#postgres installation

[codeonedigest]

https://codeonedigest.blogspot.com/2023/07/run-postgres-database-in-docker.html

[eggman-is-fat-mkay]

i will strangle you

[reasonableapproximation]

A thing I've been looking into at work lately is collation, and specifically sorting. We want to compare in-memory implementations of things to postgres implementations, which means we need to reproduce postgres sorting in Haskell. Man it's a mess.

By default postgres uses glibc to sort. So we can use the FFI to reproduce it.

This mostly works fine, except if the locale says two things compare equal, postgres falls back to byte-comparing them. Which is also fine I guess, we can implement that too, but ugh.

Except also, this doesn't work for the mac user, so they can't reproduce test failures in the test suite we implemented this in.

How does postgres do sorting on mac? Not sure.

So we figured we'd use libicu for sorting. Postgres supports that, haskell supports it (through text-icu), should be fine. I'm starting off with a case-insensitive collation.

In postgres, you specify a collation through a string like en-u-ks-level2-numeric-true. (Here, en is a language, u is a separator, ks and numeric are keys and level2 and true are values. Some keys take multiple values, so you just have to know which strings are keys I guess?) In Haskell you can do it through "attributes" or "rules". Attributes are type safe but don't support everything you might want to do with locales. Rules are completely undocumented in text-icu, you pass in a string and it parses it. I'm pretty sure the parsing is implemented in libicu itself but it would be nice if text-icu gave you even a single example of what they look like.

But okay, I've got a locale in Haskell that I think should match the postgres one. Does it? Lolno

So there's a function collate for "compare these two strings in this locale", and a function sortKey for "get the sort key of this string in this locale". It should be that "collate l a b" is the same as "compare (sortKey l a) (sortKey l b)", but there are subtle edge cases where this isn't the case, like for example when a is the empty string and b is "\0". Or any string whose characters are all drawn from a set that includes NUL, lots of other control codes, and a handful of characters somewhere in the Arabic block. In these cases, collate says they're equal but sortKey says the empty string is smaller. But pg gets the same results as collate so fine, go with that.

Also seems like text-icu and pg disagree on which blocks get sorted before which other blocks, or something? At any rate I found a lot of pairs of (latin, non-latin) where text-icu sorts the non-latin first and pg sorts it second. So far I've solved this by just saying "only generate characters in the basic multilingual plane, and ignore anything in (long list of blocks)".

(Collations have an option for choosing which order blocks get sorted in, but it's not available with attributes. I haven't bothered to try it with rules, or with the format pg uses to specify them.)

I wonder how much of this is to do with using different versions of libicu. For Haskell we use a nix shell, which is providing version 72.1. Our postgres comes from a docker image and is using 63.1. When I install libicu on our CI images, they get 67.1 (and they can't reproduce the collate/sortKey bug with the arabic characters, so fine, remove them from the test set).

(I find out version numbers locally by doing lsof and seeing that the files are named like .so.63.1. Maybe ldd would work too? But because pg is in docker I don't know where the binary is. On CI I just look at the install logs.)

I wonder if I can get 63.1 in our nix shell. No, node doesn't support below 69. Fine, let's try 69. Did you know chromium depends on libicu? My laptop's been compiling chromium for many hours now.

[fromdevcom]

Java Database Connectivity API contains commonly asked Java interview questions. A good understanding of JDBC API is required to understand and leverage many powerful features of Java technology. Here are few important practical questions and answers which can be asked in a Core Java JDBC interview. Most of the java developers are required to use JDBC API in some type of application. Though its really common, not many people understand the real depth of this powerful java API. Dozens of relational databases are seamlessly connected using java due to the simplicity of this API. To name a few Oracle, MySQL, Postgres and MS SQL are some popular ones. This article is going to cover a lot of general questions and some of the really in-depth ones to. Java Interview Preparation Tips Part 0: Things You Must Know For a Java Interview Part 1: Core Java Interview Questions Part 2: JDBC Interview Questions Part 3: Collections Framework Interview Questions Part 4: Threading Interview Questions Part 5: Serialization Interview Questions Part 6: Classpath Related Questions Part 7: Java Architect Scalability Questions What are available drivers in JDBC? JDBC technology drivers fit into one of four categories: A JDBC-ODBC bridge provides JDBC API access via one or more ODBC drivers. Note that some ODBC native code and in many cases native database client code must be loaded on each client machine that uses this type of driver. Hence, this kind of driver is generally most appropriate when automatic installation and downloading of a Java technology application is not important. A native-API partly Java technology-enabled driver converts JDBC calls into calls on the client API for Oracle, Sybase, Informix, DB2, or other DBMS. Note that, like the bridge driver, this style of driver requires that some binary code be loaded on each client machine. A net-protocol fully Java technology-enabled driver translates JDBC API calls into a DBMS-independent net protocol which is then translated to a DBMS protocol by a server. This net server middleware is able to connect all of its Java technology-based clients to many different databases. The specific protocol used depends on the vendor. In general, this is the most flexible JDBC API alternative. It is likely that all vendors of this solution will provide products suitable for Intranet use. In order for these products to also support Internet access they must handle the additional requirements for security, access through firewalls, etc., that the Web imposes. Several vendors are adding JDBC technology-based drivers to their existing database middleware products. A native-protocol fully Java technology-enabled driver converts JDBC technology calls into the network protocol used by DBMSs directly. This allows a direct call from the client machine to the DBMS server and is a practical solution for Intranet access. Since many of these protocols are proprietary the database vendors themselves will be the primary source for this style of driver. Several database vendors have these in progress. What are the types of statements in JDBC? the JDBC API has 3 Interfaces, (1. Statement, 2. PreparedStatement, 3. CallableStatement ). The key features of these are as follows: Statement This interface is used for executing a static SQL statement and returning the results it produces. The object of Statement class can be created using Connection.createStatement() method. PreparedStatement A SQL statement is pre-compiled and stored in a PreparedStatement object. This object can then be used to efficiently execute this statement multiple times. The object of PreparedStatement class can be created using Connection.prepareStatement() method. This extends Statement interface. CallableStatement This interface is used to execute SQL stored procedures. This extends PreparedStatement interface. The object of CallableStatement class can be created using Connection.prepareCall() method.

What is a stored procedure? How to call stored procedure using JDBC API? Stored procedure is a group of SQL statements that forms a logical unit and performs a particular task. Stored Procedures are used to encapsulate a set of operations or queries to execute on database. Stored procedures can be compiled and executed with different parameters and results and may have any combination of input/output parameters. Stored procedures can be called using CallableStatement class in JDBC API. Below code snippet shows how this can be achieved. CallableStatement cs = con.prepareCall("call MY_STORED_PROC_NAME"); ResultSet rs = cs.executeQuery(); What is Connection pooling? What are the advantages of using a connection pool? Connection Pooling is a technique used for sharing the server resources among requested clients. It was pioneered by database vendors to allow multiple clients to share a cached set of connection objects that provides access to a database. Getting connection and disconnecting are costly operation, which affects the application performance, so we should avoid creating multiple connection during multiple database interactions. A pool contains set of Database connections which are already connected, and any client who wants to use it can take it from pool and when done with using it can be returned back to the pool. Apart from performance this also saves you resources as there may be limited database connections available for your application. How to do database connection using JDBC thin driver ? This is one of the most commonly asked questions from JDBC fundamentals, and knowing all the steps of JDBC connection is important. import java.sql.*; class JDBCTest public static void main (String args []) throws Exception //Load driver class Class.forName ("oracle.jdbc.driver.OracleDriver"); //Create connection Connection conn = DriverManager.getConnection ("jdbc:oracle:thin:@hostname:1526:testdb", "scott", "tiger"); // @machineName:port:SID, userid, password Statement stmt = conn.createStatement(); ResultSet rs = stmt.executeQuery("select 'Hi' from dual"); while (rs.next()) System.out.println (rs.getString(1)); // Print col 1 => Hi stmt.close(); What does Class.forName() method do? Method forName() is a static method of java.lang.Class. This can be used to dynamically load a class at run-time. Class.forName() loads the class if its not already loaded. It also executes the static block of loaded class. Then this method returns an instance of the loaded class. So a call to Class.forName('MyClass') is going to do following - Load the class MyClass. - Execute any static block code of MyClass. - Return an instance of MyClass. JDBC Driver loading using Class.forName is a good example of best use of this method. The driver loading is done like this Class.forName("org.mysql.Driver"); All JDBC Drivers have a static block that registers itself with DriverManager and DriverManager has static initializer method registerDriver() which can be called in a static blocks of Driver class. A MySQL JDBC Driver has a static initializer which looks like this: static try java.sql.DriverManager.registerDriver(new Driver()); catch (SQLException E) throw new RuntimeException("Can't register driver!"); Class.forName() loads driver class and executes the static block and the Driver registers itself with the DriverManager. Which one will you use Statement or PreparedStatement? Or Which one to use when (Statement/PreparedStatement)? Compare PreparedStatement vs Statement. By Java API definitions: Statement is a object used for executing a static SQL statement and returning the results it produces. PreparedStatement is a SQL statement which is precompiled and stored in a PreparedStatement object. This object can then be used to efficiently execute this statement multiple times. There are few advantages of using PreparedStatements over Statements

Since its pre-compiled, Executing the same query multiple times in loop, binding different parameter values each time is faster. (What does pre-compiled statement means? The prepared statement(pre-compiled) concept is not specific to Java, it is a database concept. Statement precompiling means: when you execute a SQL query, database server will prepare a execution plan before executing the actual query, this execution plan will be cached at database server for further execution.) In PreparedStatement the setDate()/setString() methods can be used to escape dates and strings properly, in a database-independent way. SQL injection attacks on a system are virtually impossible when using PreparedStatements. What does setAutoCommit(false) do? A JDBC connection is created in auto-commit mode by default. This means that each individual SQL statement is treated as a transaction and will be automatically committed as soon as it is executed. If you require two or more statements to be grouped into a transaction then you need to disable auto-commit mode using below command con.setAutoCommit(false); Once auto-commit mode is disabled, no SQL statements will be committed until you explicitly call the commit method. A Simple transaction with use of autocommit flag is demonstrated below. con.setAutoCommit(false); PreparedStatement updateStmt = con.prepareStatement( "UPDATE EMPLOYEE SET SALARY = ? WHERE EMP_NAME LIKE ?"); updateStmt.setInt(1, 5000); updateSales.setString(2, "Jack"); updateStmt.executeUpdate(); updateStmt.setInt(1, 6000); updateSales.setString(2, "Tom"); updateStmt.executeUpdate(); con.commit(); con.setAutoCommit(true); What are database warnings and How can I handle database warnings in JDBC? Warnings are issued by database to notify user of a problem which may not be very severe. Database warnings do not stop the execution of SQL statements. In JDBC SQLWarning is an exception that provides information on database access warnings. Warnings are silently chained to the object whose method caused it to be reported. Warnings may be retrieved from Connection, Statement, and ResultSet objects. Handling SQLWarning from connection object //Retrieving warning from connection object SQLWarning warning = conn.getWarnings(); //Retrieving next warning from warning object itself SQLWarning nextWarning = warning.getNextWarning(); //Clear all warnings reported for this Connection object. conn.clearWarnings(); Handling SQLWarning from Statement object //Retrieving warning from statement object stmt.getWarnings(); //Retrieving next warning from warning object itself SQLWarning nextWarning = warning.getNextWarning(); //Clear all warnings reported for this Statement object. stmt.clearWarnings(); Handling SQLWarning from ResultSet object //Retrieving warning from resultset object rs.getWarnings(); //Retrieving next warning from warning object itself SQLWarning nextWarning = warning.getNextWarning(); //Clear all warnings reported for this resultset object. rs.clearWarnings(); The call to getWarnings() method in any of above way retrieves the first warning reported by calls on this object. If there is more than one warning, subsequent warnings will be chained to the first one and can be retrieved by calling the method SQLWarning.getNextWarning on the warning that was retrieved previously. A call to clearWarnings() method clears all warnings reported for this object. After a call to this method, the method getWarnings returns null until a new warning is reported for this object. Trying to call getWarning() on a connection after it has been closed will cause an SQLException to be thrown. Similarly, trying to retrieve a warning on a statement after it has been closed or on a result set after it has been closed will cause an SQLException to be thrown. Note that closing a statement also closes a result set that it might have produced. What is Metadata and why should I use it?

JDBC API has 2 Metadata interfaces DatabaseMetaData & ResultSetMetaData. The DatabaseMetaData provides Comprehensive information about the database as a whole. This interface is implemented by driver vendors to let users know the capabilities of a Database Management System (DBMS) in combination with the driver based on JDBC technology ("JDBC driver") that is used with it. Below is a sample code which demonstrates how we can use the DatabaseMetaData DatabaseMetaData md = conn.getMetaData(); System.out.println("Database Name: " + md.getDatabaseProductName()); System.out.println("Database Version: " + md.getDatabaseProductVersion()); System.out.println("Driver Name: " + md.getDriverName()); System.out.println("Driver Version: " + md.getDriverVersion()); The ResultSetMetaData is an object that can be used to get information about the types and properties of the columns in a ResultSet object. Use DatabaseMetaData to find information about your database, such as its capabilities and structure. Use ResultSetMetaData to find information about the results of an SQL query, such as size and types of columns. Below a sample code which demonstrates how we can use the ResultSetMetaData ResultSet rs = stmt.executeQuery("SELECT a, b, c FROM TABLE2"); ResultSetMetaData rsmd = rs.getMetaData(); int numberOfColumns = rsmd.getColumnCount(); boolean b = rsmd.isSearchable(1); What is RowSet? or What is the difference between RowSet and ResultSet? or Why do we need RowSet? or What are the advantages of using RowSet over ResultSet? RowSet is a interface that adds support to the JDBC API for the JavaBeans component model. A rowset, which can be used as a JavaBeans component in a visual Bean development environment, can be created and configured at design time and executed at run time. The RowSet interface provides a set of JavaBeans properties that allow a RowSet instance to be configured to connect to a JDBC data source and read some data from the data source. A group of setter methods (setInt, setBytes, setString, and so on) provide a way to pass input parameters to a rowset's command property. This command is the SQL query the rowset uses when it gets its data from a relational database, which is generally the case. Rowsets are easy to use since the RowSet interface extends the standard java.sql.ResultSet interface so it has all the methods of ResultSet. There are two clear advantages of using RowSet over ResultSet RowSet makes it possible to use the ResultSet object as a JavaBeans component. As a consequence, a result set can, for example, be a component in a Swing application. RowSet be used to make a ResultSet object scrollable and updatable. All RowSet objects are by default scrollable and updatable. If the driver and database being used do not support scrolling and/or updating of result sets, an application can populate a RowSet object implementation (e.g. JdbcRowSet) with the data of a ResultSet object and then operate on the RowSet object as if it were the ResultSet object. What is a connected RowSet? or What is the difference between connected RowSet and disconnected RowSet? or Connected vs Disconnected RowSet, which one should I use and when? Connected RowSet A RowSet object may make a connection with a data source and maintain that connection throughout its life cycle, in which case it is called a connected rowset. A rowset may also make a connection with a data source, get data from it, and then close the connection. Such a rowset is called a disconnected rowset. A disconnected rowset may make changes to its data while it is disconnected and then send the changes back to the original source of the data, but it must reestablish a connection to do so. Example of Connected RowSet: A JdbcRowSet object is a example of connected RowSet, which means it continually maintains its connection to a database using a JDBC technology-enabled driver. Disconnected RowSet A disconnected rowset may have a reader (a RowSetReader object) and a writer (a RowSetWriter object) associated with it.

The reader may be implemented in many different ways to populate a rowset with data, including getting data from a non-relational data source. The writer can also be implemented in many different ways to propagate changes made to the rowset's data back to the underlying data source. Example of Disconnected RowSet: A CachedRowSet object is a example of disconnected rowset, which means that it makes use of a connection to its data source only briefly. It connects to its data source while it is reading data to populate itself with rows and again while it is propagating changes back to its underlying data source. The rest of the time, a CachedRowSet object is disconnected, including while its data is being modified. Being disconnected makes a RowSet object much leaner and therefore much easier to pass to another component. For example, a disconnected RowSet object can be serialized and passed over the wire to a thin client such as a personal digital assistant (PDA). What is the benefit of having JdbcRowSet implementation? Why do we need a JdbcRowSet like wrapper around ResultSet? The JdbcRowSet implementation is a wrapper around a ResultSet object that has following advantages over ResultSet This implementation makes it possible to use the ResultSet object as a JavaBeans component. A JdbcRowSet can be used as a JavaBeans component in a visual Bean development environment, can be created and configured at design time and executed at run time. It can be used to make a ResultSet object scrollable and updatable. All RowSet objects are by default scrollable and updatable. If the driver and database being used do not support scrolling and/or updating of result sets, an application can populate a JdbcRowSet object with the data of a ResultSet object and then operate on the JdbcRowSet object as if it were the ResultSet object. Can you think of a questions which is not part of this post? Please don't forget to share it with me in comments section & I will try to include it in the list.

[devnews]

🔥 Top 37 GitHub Projects You Can't Miss (March 2025)!

Javascript Developer Resources – Made by 0x3d.site A curated hub for Javascript developers featuring essential tools, articles, and trending discussions. Bookmark it: javascript.0x3d.site 1. WASD: Wireless Anomaly Signal Dataset Check it out! 2. Pgserver: Super easy pip-installable Postgres Check it out! 3. Cutting-edge web scraping techniques Check it out! 4. Deploy from local to…

[wingedmiraclesublime]

蜘蛛池源码如何部署？

蜘蛛池，也被称为“爬虫池”或“爬虫集群”，是一种用于提高网络爬取效率的技术。通过将多个爬虫任务分配到不同的服务器上运行，可以显著提升数据抓取的速度和稳定性。本文将详细介绍如何部署蜘蛛池源码，帮助你快速搭建自己的爬虫集群。

1. 环境准备

在开始部署之前，确保你的服务器环境满足以下要求：

- 操作系统：Linux（推荐Ubuntu）

- Python环境：Python 3.x

- 其他依赖库：Scrapy、Twisted等

安装Python环境

如果你的服务器尚未安装Python 3.x，可以通过以下命令进行安装：

```bash

sudo apt-get update

sudo apt-get install python3

```

安装依赖库

使用pip安装所需的Python库：

```bash

pip3 install scrapy twisted

```

2. 获取源码

从GitHub或其他代码托管平台获取蜘蛛池的源码。假设源码位于`https://github.com/username/spiderpool.git`，你可以通过以下命令克隆项目：

```bash

git clone https://github.com/username/spiderpool.git

cd spiderpool

```

3. 配置文件

进入项目目录后，找到配置文件（通常为`settings.py`），根据你的需求进行配置。主要配置项包括数据库连接信息、爬虫任务队列等。

```python

DATABASE = {

'drivername': 'postgres',

'host': 'localhost',

'port': '5432',

'username': 'your_username',

'password': 'your_password',

'database': 'spiderpool'

}

```

4. 启动服务

启动蜘蛛池服务通常需要运行一个主进程和多个工作进程。具体命令可能因项目不同而异，但一般形式如下：

```bash

python manage.py startmaster

python manage.py startworker

```

5. 监控与维护

部署完成后，定期监控蜘蛛池的运行状态，确保所有工作进程正常运行。同时，根据实际需求调整配置参数，优化爬虫性能。

讨论点

你在部署蜘蛛池的过程中遇到了哪些问题？又是如何解决的呢？欢迎在评论区分享你的经验，让我们一起学习进步！

加飞机@yuantou2048

谷歌霸屏

Google外链购买

[learning-code-ficusoft]

Using Docker for Full Stack Development and Deployment

1. Introduction to Docker

What is Docker? Docker is an open-source platform that automates the deployment, scaling, and management of applications inside containers. A container packages your application and its dependencies, ensuring it runs consistently across different computing environments.

Containers vs Virtual Machines (VMs)

Containers are lightweight and use fewer resources than VMs because they share the host operating system’s kernel, while VMs simulate an entire operating system. Containers are more efficient and easier to deploy.

Docker containers provide faster startup times, less overhead, and portability across development, staging, and production environments.

Benefits of Docker in Full Stack Development

Portability: Docker ensures that your application runs the same way regardless of the environment (dev, test, or production).

Consistency: Developers can share Dockerfiles to create identical environments for different developers.

Scalability: Docker containers can be quickly replicated, allowing your application to scale horizontally without a lot of overhead.

Isolation: Docker containers provide isolated environments for each part of your application, ensuring that dependencies don’t conflict.

2. Setting Up Docker for Full Stack Applications

Installing Docker and Docker Compose

Docker can be installed on any system (Windows, macOS, Linux). Provide steps for installing Docker and Docker Compose (which simplifies multi-container management).

Commands:

docker --version to check the installed Docker version.

docker-compose --version to check the Docker Compose version.

Setting Up Project Structure

Organize your project into different directories (e.g., /frontend, /backend, /db).

Each service will have its own Dockerfile and configuration file for Docker Compose.

3. Creating Dockerfiles for Frontend and Backend

Dockerfile for the Frontend:

For a React/Angular app:

Dockerfile

FROM node:14 WORKDIR /app COPY package*.json ./ RUN npm install COPY . . EXPOSE 3000 CMD ["npm", "start"]

This Dockerfile installs Node.js dependencies, copies the application, exposes the appropriate port, and starts the server.

Dockerfile for the Backend:

For a Python Flask app

Dockerfile

FROM python:3.9 WORKDIR /app COPY requirements.txt . RUN pip install -r requirements.txt COPY . . EXPOSE 5000 CMD ["python", "app.py"]

For a Java Spring Boot app:

Dockerfile

FROM openjdk:11 WORKDIR /app COPY target/my-app.jar my-app.jar EXPOSE 8080 CMD ["java", "-jar", "my-app.jar"]

This Dockerfile installs the necessary dependencies, copies the code, exposes the necessary port, and runs the app.

4. Docker Compose for Multi-Container Applications

What is Docker Compose? Docker Compose is a tool for defining and running multi-container Docker applications. With a docker-compose.yml file, you can configure services, networks, and volumes.

docker-compose.yml Example:

yaml

version: "3" services: frontend: build: context: ./frontend ports: - "3000:3000" backend: build: context: ./backend ports: - "5000:5000" depends_on: - db db: image: postgres environment: POSTGRES_USER: user POSTGRES_PASSWORD: password POSTGRES_DB: mydb

This YAML file defines three services: frontend, backend, and a PostgreSQL database. It also sets up networking and environment variables.

5. Building and Running Docker Containers

Building Docker Images:

Use docker build -t <image_name> <path> to build images.

For example:

bash

docker build -t frontend ./frontend docker build -t backend ./backend

Running Containers:

You can run individual containers using docker run or use Docker Compose to start all services:

bash

docker-compose up

Use docker ps to list running containers, and docker logs <container_id> to check logs.

Stopping and Removing Containers:

Use docker stop <container_id> and docker rm <container_id> to stop and remove containers.

With Docker Compose: docker-compose down to stop and remove all services.

6. Dockerizing Databases

Running Databases in Docker:

You can easily run databases like PostgreSQL, MySQL, or MongoDB as Docker containers.

Example for PostgreSQL in docker-compose.yml:

yaml

db: image: postgres environment: POSTGRES_USER: user POSTGRES_PASSWORD: password POSTGRES_DB: mydb

Persistent Storage with Docker Volumes:

Use Docker volumes to persist database data even when containers are stopped or removed:

yaml

volumes: - db_data:/var/lib/postgresql/data

Define the volume at the bottom of the file:

yaml

volumes: db_data:

Connecting Backend to Databases:

Your backend services can access databases via Docker networking. In the backend service, refer to the database by its service name (e.g., db).

7. Continuous Integration and Deployment (CI/CD) with Docker

Setting Up a CI/CD Pipeline:

Use Docker in CI/CD pipelines to ensure consistency across environments.

Example: GitHub Actions or Jenkins pipeline using Docker to build and push images.

Example .github/workflows/docker.yml:

yaml

name: CI/CD Pipeline on: [push] jobs: build: runs-on: ubuntu-latest steps: - name: Checkout Code uses: actions/checkout@v2 - name: Build Docker Image run: docker build -t myapp . - name: Push Docker Image run: docker push myapp

Automating Deployment:

Once images are built and pushed to a Docker registry (e.g., Docker Hub, Amazon ECR), they can be pulled into your production or staging environment.

8. Scaling Applications with Docker

Docker Swarm for Orchestration:

Docker Swarm is a native clustering and orchestration tool for Docker. You can scale your services by specifying the number of replicas.

Example:

bash

docker service scale myapp=5

Kubernetes for Advanced Orchestration:

Kubernetes (K8s) is more complex but offers greater scalability and fault tolerance. It can manage Docker containers at scale.

Load Balancing and Service Discovery:

Use Docker Swarm or Kubernetes to automatically load balance traffic to different container replicas.

9. Best Practices

Optimizing Docker Images:

Use smaller base images (e.g., alpine images) to reduce image size.

Use multi-stage builds to avoid unnecessary dependencies in the final image.

Environment Variables and Secrets Management:

Store sensitive data like API keys or database credentials in Docker secrets or environment variables rather than hardcoding them.

Logging and Monitoring:

Use tools like Docker’s built-in logging drivers, or integrate with ELK stack (Elasticsearch, Logstash, Kibana) for advanced logging.

For monitoring, tools like Prometheus and Grafana can be used to track Docker container metrics.

10. Conclusion

Why Use Docker in Full Stack Development? Docker simplifies the management of complex full-stack applications by ensuring consistent environments across all stages of development. It also offers significant performance benefits and scalability options.

Recommendations:

Encourage users to integrate Docker with CI/CD pipelines for automated builds and deployment.

Mention the use of Docker for microservices architecture, enabling easy scaling and management of individual services.

WEBSITE: https://www.ficusoft.in/full-stack-developer-course-in-chennai/

[actautoelectrical]

ACT Auto Electrical Listed on PostgresConf – Trusted Auto Electrical Experts

ACT Auto Electrical is now listed on PostgresConf, making our auto electrical services more accessible than ever. We specialize in repairs, wiring, diagnostics, and installations for a wide range of vehicles, including trucks, tractors, and earthmoving equipment. Our team ensures efficiency and reliability in every job. Visit our PostgresConf profile to learn more about our services and how we can assist with your vehicle's electrical needs.

[techexperttutorials]

How to Install Postgres 17 and pgAdmin in Windows

[saifosys]

Sonarqube Setup with Postgresql

sonarqube installation along with java 17 Postgresql Database Prerequisites Need an AWS EC2 instance (min t2.small)  Install Java 17 (openjdk-17) apt-get update apt list | grep openjdk-17 apt-get install openjdk-17-jdk -y Install & Setup Postgres Database for SonarQube Source: https://www.postgresql.org/download/linux/ubuntu/ Install Postgresql database Import the repository signing…

[cameronmcnz]

How to Install PostgreSQL on Windows 10 or 11 #postgres #javascript #pyt...

[suncloudvn]

PostgreSQL là gì? Cách cài đặt và so sánh PostgreSQL vs MySQL

PostgreSQL là một hệ quản trị cơ sở dữ liệu quan hệ mạnh mẽ và linh hoạt, được sử dụng rộng rãi trong nhiều ứng dụng từ nhỏ đến lớn. Bài viết này sẽ cung cấp cho bạn cái nhìn tổng quan về PostgreSQL là gì, hướng dẫn cài đặt chi tiết và so sánh sự khác biệt giữa PostgreSQL và MySQL. Qua đó, bạn sẽ nắm bắt được những điểm mạnh, điểm yếu của từng hệ thống và đưa ra lựa chọn phù hợp nhất cho nhu cầu của mình. Hãy cùng khám phá ngay nhé!

1. PostgreSQL là gì?

PostgreSQL thường được gọi là Postgres, là một hệ quản trị cơ sở dữ liệu quan hệ đối tượng (ORDBMS) mã nguồn mở và mạnh mẽ. Được phát triển lần đầu tiên vào năm 1986 tại Đại học California, Berkeley, PostgreSQL đã trở thành một trong những hệ quản trị cơ sở dữ liệu phổ biến nhất trên thế giới nhờ vào tính linh hoạt, khả năng mở rộng và tính bảo mật cao.

Các tính năng nổi bật của PostgreSQL là gì?

PostgreSQL đảm bảo tính toàn vẹn của dữ liệu thông qua việc tuân thủ đầy đủ các thuộc tính ACID. Điều này đảm bảo rằng tất cả các giao dịch trong cơ sở dữ liệu đều được thực hiện một cách toàn vẹn và an toàn.

PostgreSQL hỗ trợ nhiều loại dữ liệu khác nhau, từ các loại dữ liệu cơ bản như integer, varchar đến các loại dữ liệu phức tạp hơn như JSON, XML. Điều này giúp PostgreSQL trở thành một lựa chọn lý tưởng cho các ứng dụng đòi hỏi xử lý dữ liệu đa dạng.

Mở rộng và tùy biến: Người dùng có thể tạo các loại dữ liệu mới, hàm mới, chỉ mục và thậm chí là các ngôn ngữ lập trình mới để mở rộng chức năng của cơ sở dữ liệu.

PostgreSQL cung cấp nhiều tính năng bảo mật mạnh mẽ như xác thực dựa trên vai trò, mã hóa dữ liệu (data encryption) và hỗ trợ các giao thức bảo mật như SSL/TLS giúp bảo vệ dữ liệu khỏi các mối đe dọa từ bên ngoài và đảm bảo tính riêng tư của dữ liệu.

PostgreSQL có khả năng xử lý các truy vấn phức tạp và khối lượng dữ liệu lớn thông qua hỗ trợ song song và phân tán. Các tính năng như sharding và replication giúp PostgreSQL có thể mở rộng và duy trì hiệu suất cao ngay cả khi khối lượng dữ liệu tăng lên.

Phiên bản cập nhật mới nhất của PostgreSQL

PostgreSQL 14, phiên bản mới nhất tính đến năm 2024, mang lại nhiều cải tiến đáng kể về hiệu suất và tính năng. Một số cải tiến nổi bật như:

Cải tiến hiệu suất: PostgreSQL 14 cải thiện hiệu suất của các truy vấn song song, giúp tăng tốc độ xử lý các truy vấn phức tạp.

Quản lý bộ nhớ tốt hơn: Phiên bản mới cung cấp các cơ chế quản lý bộ nhớ tiên tiến, giúp tối ưu hóa việc sử dụng t��i nguyên hệ thống.

Hỗ trợ tốt hơn cho JSON: PostgreSQL 14 cải thiện hỗ trợ cho việc xử lý dữ liệu JSON, giúp dễ dàng hơn trong việc làm việc với các ứng dụng web và dịch vụ RESTful.

Cải tiến về bảo mật: Các tính năng bảo mật mới như cải thiện mã hóa và xác thực giúp bảo vệ dữ liệu tốt hơn.

2. Hướng dẫn cài đặt PostgreSQL

Cài đặt trên Linux

Để cài đặt PostgreSQL trên hệ điều hành Linux, bạn có thể sử dụng các gói phần mềm từ kho của hệ điều hành. Ví dụ, trên Ubuntu, bạn có thể cài đặt PostgreSQL bằng lệnh sau:

sudo apt update

sudo apt install postgresql postgresql-contrib

Cài đặt trên Windows

PostgreSQL cung cấp các bộ cài đặt cho Windows, bạn có thể tải về từ trang web chính thức của PostgreSQL. Sau khi tải về, bạn chỉ cần chạy file cài đặt và làm theo hướng dẫn để hoàn tất quá trình cài đặt.

Cài đặt trên macOS

Trên macOS, bạn có thể cài đặt PostgreSQL thông qua Homebrew:

brew update

brew install postgresql

Sau khi cài đặt, bạn có thể khởi động PostgreSQL bằng lệnh:

brew services start postgresql

3. Sự khác biệt PostgreSQL vs MySQL là gì?

PostgreSQL và MySQL là hai hệ quản trị cơ sở dữ liệu quan hệ phổ biến, mỗi hệ có những đặc điểm và ưu điểm riêng. Dưới đây là sự khác biệt chính giữa PostgreSQL và MySQL:

Kết luận

PostgreSQL là một hệ quản trị cơ sở dữ liệu mạnh mẽ và linh hoạt, phù hợp với nhiều loại ứng dụng khác nhau từ web, phân tích dữ liệu, đến các ứng dụng GIS. Với các tính năng tiên tiến, tính bảo mật cao và khả năng mở rộng tốt, PostgreSQL đã và đang là lựa chọn hàng đầu của nhiều nhà phát triển và tổ chức trên toàn thế giới. Hy vọng qua bài viết bạn đã hiểu rõ PostgreSQL là gì cũng như sự khác biệt so với MySQL. Nếu có bất kỳ câu hỏi gì cần giải đáp, hãy liên hệ với chúng tôi để được tư vấn, hỗ trợ nhanh nhất nhé.

Nguồn: https://suncloud.vn/postgresql-la-gi

[tutorialwithexample]

Unlocking PostgreSQL Power: Tips, Tricks, and Hands-On Tutorial

Welcome to our PostgreSQL Tutorial! PostgreSQL, often called "Postgres," is a powerful, open-source database system used by developers and businesses worldwide. Whether you’re building a small application or managing large datasets, PostgreSQL is versatile and reliable.

What is PostgreSQL?

PostgreSQL is a relational database management system (RDBMS). This means it organizes data into tables that can be linked by relationships. It supports SQL (Structured Query Language), the standard language for interacting with databases.

Why Choose PostgreSQL?

Open Source: PostgreSQL is free to use and has a strong community support.

Extensibility: It allows you to create custom functions and data types.

Performance: PostgreSQL handles large volumes of data efficiently.

ACID Compliance: Ensures data integrity with reliable transactions.

Getting Started

Installation: Download and install PostgreSQL from the official website. It supports Windows, macOS, and Linux.

Connecting to PostgreSQL: Use the psql command-line tool or GUI tools like pgAdmin to connect and manage your database.

Creating a Database: Use the command CREATE DATABASE followed by your desired database name.

Basic Operations

Inserting Data: Add records using the INSERT INTO command.

Querying Data: Retrieve data with the SELECT statement.

Updating Data: Modify existing records using UPDATE.

Deleting Data: Remove unwanted records with DELETE.

Explore More

To dive deeper into PostgreSQL and explore advanced features, check out this PostgreSQL Tutorial. Happy learning!

By following this PostgreSQL Tutorial, you'll quickly become comfortable managing and querying your databases with ease.

[qcs01]

Managing Containerized Applications Using Ansible: A Guide for College Students and Working Professionals

As containerization becomes a cornerstone of modern application deployment, managing containerized applications effectively is crucial. Ansible, a powerful automation tool, provides robust capabilities for managing these containerized environments. This blog post will guide you through the process of managing containerized applications using Ansible, tailored for both college students and working professionals.

What is Ansible?

Ansible is an open-source automation tool that simplifies configuration management, application deployment, and task automation. It's known for its agentless architecture, ease of use, and powerful features, making it ideal for managing containerized applications.

Why Use Ansible for Container Management?

Consistency: Ensure that container configurations are consistent across different environments.

Automation: Automate repetitive tasks such as container deployment, scaling, and monitoring.

Scalability: Manage containers at scale, across multiple hosts and environments.

Integration: Seamlessly integrate with CI/CD pipelines, monitoring tools, and other infrastructure components.

Prerequisites

Before you start, ensure you have the following:

Ansible installed on your local machine.

Docker installed on the target hosts.

Basic knowledge of YAML and Docker.

Setting Up Ansible

Install Ansible on your local machine:

pip install ansible

Basic Concepts

Inventory

An inventory file lists the hosts and groups of hosts that Ansible manages. Here's a simple example:

[containers] host1.example.com host2.example.com

Playbooks

Playbooks define the tasks to be executed on the managed hosts. Below is an example of a playbook to manage Docker containers.

Example Playbook: Deploying a Docker Container

Let's start with a simple example of deploying an NGINX container using Ansible.

Step 1: Create the Inventory File

Create a file named inventory:

[containers] localhost ansible_connection=local

Step 2: Create the Playbook

Create a file named deploy_nginx.yml:

name: Deploy NGINX container hosts: containers become: yes tasks:

name: Install Docker apt: name: docker.io state: present when: ansible_os_family == "Debian"

name: Ensure Docker is running service: name: docker state: started enabled: yes

name: Pull NGINX image docker_image: name: nginx source: pull

name: Run NGINX container docker_container: name: nginx image: nginx state: started ports:

"80:80"

Step 3: Run the Playbook

Execute the playbook using the following command:

ansible-playbook -i inventory deploy_nginx.yml

Advanced Topics

Managing Multi-Container Applications

For more complex applications, such as those defined by Docker Compose, you can manage multi-container setups with Ansible.

Example: Deploying a Docker Compose Application

Create a Docker Compose file docker-compose.yml:

version: '3' services: web: image: nginx ports: - "80:80" db: image: postgres environment: POSTGRES_PASSWORD: example

Create an Ansible playbook deploy_compose.yml:

name: Deploy Docker Compose application hosts: containers become: yes tasks:

name: Install Docker apt: name: docker.io state: present when: ansible_os_family == "Debian"

name: Install Docker Compose get_url: url: https://github.com/docker/compose/releases/download/1.29.2/docker-compose-uname -s-uname -m dest: /usr/local/bin/docker-compose mode: '0755'

name: Create Docker Compose file copy: dest: /opt/docker-compose.yml content: | version: '3' services: web: image: nginx ports: - "80:80" db: image: postgres environment: POSTGRES_PASSWORD: example

name: Run Docker Compose command: docker-compose -f /opt/docker-compose.yml up -d

Run the playbook:

ansible-playbook -i inventory deploy_compose.yml

Integrating Ansible with CI/CD

Ansible can be integrated into CI/CD pipelines for continuous deployment of containerized applications. Tools like Jenkins, GitLab CI, and GitHub Actions can trigger Ansible playbooks to deploy containers whenever new code is pushed.

Example: Using GitHub Actions

Create a GitHub Actions workflow file .github/workflows/deploy.yml:

name: Deploy with Ansible

on: push: branches: - main

jobs: deploy: runs-on: ubuntu-lateststeps: - name: Checkout code uses: actions/checkout@v2 - name: Set up Ansible run: sudo apt update && sudo apt install -y ansible - name: Run Ansible playbook run: ansible-playbook -i inventory deploy_compose.yml

Conclusion

Managing containerized applications with Ansible streamlines the deployment and maintenance processes, ensuring consistency and reliability. Whether you're a college student diving into DevOps or a working professional seeking to enhance your automation skills, Ansible provides the tools you need to efficiently manage your containerized environments.

For more details click www.qcsdclabs.com