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Develop a Kafka producer to send messages to a Kafka topic

Here’s a guide and code examples to develop a Kafka producer to send messages to a Kafka topic. The examples cover both plain Kafka Producer API and Spring Kafka Producer for convenience. 1. Plain Kafka Producer API Maven Dependencies Add the Kafka client dependency in your pom.xml : < dependency > < groupId > org.apache.kafka </ groupId > < artifactId > kafka-clients </ artifactId > < version > 3.6.0 </ version > <!-- Replace with your Kafka version --> </ dependency > Java Code Example This example demonstrates producing messages to a Kafka topic using the plain Kafka Producer API. import org.apache.kafka.clients.producer.KafkaProducer; import org.apache.kafka.clients.producer.ProducerRecord; import org.apache.kafka.clients.producer.RecordMetadata; import java.util.Properties; public class KafkaMessageProducer { public static void main( String [] args) { // Configure Kafka produce...
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Using the MinIO API via curl

Using the MinIO API via curl is straightforward, as MinIO is compatible with Amazon S3 API, so most commands follow a similar syntax. Here’s a guide on how to use curl with the MinIO API for some common operations like uploading, downloading, and managing objects. Prerequisites Access Key and Secret Key : Obtain your MinIO Access Key and Secret Key. MinIO Endpoint : Know your MinIO server endpoint, e.g., http://localhost:9000 . Bucket : You may need an existing bucket name, or create a new one using the commands below. Authentication Header For requests to work with MinIO, you need to include authentication in the headers. MinIO uses AWS Signature Version 4 for signing requests. Common Examples 1. List Buckets To list all buckets in your MinIO account, use: curl -X GET \ - -url "http://localhost:9000/" \ - H "Authorization: AWS <AccessKey>:<Signature>" 2. Create a Bucket To create a new bucket, use: curl -X PUT \ - -url "htt...
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max_active_runs of Airflow

In Apache Airflow, if you want to ensure that a new run of a DAG doesn’t start before the previous one has completed, you can use the max_active_runs parameter in the DAG definition. Setting this parameter to 1 ensures that only one instance of the DAG is running at any given time. Setting max_active_runs for a DAG Here’s an example of how to set up a DAG with max_active_runs=1 : from airflow import DAG from airflow.operators.dummy_operator import DummyOperator from datetime import datetime # Define the DAG with DAG( 'my_dag' , description= 'A sample DAG' , schedule_interval= '@daily' , # Set your schedule start_date=datetime( 2023 , 1 , 1 ), catchup= False , max_active_runs= 1 # This prevents new runs before the previous run completes ) as dag: # Define tasks start = DummyOperator(task_id= 'start' ) end = DummyOperator(task_id= 'end' ) # Define task dependencies ...
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Boilerplate for typescript server programing

Here are some recommended boilerplates and frameworks for TypeScript server programming, depending on your requirements: 1. NestJS (Highly Recommended for Enterprise-Grade Applications) NestJS is a progressive Node.js framework built with TypeScript. It provides an opinionated structure and is excellent for building scalable and maintainable server-side applications. Features : Dependency injection Modular architecture Built-in support for WebSockets, GraphQL, REST APIs Easy integration with tools like Swagger, TypeORM, and Mongoose Getting Started : Install Nest CLI: npm i -g @nestjs/cli nest new project-name Boilerplate is automatically generated with ready-to-use configurations for controllers, services, and modules. Website : https://nestjs.com/ 2. Express with TypeScript Express.js is lightweight and minimal, making it ideal for developers who prefer flexibility over opinionated frameworks. Boilerplate : You can start with an official or community-maintai...
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how to delete all issues on project in sentry, 센트리 이슈 삭제하기

As of now, Sentry doesn't have a direct feature to delete all issues in bulk through the web interface. However, there are a few methods you can use to archive, resolve, or delete issues programmatically or by adjusting project settings: 1. Bulk Archive Issues from the Web Interface Though there is no mass delete option, you can bulk archive or resolve issues, which essentially hides them from active issue lists. Steps: Go to your Sentry project. In the issue list view, select the issues you want to archive or resolve. Use the "Select All" checkbox to select multiple issues. Choose "Resolve" or "Archive" from the bulk action dropdown. However, this doesn't delete the issues permanently; they will be archived or marked as resolved. 2. Adjust Retention Policy (Data Retention Settings) If you're looking to remove older issues, you can adjust the retention policy at the organization level. Sentry allows you to configure how long issue...
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difference between truncate and truncate_preserve in hbase

In HBase, both truncate and truncate_preserve commands are used to delete all the data in a table, but they behave differently in terms of how they handle the table’s schema and regions. 1. truncate Purpose : Deletes all data and regions in a table and then recreates it with the same schema. What It Does : When you run truncate , it: Disables the table. Deletes all data and metadata (including region splits) in the table. Drops all regions and recreates the table as a single region with the original schema. Re-enables the table. Effect on Regions : After truncate , all region splits are lost, so the table will start with only one region. This is useful for development or quick data purging but is inefficient for large tables that rely on pre-split regions for load balancing. Command Syntax : truncate 'table_name' 2. truncate_preserve Purpose : Deletes all data in a table but preserves the table’s regions and schema. What It Does : When you use truncate_...
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Reactjs datetime range picker

To create a datetime range picker in React, you can use a library such as react-datetime-range-picker . This library provides a customizable date and time range picker component that you can easily integrate into your React application. Here's an example of how you can use it: Install the library using npm or yarn: npm install react-datetime- range -picker Import the necessary components into your React component: import React, { useState } from 'react' ; import DateTimeRangePicker from 'react-datetime-range-picker' ; Create a state to hold the selected date and time range: const [selectedRange, setSelectedRange] = useState({ startDate: null , endDate: null }); Render the DateTimeRangePicker component and handle the selection changes: ```jsx const handleRangeChange = (range) => { setSelectedRange(range); }; return ( ); ``` In the example above, the DateTimeRangePicker component is rendered with the onChange event handler and th...
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[Ubuntu] Apache2.4.x 설치

Apache2.4.x 버전부터는 APR 과 APR-util을 별로도 설치하여야 한다. 하위버전에서는 설치파일에 포함되어 있었으나 버전 업이 되면서 삭제되어 configure를 실행하면 아래와 같은 에러메시지를 발생하면서 종료된다. Configuring Apache Portable Runtime library ... Checking for APR... no Confgirue: error: APR not found. Please read the documentation http://apr.apache.org/   에서 다운받아 설치함 *APR(Apache Portable Runtime) 설치 $ wget http://mirror.sdunix.com/apache//apr/apr-1.4.6.tar.gz $ tar xvf apr-1.4.6.tar.gz ~/apr-1.4.6$ ./configure ~/apr-1.4.6$ ./make ~/apr-1.4.6$ ./sudo make install *ARP-Util 설치 $ wget http://apache.tt.co.kr//apr/apr-util-1.4.1.tar.gz $ tar xvf apr-util-1.4.1.tar.gz ~/apr-util-1.4.1$ ./configure --with-apr=/usr/local/apr ~/apr-util-1.4.1$ make ~/apr-util-1.4.1$ sudo make install Apache 재설치시 Error 발생. configure: error: pcre-config for libpcre not found.PCRE is required and available from http://pcre.org/ *PCRE(Perl Compatible Regular Expressions) 설치 $ ...
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Kafka consumer in a Spring Boot application using a scheduled task

Here’s how to develop a Kafka consumer in a Spring Boot application using a scheduled task for consuming messages. This approach uses @Scheduled to poll Kafka messages at fixed intervals. Step 1: Add Maven Dependencies Add the required dependencies for Spring Kafka and Scheduling in your pom.xml : < dependency > < groupId > org.springframework.kafka </ groupId > < artifactId > spring-kafka </ artifactId > </ dependency > < dependency > < groupId > org.springframework.boot </ groupId > < artifactId > spring-boot-starter </ artifactId > </ dependency > Step 2: Configure Kafka Consumer in application.yml spring: kafka: bootstrap-servers: localhost: 9092 consumer: group-id: schedule-consumer-group key-deserializer: org .apache .kafka .common .serialization .StringDeserializer value-deserializer: org .apache .kafka .common .serialization .StringDeserialize...
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운영체제를 개발 방법

운영체제(OS)를 개발하는 것은 매우 복잡하고 기술적으로 도전적인 작업입니다. 이는 컴퓨터 하드웨어와 소프트웨어 간의 상호작용을 관리하는 핵심 소프트웨어이기 때문입니다. 아래는 새로운 운영체제를 개발하는 데 필요한 주요 단계를 정리한 내용입니다. 1. 목적과 요구사항 정의 운영체제의 목적 : 개인용, 서버용, 임베디드 시스템 등 어떤 용도로 사용할지 결정하세요. 핵심 기능 정의 : 파일 시스템, 프로세스 관리, 메모리 관리, 네트워크 지원 등 필수 기능을 정리합니다. 목표 플랫폼 : x86, ARM, RISC-V 등 어떤 하드웨어 아키텍처를 지원할지 결정합니다. 2. 운영체제 설계 커널 타입 선택 : 모놀리식 커널 : 성능은 좋지만 복잡성이 높음. 마이크로커널 : 모듈화가 잘 되어 유지보수가 쉬움. 하이브리드 커널 : 위 두 가지의 장점을 결합. 사용자 인터페이스(UI) : CLI(Command Line Interface)와 GUI 중 어떤 인터페이스를 제공할지 결정. 멀티태스킹 방식 : 선점형(Premptive) 또는 비선점형(Non-preemptive) 멀티태스킹 구현 여부. 3. 개발 환경 설정 개발 언어 선택 : 운영체제 개발에는 일반적으로 C와 C++가 사용됩니다. 부트로더는 종종 어셈블리어로 작성됩니다. 툴체인 준비 : 컴파일러(GCC, Clang 등) 디버거(QEMU, GDB 등) 에뮬레이터(QEMU) 또는 실제 하드웨어. 버전 관리 시스템 : Git 등으로 소스 코드를 관리. 4. 부트로더 개발 부트로더는 컴퓨터가 켜질 때 하드웨어를 초기화하고 운영체제를 메모리에 로드합니다. 대표적인 부트로더 예: GRUB, LILO. 자신만의 부트로더를 제작하거나 기존 부트로더를 커스터마이즈할 수 있습니다. 5. 커널 개발 프로세스 관리 : 프로세스 생성, 스케줄링, 종료 구현. 메모리 관리 : 물리 메모리와 가상 메모리 관리. 페이징 또는 세그멘테이션 지원. 입출력 관...
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