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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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Sparse encoder

A Sparse Encoder refers to a variant of neural network architectures where sparsity is introduced in the encoding process. This can mean either: Sparse Input Representations : The input features to the encoder are sparse (many values are zero). Sparse Output Representations : The encoder is designed to produce sparse outputs where most of the encoded feature values are zero. Sparse encoders are often used to improve model interpretability, efficiency, and generalization. They can be applied in various contexts, including traditional neural networks, autoencoders, and even transformer-based models. Key Characteristics of Sparse Encoders Sparsity in Representations : The model learns a feature representation where only a subset of neurons is active for a given input. This mimics how biological neurons operate, promoting interpretability and reducing noise in representations. Reduced Computational Cost : Sparse operations often result in lower computational overhead since...
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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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Nginx Openssl 설정

인증서 만들기 #openssl req -new -newkey rsa:2048 -nodes -keyout open_ssl.key -out open_ssl.csr Generating a 2048 bit RSA private key ... ... Please enter the following 'extra' attributes to be sent with your certificate request A challenge password []: 테스트를 위한 SSL 인증서 생성 #openssl x509 -req -days 365 -in open_ssl.csr -signkey open_ssl.key -out open_ssl.crt #ls -al -rw-r--r-- 1 root root 1306 Jun 18 11:27 open_ssl.crt -rw-r--r-- 1 root root 1110 Jun 18 11:21 open_ssl.csr -rw-r--r-- 1 root root 1704 Jun 18 11:21 open_ssl.key Nginx 의 SSL 모듈 탑재 확인 #/usr/local/nginx/sbin/nginx -V nginx version: nginx/1.5.8 built by gcc 4.4.6 20120305 (Red Hat 4.4.6-4) (GCC) TLS SNI support enabled configure arguments: --prefix=/daum/program/nginx --with-http_ssl_module "--with-http_ssl_module" 부분 없다면 아래 방식으로 Nginx 재설치 # ./configure --prefix=/usr/local/nginx --with-http_ssl_module ... # make && make install Nginx 서버 config 설정 # HTTPS server # serve...
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To monitor logs for a Kubernetes CronJob

To monitor logs for a Kubernetes CronJob , you can follow these steps: 1. List the CronJob and Its Jobs First, get the list of CronJobs to identify the specific one you're interested in: kubectl get cronjobs After identifying the CronJob, list the Jobs it created using the following command (replace my-cronjob with the name of your CronJob): kubectl get jobs --selector=job-name=my-cronjob 2. Get the Pod Created by the Job CronJobs create Kubernetes Jobs, and Jobs spawn Pods to execute the tasks. To view the Pods created by a specific Job: kubectl get pods --selector=job-name=my-cronjob-<timestamp> Replace my-cronjob-<timestamp> with the name of the Job you identified earlier. If you're unsure about the exact name, you can list all Pods and filter the results: kubectl get pods 3. View the Logs of the Pod Once you have the name of the Pod, you can check its logs. Use the following command (replace my-pod with the actual ...
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Sort the distinct values by their count in descending order using the DataFrame API

To sort the distinct values by their count in descending order using the DataFrame API in Spark, you can use the orderBy() function with the ascending=False parameter. Here’s how you can modify the DataFrame API example to include sorting in descending order: Example: Get Distinct Values and Their Counts with Descending Order Sorting # Read the table into a DataFrame df = spark. read . table ( "table_name" ) # Group by the field and count , then order by count in descending order distinct_counts = df.groupBy( "field_name" ). count ().orderBy( "count" , ascending=False) # Show the results distinct_counts.show() Explanation: groupBy("field_name") : Groups the data by the distinct values in the field_name column. count() : Counts the number of occurrences for each distinct value. orderBy("count", ascending=False) : Sorts the result by the count in descending order . Optional: Collecting the Sorted Results If you...
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[Ubuntu] *.deb 파일 설치 방법

확장자가 .deb 인 파일은 원래 Debian 리눅스에서의 설치파일입니다. Ubuntu 는 원래 Debian 리눅스에서 파생되었기 때문에, 많은 부분에서 서로 닮아 있습니다. 따라서 별다른 변환 절차 없이 아래와 같이 바로 설치가 가능합니다. [user@hostname]# sudo dpkg -i *.deb *.rpm 파일을 *.deb 파일로 변환 [user@hostname]$ sudo apt-get install alien [user@hostname]$ sudo alien -c *.rpm
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Node.js memory limit, 노드 메모리 제한하기

To set the memory size when running a Node.js application with npm, you can adjust the memory limit by setting the --max-old-space-size flag, which increases the V8 (JavaScript engine) heap size. This can be done in a few ways: 1. Directly in the Command Line: You can run your npm script with the --max-old-space-size flag: node --max-old-space-size = 4096 your-script.js This sets the memory limit to 4GB (4096 MB). You can adjust the value depending on the desired memory limit. 2. In Your package.json Scripts: You can modify your package.json file to include this flag within your npm scripts. { "scripts" : { "start" : "node --max-old-space-size=4096 your-script.js" } } Then, you can run your script using npm: npm run start 3. Using Environment Variables: You can also set an environment variable to increase the memory limit. On Linux or macOS: NODE_OPTIONS= "--max-old-space-size=4096" npm run start On Windows (Comm...
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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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Elasticsearch Ingest API

Elasticsearch Ingest is a feature that allows you to preprocess documents before indexing them. It consists of a pipeline of processors that can manipulate the contents of the documents. One way to test the effectiveness of an Ingest pipeline is to simulate its execution on a sample document. This can be done using the Elasticsearch Ingest API's "simulate" endpoint. To use the "simulate" endpoint, you need to provide a JSON object that represents the document you want to test, and a JSON object that represents the pipeline you want to simulate. Here is an example of how to use the "simulate" endpoint: curl -H 'Content - Type : application/json' -XGET 'localhost : 9200 /_ingest/pipeline/_simulate' -d '{ "pipeline" : { "description" : "Sample pipeline" , "processors" : [ { "set" : { "field" : "foo" , "value" :...
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