ¦Ó¦Ø¦Í ¦Ä¦Ô¦Í¦Á¦Ó¦Ï¦Ó?¦Ó¦Ø¦Í Data Replication ¦Ð¦Ï¦Ô ¦Ð¦Ñ¦Ï¦Ò¦Õ?¦Ñ¦Å¦É, ¦Ò¦Ó¦Á ¦Ð¦Ë¦Á?¦Ò¦É¦Á ¦Ó¦Ï¦Ô 6¦Ï¦Ô ¦²¦Ô¦Í¦Å¦Ä¦Ñ?¦Ï¦Ô ¦ª¦Ï¦É¦Í¦Ï¦Ó?¦Ó¦Ø¦Í ¦¡¦Í¦Ï¦É¦Ö¦Ó¦Ï? ¦«¦Ï¦Ã¦É¦Ò¦Ì¦É¦Ê¦Ï? FOSSCOMM 2013 ¦Ò¦Ó¦É? 21/4/2013 ¦Ò¦Ó¦Ï ¦¶¦Á¦Ñ¦Ï¦Ê?¦Ð¦Å¦É¦Ï ¦°¦Á¦Í¦Å¦Ð¦É¦Ò¦Ó?¦Ì¦É¦Ï ¦¡¦È¦Ç¦Í?¦Í.
PostgreSQL: M„¢‘]Áè¡ÁèÂà Á£ÂÃÁô Data Replication from Jimmy Angelakos
]]> 949 3 https://cdn.slidesharecdn.com/ss_thumbnails/datareplication-130423134220-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://public.slidesharecdn.com/v2/images/profile-picture.png Systems and Database Architect and recognized PostgreSQL expert with a wealth of experience gained from his career in Software Architecture and key roles at 2ndQuadrant and EDB. Studied Computer Science at the University of Aberdeen and has worked with, and contributed to, Open-Source tools for 25+ years. Passionate about participating in the community, active member of PostgreSQL Europe and an occasional contributor to the PostgreSQL project. Regular speaker at conferences and events focused on databases and Open-Source software, sharing my insights with the community. Author of PostgreSQL Mistakes and How to Avoid Them: http://mng.bz/NVzn vyruss.org/computing https://cdn.slidesharecdn.com/ss_thumbnails/dontdothis-230209110136-5b79c747-thumbnail.jpg?width=320&height=320&fit=bounds vyruss000/dont-do-this-fosdem-2023 Don&#39;t Do This [FOSDEM ... https://cdn.slidesharecdn.com/ss_thumbnails/slowthingsdownfosdem-220206162647-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/slow-things-down-to-make-them-go-faster-fosdem-2022/251118836 Slow things down to ma... https://cdn.slidesharecdn.com/ss_thumbnails/practicalpartitioninginproductionwithpgpgvision-210626074835-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/practical-partitioning-in-production-with-postgres-postgres-vision-2021/249499102 Practical Partitioning...