POSTGRESQL is an open-source, full-featured relational database. This presentation gives an overview of the Postgres 11 release.
Creative Commons Attribution License http://momjian.us/presentations
Last updated: September, 2018
The document discusses the top 12 new features of Oracle 12c, including improved column defaults that allow identity columns, increased size limits for VARCHAR columns up to 32K, improved queries for top-N results using ROW LIMIT clauses, and adaptive execution plans that allow the optimizer to choose alternative execution plans based on statistics gathered during the first execution. Temporary undo segments are also introduced to avoid generating redo for temporary table operations.
Devrim Gunduz gives a presentation on Write-Ahead Logging (WAL) in PostgreSQL. WAL logs all transactions to files called write-ahead logs (WAL files) before changes are written to data files. This allows for crash recovery by replaying WAL files. WAL files are used for replication, backup, and point-in-time recovery (PITR) by replaying WAL files to restore the database to a previous state. Checkpoints write all dirty shared buffers to disk and update the pg_control file with the checkpoint location.
This document profiles an Oracle DBA with over 18 years of experience. It lists their work experience including being Vice President of an Oracle user group in Guatemala since 2014 and a member of various Oracle communities. It also references a blog they co-wrote with an Oracle Ace from Argentina. The rest of the document discusses performance tuning concepts and strategies including analyzing response times, throughput indicators, and using metrics like average, variance, and dispersion to understand predictability. It provides examples of using Oracle tools to collect job and query timings and demonstrates analyzing backups and elapsed times. The goal is to identify the slowest or least predictable processes or queries for further optimization.
Setup oracle golden gate 11g replicationKanwar Batra
How to setup Oracle Goldengate Replication between 11gR2 RAC or Single node instances. For RAC setup the GoldenGate custom cluster service . Not part of this document
This document provides an agenda and background information for a presentation on PostgreSQL. The agenda includes topics such as practical use of PostgreSQL, features, replication, and how to get started. The background section discusses the history and development of PostgreSQL, including its origins from INGRES and POSTGRES projects. It also introduces the PostgreSQL Global Development Team.
OOW16 - Oracle Database 12c - The Best Oracle Database 12c New Features for D...Alex Zaballa
This document provides an overview of new features in Oracle Database 12c for developers and DBAs. It begins with an introduction by Alex Zaballa and then covers several new features including native support for JSON, data redaction, row limits and offsets for SQL queries, PL/SQL functions callable from SQL, session level sequences, and temporary undo. The document includes demonstrations of many of these new features.
Watch the full webinar at: http://embt.co/1pb4Zb4
This presentation is a must-see for anyone interested in Oracle 12! Dan is an Oracle ACE Director and has assembled this presentation with fresh and inside information from Oracle Corp and OOW13. Dan has pulled his top Oracle 12 features from the plethora of new features available and documented in his user group presentations "Oracle 12c New Features for Developers" and "Oracle 12c New Features for DBA's".
Top 10 features will include:
New SQL Syntax
New SQL and PL/SQL Limits
Pluggable Database
New Packages
Deprecated Features
New SQL Tuning Features
This presentation covers new SQL & PL/SQL syntax and options, the container DB of course, new SQL optimizer features, deprecated features, hints, and more. If you're supporting applications, then you won't want to miss this webinar!
PostgreSQL 9.4, 9.5 and Beyond @ COSCUP 2015 TaipeiSatoshi Nagayasu
The document provides an overview of new features in PostgreSQL versions 9.4 and 9.5, including improvements to NoSQL support with JSONB and GIN indexes, analytics functions like aggregation and materialized views, SQL features like UPSERT, security with row level access policies, replication capabilities using logical decoding, and infrastructure to support parallelization. It also outlines the status and changes between versions, and resources for using and learning about PostgreSQL.
RMAN in Oracle Database 12c provides several new features to enhance backup and recovery capabilities. These include support for pluggable database backups, using SQL statements directly in RMAN, separating DBA privileges for security, and enhancing active database duplication. RMAN also allows multisection backups of very large files and table recovery directly from RMAN backups.
Size can creep up on you. Some day you may wake up to a multi-terabyte Postgres system handling over 3000 tps staring you down. Learn the best ways to manage these systems as they grow, and find out what new features in 9.0 have made life easier for administrators and application developers working with big data.
This talk will lead you through solutions to problems Postgres faces when it gets big: backups, transaction wraparound, bloat, huge catalogs and upgrades. You need to monitor the right things, find the gems in DBA-friendly database functions and catalog tables, and know the right places to look to spot problems early. We’ll also go over monitoring best practices and open source tools to get the job done.
Working with multiple versions of Postgres back to version 8.2 will be included, and as well as tips on making the most out of new features in 9.0. War stories will be taken from real-world work with Emma, an email marketing company with a few large databases.
1) Oracle 10g introduces flashback query which allows users to query past states of data within a specified time period by accessing the undo logs.
2) Flashback table allows users to recover accidentally dropped tables from the recycle bin.
3) Rollback monitoring provides estimated time to complete long running transactions such as rollbacks.
The document discusses table partitioning and sharding in PostgreSQL as approaches to improve performance and scalability as data volumes grow over time. Table partitioning involves splitting a master table into multiple child tables or partitions based on a partition function to distribute data. Sharding distributes partitions across multiple database servers. The document provides steps to implement table partitioning and sharding in PostgreSQL using the Citus extension to distribute a sample sales table across a master and worker node.
This presentation explains all of the new features that are relevant for developers in Oracle 12c. It's been out for a couple of years, but many companies haven't updated to 12c. So, if you're looking to update soon, or are just interested in what the new features are, look at this presentation.
The full post is available at http://www.completeitprofessional.com/oracle-12c-new-features-for-developers
In the “Sharing is caring” spirit, we came up with a series of internal talks called, By Showmaxers, for Showmaxers, and we recently started making them public. There are already talks about Networks, and Android app building, available.
Our latest talk focuses on PostgreSQL Terminology, and is led by Angus Dippenaar. He worked on Showmax projects from South Africa, and moved to work with us in Prague, Czech Republic.
The talk was meant to fill some holes in our knowledge of PostgreSQL. So, it guides you through the basic PostgreSQL terminology you need to understand when reading the official documentation and blogs.
You may learn what all these POstgreSQL terms mean:
Command, query, local or global object, non-schema local objects, relation, tablespace, database, database cluster, instance and its processes like postmaster or backend; session, connection, heap, file segment, table, TOAST, tuple, view, materialized (view), transaction, commit, rollback, index, write-ahead log, WAL record, WAL file, checkpoint, Multi-version concurrency control (MVCC), dead tuples (dead rows), or transaction exhaustion.
The terminology is followed by a demonstration of transaction exhaustion.
Get the complete explanation and see the demonstration of the transaction exhaustion and of tuple freezing in the talk on YouTube: https://youtu.be/E-RkI3Ws7gM.
Tony jambu (obscure) tools of the trade for tuning oracle sq lsInSync Conference
There are several tools available for SQL tuning in Oracle, including those that generate explain plans, analyze trace files, and provide real-time SQL monitoring. The document discusses tuning methodology, generating explain plans with SQL*Plus and Autotrace, tracing using parameters and DBMS_MONITOR, and tools like DBMS_XPLAN, TRCA, SQLTXPLAIN, Oracle Active Report, and Toad. It provides examples of using many of these tools to analyze SQL performance.
This document discusses stored procedures in MySQL and MSSQL, including their advantages, syntax, and examples. It also covers the differences between procedures and functions, and provides an example of creating a trigger to update total department salaries when employees are inserted, updated, or deleted.
Tony Jambu (obscure) tools of the trade for tuning oracle sq lsInSync Conference
This document provides an overview of various tools that can be used for tuning Oracle SQL statements. It discusses tuning methodology, generating explain plans and traces, and tools like SQL*Plus autotrace, DBMS_XPLAN, TRCA trace analyzer, and SQLTXPLAIN. Demo examples are provided for many of the tools to analyze SQL performance.
Performance improvements in PostgreSQL 9.5 and beyondTomas Vondra
This document discusses several performance improvements made in PostgreSQL versions 9.5 and beyond. Some key improvements discussed include:
- Faster sorting through allowing sorting by inlined functions, abbreviated keys for VARCHAR/TEXT/NUMERIC, and Sort Support benefits.
- Improved hash joins through reduced palloc overhead, smaller NTUP_PER_BUCKET, and dynamically resizing the hash table.
- Index improvements like avoiding index tuple copying, GiST and bitmap index scan optimizations, and block range tracking in BRIN indexes.
- Aggregate functions see speedups through using 128-bit integers for internal state instead of NUMERIC in some cases.
- Other optimizations affect PL/pgSQL performance,
The document summarizes upcoming improvements and enhancements in MySQL 5.5 related to scalability and performance. Key points include:
1) Semi-synchronous replication, the Performance Schema, SIGNAL/RESIGNAL, and additional partitioning options to improve data integrity and monitoring.
2) Major InnoDB improvements including a faster memory allocator, improved change buffering, prefetching and flushing techniques, and additional background threads to increase scalability.
3) Methods to control resource usage like I/O capacity, purge scheduling, and flushing for better performance under varying workloads.
PostgreSQL 9.5 includes several new features to improve performance and functionality for developers:
UPSERT allows inserting or updating a row based on unique constraints. BRIN indexes provide very small indexes ideal for large naturally ordered tables. GROUPING SETS, CUBE and ROLLUP allow multiple groupings in a single query. Row-level security policies control access at the row level. SKIP LOCKED ignores locked rows. TABLESAMPLE selects random rows. IMPORT FOREIGN SCHEMA simplifies importing schemas from other databases. Foreign tables can now participate in inheritance. JSONB documents can be modified and merged. Sorting performance is improved with abbreviated keys. Parallel vacuuming allows vacuum operations to use multiple processes.
PostgreSQL 8.4 introduced several new features including common table expressions, window functions, parallel restore, and performance improvements. Version 9.0 will focus on improving replication support through streaming replication and read-only hot standby servers. Overall, PostgreSQL continues to expand its feature set to better support modern SQL standards.
This document provides an overview of managing the Oracle database instance. It covers starting and stopping the Oracle database and components using Oracle Enterprise Manager and SQL*Plus. It describes accessing databases with SQL*Plus and modifying initialization parameters. It also discusses the stages of database startup, shutdown options, viewing the alert log, and accessing dynamic performance views.
Upgrading MySQL databases do not come without risk. There is no guarantee that no problems will happen if you move to a new major MySQL version.
Should we just upgrade and rollback immediately if problems occur? But what if these problems only happen a few days after migrating to this new version?
You might have a database environment that is risk-adverse, where you really have to be sure that this new MySQL version will handle the workload properly.
Examples:
- Both MySQL 5.6 and 5.7 have a lot of changes in the MySQL Optimizer. It is expected that this improves performance of my queries, but is it really the case? What if there is a performance regression? How will this affect my database performance?
- Also, there are a lot of incompatible changes which are documented in the release notes, how do I know if I'm affected by this in my workload? It's a lot to read..
- Can I go immediately from MySQL 5.5 to 5.7 and skip MySQL 5.6 even though the MySQL documentation states that this is not supported?
- Many companies have staging environments, but is there a QA team and do they really test all functionality, under a similar workload?
This presentation will show you a process, using open source tools, of these types of migrations with a focus on assessing risk and fixing any problems you might run into prior to the migration.
This process can then be used for various changes:
- MySQL upgrades for major version upgrades
- Switching storage engines
- Changing hardware architecture
Additionally, we will describe ways to do the actual migration and rollback with the least amount of downtime.
DBA Commands and Concepts That Every Developer Should KnowAlex Zaballa
DBA Commands and Concepts That Every Developer Should Know was presented by Alex Zaballa, an Oracle DBA with experience in Brazil and Angola. The presentation covered Oracle Flashback Query, Flashback Table, RMAN table recovery, pending statistics, explain plan, DBMS_APPLICATION_INFO, row-by-row vs bulk processing, Virtual Private Database, extended data types, SQL text expansion, identity columns, UTL_CALL_STACK, READ privileges vs SELECT privileges, and online table redefinition. The presentation included demonstrations of many of these concepts.
In this first of a series of presentations, we'll overview the differences between SQL and PL/SQL, and the first steps in optimization, as understanding RULE vs. COST, and how to slash 90% response time in data extractions running in SQL*Plus.
An overview presentation covering the use of Oracle's PX functionality including some tips and traps. Detailed white paper at http://oracledoug.com/px.html
This document discusses various topics related to dynamic websites using PHP with Oracle DB including:
1. Quizzes on database relations and queries
2. Installing and connecting to Oracle 11g
3. Using SQL Developer tool
4. An overview of PL/SQL including blocks, conditions, loops
5. Stored procedures and functions
6. Triggers
7. Basic HTML markup
The document provides an introduction to stored procedures in SQL. Key points include:
- Stored procedures allow code to be executed faster than batches by pre-compiling the code.
- They centralize business logic and error handling routines for consistent implementation across users.
- Parameters can be passed into stored procedures to make them more flexible. Output parameters allow returning values.
- Best practices include adding comments, error handling, and using transactions for consistency across nested stored procedures.
The document provides an introduction to stored procedures in SQL. Key points include:
- Stored procedures allow code to be executed as a batch after being compiled once, improving performance over executing individual SQL statements.
- Stored procedures can accept input parameters, return output parameters, and be used to enforce consistent implementation of business logic and error handling.
- Best practices for stored procedures include adding documentation, error handling, and using input/output parameters to make procedures more flexible and reusable.
What's New in MariaDB Server 10.2 and MariaDB MaxScale 2.1MariaDB plc
The document provides an overview of new features and enhancements in MariaDB Server 10.2 and MaxScale 2.1. For MariaDB Server 10.2, key additions include window functions, common table expressions, JSON and GeoJSON functions, new replication features like delayed replication, storage engine enhancements including a new MyRocks storage engine, and performance optimizations. MaxScale 2.1 focuses on performance improvements up to 2.8x faster, enhanced security features like encrypted binlogs and SSL, and support for Aurora clusters and dynamic configuration.
What's New in MariaDB Server 10.2 and MariaDB MaxScale 2.1MariaDB plc
MariaDB Server 10.2 includes several new features for analytics, JSON, replication, database compatibility, storage engines, security, administration, performance, and optimizations. Some key additions include window functions and common table expressions for more efficient queries, JSON and GeoJSON functions, delayed and compressed replication, multi-trigger support, CHECK constraints, indexes on virtual columns, the MyRocks storage engine, per-user load limitations, and TLS connections. MaxScale 2.1 provides up to 2.8x performance gains along with new security features like encrypted binlogs and LDAP authentication as well as support for Aurora clusters and dynamic configurations.
12cR1 new features. I have tried to cover all new features of 12cR1 and many more may be missing. These are all my own views and do not necessarily reflect the views of Oracle. Requesting all visitors to comment on it to improve further.
Oracle Database 12c - The Best Oracle Database 12c Tuning Features for Develo...Alex Zaballa
Oracle Database 12c includes many new tuning features for developers and DBAs. Some key features include:
- Multitenant architecture allows multiple pluggable databases to consolidate workloads on a single database instance for improved utilization and administration.
- In-memory column store enables real-time analytics on frequently accessed data held entirely in memory for faster performance.
- New SQL syntax like FETCH FIRST for row limiting and offsetting provides more readable and intuitive replacements for previous techniques.
- Adaptive query optimization allows queries to utilize different execution plans like switching between nested loops and hash joins based on runtime statistics for improved performance.
MySQL 8 -- A new beginning : Sunshine PHP/PHP UK (updated)Dave Stokes
MySQL 8 has many new features and this presentation covers the new data dictionary, improved JSON functions, roles, histograms, and much more. Updated after SunshinePHP 2018 after feedback
Cloud Migration Paths: Kubernetes, IaaS, or DBaaSEDB
Moving to the cloud is hard, and moving Postgres databases to the cloud is even harder. Public cloud or private cloud? Infrastructure as a Service (IaaS), or Platform as a Service (PaaS)? Kubernetes for the application, or for the database and the application? This talk will juxtapose self-managed Kubernetes and container-based database solutions, Postgres deployments on IaaS, and Postgres DBaaS solutions of which EDB’s DBaaS BigAnimal is the latest example.
Die 10 besten PostgreSQL-Replikationsstrategien für Ihr UnternehmenEDB
Dieses Webinar hilft Ihnen, die Unterschiede zwischen den verschiedenen Replikationsansätzen zu verstehen, die Anforderungen der jeweiligen Strategie zu erkennen und sich über die Möglichkeiten klar zu werden, was mit jeder einzelnen zu erreichen ist. Damit werden Sie hoffentlich eher in der Lage sein, herauszufinden, welche PostgreSQL-Replikationsarten Sie wirklich für Ihr System benötigen.
- Wie physische und logische Replikation in PostgreSQL funktionieren
- Unterschiede zwischen synchroner und asynchroner Replikation
- Vorteile, Nachteile und Herausforderungen bei der Multi-Master-Replikation
- Welche Replikationsstrategie für unterschiedliche Use-Cases besser geeignet ist
Referent:
Borys Neselovskyi, Regional Sales Engineer DACH, EDB
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For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
Cuando busca alternativas a Oracle en la nube, hacer el cambio puede parecer un trabajo duro. Entendemos que la migración involucra más que solo la base de datos. La compatibilidad es un punto clave, especialmente cuando se consideran los recursos que posiblemente ya haya invertido en Oracle, como por ejemplo el código de aplicación específico de Oracle.Este seminario web explorará las opciones y las principales consideraciones al pasar de las bases de datos de Oracle a la nube.
- Revisión detallada de las ofertas de bases de datos disponibles en la nube
- Factores críticos que se deben considerar considerar para elegir la oferta en la nube más adecuada
- Cómo la experiencia de EDB con PostgreSQL puede ayudarlo en su decisión
- Demostración de BigAnimal de EDB
Présentateur:
Sergio Romera, Senior Sales Engineer EMEA, EDB
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For more #webinars, visit http://bit.ly/EDB-Webinars
Download free #PostgreSQL whitepapers: http://bit.ly/EDB-Whitepapers
Read our #Postgres Blog http://bit.ly/EDB-Blogs
Follow us on Facebook at http://bit.ly/EDB-FB
Follow us on Twitter at http://bit.ly/EDB-Twitter
Follow us on LinkedIn at http://bit.ly/EDB-LinkedIn
Reach us via email at marketing@enterprisedb.com
This document provides an overview and demonstration of EnterpriseDB's Failover Manager (EFM). It begins with an overview of EFM's capabilities in ensuring high availability and minimizing downtime during database upgrades or maintenance. It then covers installation and configuration prerequisites, supported platforms, and the EFM architecture involving a primary, standby, and witness database nodes. The remainder demonstrates switchover and failover functionality through a live demo in a replication environment using CentOS 7.7 and EnterpriseDB PostgreSQL Advanced Server 13.
Database come PostgreSQL non possono girare su Kubernetes. Questo è il ritornello che sentiamo continuamente, ma al tempo stesso la motivazione per noi di EDB di abbattere questo muro, una volta per tutte.
In questo webinar parleremo della nostra avventura finora per portare PostgreSQL su Kubernetes. Scopri perché crediamo che fare benchmark di storage e del database prima di andare in produzione porti a una più sana e longeva vita di un DBMS, anche su Kubernetes.
Condivideremo il nostro processo, i risultati fin qui ottenuti e sveleremo i nostri piani per il futuro con Cloud Native PostgreSQL.
Las Variaciones de la Replicación de PostgreSQLEDB
Replicación física, replicación lógica, síncrona, asíncrona, multi-maestro, escalabilidad horizontal, etc. Son muchos los términos asociados con la replicación de bases de datos. En esta charla revisaremos los conceptos fundamentales detrás de cada variación de la replicación de PostgreSQL, y en qué casos conviene usar una o la otra. La presentación incluye una parte práctica con demostraciones aunque no será un tutorial sobre como configurar un cluster. El enfoque está en entender cada variación para elegir la mejor dependiendo del caso de uso.
Cosas que aprenderán:
- Cómo funciona la replicación física en PostgreSQL
- Cómo funciona la replicación lógica en PostgreSQL
- Diferencias entre replicación síncrona y asíncrona
- Qué es replicación multi-maestro
NoSQL and Spatial Database Capabilities using PostgreSQLEDB
PostgreSQL is an object-relational database system. NoSQL on the other hand is a non-relational database and is document-oriented. Learn how the PostgreSQL database gives one the flexible options to combine NoSQL workloads with the relational query power by offering JSON data types. With PostgreSQL, new capabilities can be developed and plugged into the database as required.
Attend this webinar to learn:
- The new features and capabilities in PostgreSQL for new workloads, requiring greater flexibility in the data model
- NoSQL with JSON, Hstore and its performance and features for enterprises
- Spatial SQL - advanced features in PostGIS application with PostGIS extension
"Why use PgBouncer? It’s a lightweight, easy to configure connection pooler and it does one job well. As you’d expect from a talk on connection pooling, we’ll give a brief summary of connection pooling and why it increases efficiency. We’ll look at when not to use connection pooling, and we’ll demonstrate how to configure PgBouncer and how it works. But. Did you know you can also do this? 1. Scaling PgBouncer PgBouncer is single threaded which means a single instance of PgBouncer isn’t going to do you much good on a multi-threaded and/or multi-CPU machine. We’ll show you how to add more PgBouncer instances so you can use more than one thread for easy scaling. 2. Read-write / read only routing Using different pgBouncer databases you can route read-write traffic to the primary database and route read-only traffic to a number of standby databases. 3. Load balancing When we use multiple PgBouncer instances, load balancing comes for free. Load balancing can be directed to different standbys, and weighted according to ratios of load. 4. Silent failover You can perform silent failover during promotion of a new primary (assuming you have a VIP/DNS etc that always points to the primary). 5. And even: DoS prevention and protection from “badly behaved” applications! By using distinct port numbers you can provide database connections which deal with sudden bursts of incoming traffic in very different ways, which can help prevent the database from becoming swamped during high activity periods. You should leave the presentation wondering if there is anything PgBouncer can’t do."
In this talk I'll discuss how we can combine the power of PostgreSQL with TensorFlow to perform data analysis. By using the pl/python3 procedural language we can integrate machine learning libraries such as TensorFlow with PostgreSQL, opening the door for powerful data analytics combining SQL with AI. Typical use-cases might involve regression analysis to find relationships in an existing dataset and to predict results based on new inputs, or to analyse time series data and extrapolate future data taking into account general trends and seasonal variability whilst ignoring noise. Python is an ideal language for building custom systems to do this kind of work as it gives us access to a rich ecosystem of libraries such as Pandas and Numpy, in addition to TensorFlow itself.
Practical Partitioning in Production with PostgresEDB
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. We will be looking at the problems caused by having very large tables in your database and how declarative table partitioning in Postgres can help. Also, how to perform dimensioning before but also after creating huge tables, partitioning key selection, the importance of upgrading to get the latest Postgres features and finally we will dive into a real-world scenario of having to partition an existing huge table in use on a production system.
There have been plenty of “explaining EXPLAIN” type talks over the years, which provide a great introduction to it. They often also cover how to identify a few of the more common issues through it. EXPLAIN is a deep topic though, and to do a good introduction talk, you have to skip over a lot of the tricky bits. As such, this talk will not be a good introduction to EXPLAIN, but instead a deeper dive into some of the things most don’t cover. The idea is to start with some of the more complex and unintuitive calculations needed to work out the relationships between operations, rows, threads, loops, timings, buffers, CTEs and subplans. Most popular tools handle at least several of these well, but there are cases where they don’t that are worth being conscious of and alert to. For example, we’ll have a look at whether certain numbers are averaged per-loop or per-thread, or both. We’ll also cover a resulting rounding issue or two to be on the lookout for. Finally, some per-operation timing quirks are worth looking out for where CTEs and subqueries are concerned, for example CTEs that are referenced more than once. As time allows, we can also look at a few rarer issues that can be spotted via EXPLAIN, as well as a few more gotchas that we’ve picked up along the way. This includes things like spotting when the query is JIT, planning, or trigger time dominated, spotting the signs of table and index bloat, issues like lossy bitmap scans or index-only scans fetching from the heap, as well as some things to be aware of when using auto_explain.
This document provides an overview of using PostgreSQL for IoT applications. Chris Ellis discusses why PostgreSQL is a good fit for IoT due to its flexibility and extensibility. He describes various ways of storing, loading, and processing IoT time series and sensor data in PostgreSQL, including partitioning, batch loading, and window functions. The document also briefly mentions the TimescaleDB extension for additional time series functionality.
The document describes a migration from an Oracle database topology to a PostgreSQL database topology at ACI. It discusses the starting Oracle topology with issues around operational complexity and non-ACID compliance. It then describes the target PostgreSQL topology with improved performance, availability and lower costs. The document outlines decisions around tools, extensions, code changes and testing approaches needed for the migration. It also discusses options for migrating the data and cutting over to the new PostgreSQL environment.
The document provides an introduction to using the psql command line tool for interacting with PostgreSQL databases. It explains how to connect to a database, perform basic queries, explain query plans, and get information about tables, schemas, and users.
EDB 13 - New Enhancements for Security and Usability - APJEDB
Database security is always of paramount importance to all organizations. In this webinar, we will explore the security, usability, and portability updates of the latest version of the EDB database server and tools.
Join us in this webinar to learn:
- The new security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity, and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
Dans ce webinar, nous allons parler des différences entre une sauvegarde physique et une sauvegarde logique. Nous allons lister les avantages et inconvénients, les principales considérations et les outils disponibles pour les deux méthodes.
- Perte de données
- Exports logiques
- Standbys
- WALs et Recovery
- Snapshots VM/Disques
- Sauvegardes physique
- Conclusion
Vieni a scoprire Cloud Native PostgreSQL (CNP), l’operatore per Kubernetes, direttamente da coloro che lo hanno ideato e lo sviluppano in EDB.
CNP facilita l’integrazione di database PostgreSQL con le tue applicazioni all’interno di cluster Kubernetes e OpenShift Container Platform di RedHat, grazie alla sua gestione automatica dell’architettura primario/standby che include: self-healing, failover, switchover, rolling update, backup, ecc.
Durante il webinar affronteremo i seguenti punti:
- DevOps e Cloud Native
- Introduzione a Cloud Native PostgreSQL
- Architetture
- Caratteristiche principali
- Esempi di uso e configurazione
- Kubernetes, Storage e Postgres
- Demo
- Conclusioni
New enhancements for security and usability in EDB 13EDB
EDB 13 enhances our flagship database server and tools. This webinar will explore its security, usability, and portability updates. Join us to learn how EDB 13 can help you improve your PostgreSQL productivity and data protection.
Webinar highlights include:
- New security features such as SCRAM and the encryption of database passwords and traffic between Failover Manager agents
- Usability updates that automate partitioning, verify backup integrity and streamline the management of failover and backups
- Portability improvements that simplify running PostgreSQL across on-premise and cloud environments
The webinar will review a multi-layered framework for PostgreSQL security, with a deeper focus on limiting access to the database and data, as well as securing the data.
Using the popular AAA (Authentication, Authorization, Auditing) framework we will cover:
- Best practices for authentication (trust, certificate, MD5, Scram, etc).
- Advanced approaches, such as password profiles.
- Deep dive of authorization and data access control for roles, database objects (tables, etc), view usage, row-level security, and data redaction.
- Auditing, encryption, and SQL injection attack prevention.
Note: this session is delivered in German
Speaker:
Borys Neselovskyi, Sales Engineer, EDB
EDB Cloud Native Postgres includes database container images and a Kubernetes Operator that manage the lifecycle of a database from deployment to operations. This Kubernetes Operator for Postgres is written by EDB entirely from scratch in the Go language and relies exclusively on the Kubernetes API.
Attend this webinar to learn about:
- DevOps & Cloud Native
- Overview of Cloud Native Postgres
- Storage for Postgres workloads in Kubernetes
- Using Cloud Native Postgres
- Demo
Redefining Cybersecurity with AI CapabilitiesPriyanka Aash
In this comprehensive overview of Cisco's latest innovations in cybersecurity, the focus is squarely on resilience and adaptation in the face of evolving threats. The discussion covers the imperative of tackling Mal information, the increasing sophistication of insider attacks, and the expanding attack surfaces in a hybrid work environment. Emphasizing a shift towards integrated platforms over fragmented tools, Cisco introduces its Security Cloud, designed to provide end-to-end visibility and robust protection across user interactions, cloud environments, and breaches. AI emerges as a pivotal tool, from enhancing user experiences to predicting and defending against cyber threats. The blog underscores Cisco's commitment to simplifying security stacks while ensuring efficacy and economic feasibility, making a compelling case for their platform approach in safeguarding digital landscapes.
"Hands-on development experience using wasm Blazor", Furdak Vladyslav.pptxFwdays
I will share my personal experience of full-time development on wasm Blazor
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Major features postgres 11
1. Major Features: Postgres 11
BRUCE MOMJIAN
POSTGRESQL is an open-source, full-featured relational database.
This presentation gives an overview of the Postgres 11 release.
Creative Commons Attribution License http://momjian.us/presentations
Last updated: September, 2018
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2. Postgres 11 Feature Outline
1. Partitioning improvements
2. Parallelism improvements
3. Stored procedures with transaction control
4. Executor-stage compilation
5. Prevent table rewrite for ALTER TABLE … ADD COLUMN with
non-NULL default
6. Finer-grained access control
7. Write-ahead log (WAL) improvements
8. Allow ’quit’ and ’exit’ to exit psql
9. Miscellaneous
Full item list at https://www.postgresql.org/docs/devel/static/
release-11.html
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3. 1. Partitioning Improvements
◮ Partitioning syntax added in Postgres 10
◮ simplified administration
◮ Postgres 11
◮ faster partition pruning during optimization
◮ executor-level partition pruning, e.g., for joins
◮ hash partitioning
◮ move updated rows to new partitions
◮ allow a default partition for non-matching rows
◮ allow unique/primary indexes when the partition key is
included, and allow foreign keys to reference them
◮ more items
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4. Hash Partitioning Example
-- hash partition
CREATE TABLE part_test (x int, y text) PARTITION BY hash (x);
-- create child partitions
CREATE TABLE part_test_0 PARTITION OF part_test FOR VALUES
WITH (MODULUS 4, REMAINDER 0);
CREATE TABLE part_test_1 PARTITION OF part_test FOR VALUES
WITH (MODULUS 4, REMAINDER 1);
CREATE TABLE part_test_2 PARTITION OF part_test FOR VALUES
WITH (MODULUS 4, REMAINDER 2);
CREATE TABLE part_test_3 PARTITION OF part_test FOR VALUES
WITH (MODULUS 4, REMAINDER 3);
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5. Partitioning Row Migration
-- insert 1k rows
INSERT INTO part_test SELECT generate_series(0, 999), ’old’;
-- What partition contains row zero?
SELECT relname
FROM pg_class
WHERE oid = (SELECT tableoid FROM part_test WHERE x = 0);
relname
-------------
part_test_0
-- change row zero to row 1003
UPDATE part_test SET x = 1003, y = ’new’ WHERE x = 0;
--What partition contains row 1003? Values are hashed twice.
SELECT relname
FROM pg_class
WHERE oid = (SELECT tableoid FROM part_test WHERE x = 1003);
relname
-------------
part_test_1
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6. Partitioning Row Distribution
-- How are the rows distributed?
SELECT name, y, COUNT(*)
FROM part_test, LATERAL (
SELECT relname
FROM pg_class
WHERE pg_class.oid = part_test.tableoid) AS table_name (name)
GROUP BY name, y
ORDER BY 1, 2;
name | y | count
-------------+-----+-------
part_test_0 | old | 258
part_test_1 | new | 1
part_test_1 | old | 234
part_test_2 | old | 276
part_test_3 | old | 231
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7. Range Partitioning Example
-- range partition
CREATE TABLE part_test2 (instant TIMESTAMP WITH TIME ZONE, description TEXT)
PARTITION BY RANGE (instant);
CREATE TABLE part_test2_2017 PARTITION OF part_test2 FOR VALUES
FROM (’2017-01-01’) TO (’2018-01-01’);
CREATE TABLE part_test2_2018 PARTITION OF part_test2 FOR VALUES
FROM (’2018-01-01’) TO (’2019-01-01’);
-- create default partition
CREATE TABLE part_test2_default PARTITION OF part_test2 DEFAULT;
-- add primary key to parent table
ALTER TABLE part_test2 ADD PRIMARY KEY (instant);
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8. Default Partition
-- insert two years of rows
INSERT INTO part_test2
SELECT generate_series(’2017-01-01’::timestamptz,
’2018-12-31’, ’1 day’), ’rain’;
-- insert rows outside of the defined range
INSERT INTO part_test2 VALUES (’2019-02-20’, ’snow’);
SELECT name, COUNT(*)
FROM part_test2, LATERAL (
SELECT relname
FROM pg_class
WHERE pg_class.oid = part_test2.tableoid) AS table_name (name)
GROUP BY name
ORDER BY 1;
name | count
--------------------+-------
part_test2_2017 | 365
part_test2_2018 | 365
part_test2_default | 1
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9. 2. Parallelism Improvements
◮ Parallel btree index builds
◮ Parallel hash joins
◮ Parallelize individual SELECTs in UNION
◮ Seven more items
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10. 3. Stored Procedures with Transaction Control
◮ Similar to functions
◮ allows transaction commit and abort blocks inside procedures
◮ returns no values
◮ commands prohibited in transaction blocks are still
prohibited in procedures, e.g., VACUUM
◮ inner transactions cannot be committed independently of
outer transactions, i.e., no autonomous transactions
◮ Supported languages
◮ PL/pgSQL
◮ PL/Perl
◮ PL/Python
◮ PL/Tcl
◮ SPI
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11. Stored Procedure Example
CREATE TABLE system (status text NOT NULL);
-- no more than one row in the table
CREATE UNIQUE INDEX ON system ((true));
CREATE TABLE customer (name TEXT, sales_monthly_total NUMERIC(10,2));
CREATE TABLE employee (name TEXT, sales_monthly_total NUMERIC(10,2));
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12. Stored Procedure Example
CREATE PROCEDURE end_of_month_processing() AS $$
BEGIN
INSERT INTO system VALUES (’end-of-month processing’)
ON CONFLICT ((true)) DO UPDATE SET status = excluded.status;
-- allow all sessions to see the new status
COMMIT;
UPDATE customer SET sales_monthly_total = 0;
UPDATE employee SET sales_monthly_total = 0;
INSERT INTO system VALUES (’normal operation’)
ON CONFLICT ((true)) DO UPDATE SET STATUS = excluded.status;
-- allow all sessions to see the new status
COMMIT;
-- inform managers only after complete
PERFORM email_managers(’end-of-month processing complete’);
END
$$ LANGUAGE plpgsql;
CALL end_of_month_processing();
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13. Stored Procedure Example
CREATE TABLE web_session (data JSONB, last_active TIMESTAMP WITH TIME ZONE);
-- add five web sessions
INSERT INTO web_session
SELECT ’{"abc": 1}’, CURRENT_TIMESTAMP
FROM generate_series(1, 5);
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14. Stored Procedure Example
CREATE PROCEDURE expire_web_sessions(min_expire INTERVAL) AS $$
DECLARE
rows INTEGER;
BEGIN
WHILE TRUE LOOP
-- clock_timestamp() is updated on every loop
DELETE FROM web_session WHERE last_active < clock_timestamp()-min_expire;
GET DIAGNOSTICS rows = ROW_COUNT;
COMMIT;
RAISE NOTICE ’% rows deleted’, rows;
-- check at half of expiration time
PERFORM pg_sleep(EXTRACT(EPOCH FROM min_expire) / 2);
END LOOP;
END
$$ LANGUAGE plpgsql;
CALL expire_web_sessions(’15 minutes’);
NOTICE: 0 rows deleted
NOTICE: 0 rows deleted
NOTICE: 5 rows deleted
NOTICE: 0 rows deleted
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15. 4. Executor-Stage Compilation
utility
Plan
Optimal Path
Query
Generate Plan
Traffic Cop
Generate Paths
Execute Plan
e.g. CREATE TABLE, COPY
SELECT, INSERT, UPDATE, DELETE
Rewrite Query
Parse Statement
Utility
Command
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16. Executor-Stage Compilation
utility
Optimal Path
Query
Plan
Plan with Ojbect Code
Execute Plan
Just−in−Time Compiler
Object Code
Generate Plan
Traffic Cop
Generate Paths
e.g. CREATE TABLE, COPY
SELECT, INSERT, UPDATE, DELETE
Rewrite Query
Parse Statement
Utility
Command
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17. 5. Prevent Table Rewrite For ALTER TABLE …
ADD COLUMN with Non-NULL Default
-- Postgres 10
CREATE TABLE alter_test (id SERIAL, name TEXT);
INSERT INTO alter_test (name) SELECT repeat(’x’, 100);
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16439
ALTER TABLE alter_test ADD COLUMN col1 INTEGER;
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16439
ALTER TABLE alter_test ADD COLUMN col2 INTEGER DEFAULT 1;
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16447
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18. Prevent Table Rewrite For ALTER TABLE …
ADD COLUMN with Non-NULL Default
-- Postgres 11
CREATE TABLE alter_test (id SERIAL, name TEXT);
INSERT INTO alter_test (name) SELECT repeat(’x’, 100);
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16388
ALTER TABLE alter_test ADD COLUMN col1 INTEGER;
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16388
ALTER TABLE alter_test ADD COLUMN col2 INTEGER DEFAULT 1;
SELECT relfilenode FROM pg_class WHERE relname = ’alter_test’;
relfilenode
-------------
16388
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19. 6. Finer-Grained Access Control
◮ Superuser-only file system access now controlled by role
membership
◮ pg_read_server_files
◮ pg_write_server_files
◮ pg_execute_server_program
◮ Superuser-only access to file system functions now controlled
by function execute permissions
◮ pg_ls_dir()
◮ pg_read_file()
◮ pg_read_binary_file()
◮ pg_stat_file()
◮ Superuser-only import/export of large objects now controlled
by function execute permissions
◮ lo_import()
◮ lo_export()
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20. 7. Write-Ahead Log (WAL) Improvements
◮ Allow WAL file size to be specified via initdb or pg_resetwal
◮ default still 16MB
◮ larger files simplify WAL archiving for active clusters
◮ Halve number of WAL files kept in pg_wal
◮ Zero trailing bytes during forced WAL switch
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21. 8. Allow ’quit’ and ’exit’ to Exit Psql
$ psql test
psql (11beta3)
Type "help" for help.
test=> quit
$ psql test
psql (11beta3)
Type "help" for help.
test=> exit
$ psql test
psql (11beta3)
Type "help" for help.
test=> SELECT
test-> quit
Use q to quit.
test-> q
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22. Allow ’quit’ and ’exit’ to Exit Psql
$ psql test
psql (11beta3)
Type "help" for help.
test=> quit
test-> exit
test-> q
$ psql test
psql (11beta3)
Type "help" for help.
test=> SELECT ’
test’> q
Use control-D to quit.
test’> ^D
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23. 9. Miscellaneous
◮ Allow unique indexes to contain non-unique columns via
INCLUDE
◮ additional columns can be used for index lookups or
index-only scans
◮ Window function improvements
◮ Add extensions to convert JSONB data to/from PL/Perl and
PL/Python
◮ Add support for large pages on Windows
◮ Allow pg_prewarm to restore previous shared buffer contents
◮ Allow a password prompt for TLS private key access
◮ Sharding advances
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