Error Geek

CORS (Cross-Origin Resource Sharing) errors occur when a web application running in a browser requests a resource from a different domain or port than the one it originated from. Spring Boot provides built-in support for handling CORS errors. Here are the steps you can follow to solve a CORS error in Spring Boot: Add the following dependencies to your project's build file: implementation ' org. springframework . boot :spring-boot-starter-web ' In your Spring Boot application, create a class that extends the WebMvcConfigurer interface and add the following code to it: @Configuration public class WebConfig implements WebMvcConfigurer { @Override public void addCorsMappings(CorsRegistry registry) { registry. addMapping ( "/**" ). allowedOrigins ( "*" ) . allowedMethods ( "GET" , "POST" , "PUT" , "DELETE" , "HEAD" ) . allowedHeaders ( "*" ). allowCredentials ...

Apache Hudi is an open-source data management framework that enables high-performance and scalable data ingestion, storage, and processing. Hudi stands for “Hadoop Upserts Deletes and Incrementals” and is designed to handle large-scale data sets in distributed computing environments such as Apache Hadoop, Apache Spark, and Apache Flink. One of the main features of Apache Hudi is its support for upserts (updates and inserts), deletes, and incremental data processing. This makes it ideal for use cases where data is constantly changing and requires efficient updates and deletes. Hudi provides a mechanism to efficiently store and process the incremental changes made to the data, making it ideal for use cases such as real-time analytics, stream processing, and machine learning. Apache HUDI provides a robust and scalable data ingestion framework that can handle a variety of use cases , that make it a valuable data management tool. Here are some examples of use cases where Apache Hudi can be ...

 To read a file from AWS S3 using Python, you will need to use the AWS SDK for Python (Boto3). Here's an example code snippet to read a file from S3: Preview: import boto3 # Create an S3 client s3 = boto3.client( 's3' ) # Define the bucket and object key bucket_name = 'my-bucket' object_key = 'path/to/my/file.txt' # Read the file from S3 response = s3.get_object(Bucket=bucket_name, Key=object_key) file_content = response[ 'Body' ].read().decode( 'utf-8' ) # Print the file content print (file_content) In the code above, you first create an S3 client using the boto3.client method. Then you define the bucket name and object key for the file you want to read. Finally, you use the s3.get_object method to retrieve the file content from S3 and decode it to a string using UTF-8 encoding. Note that you will need to have the appropriate AWS credentials configured to access the S3 bucket. You can either set these as environment...