Tuesday, September 26, 2023

Spring Boot service that reads from the AWS Glue Data Catalog

 To create a Spring Boot service that reads from the AWS Glue Data Catalog, you need to set up a few components:

  1. Spring Boot Application: Set up a Spring Boot application.
  2. AWS SDK for Glue: Add the necessary dependencies for AWS Glue.
  3. AWS Configuration: Configure the AWS credentials and region.
  4. Service Class: Create a service class to interact with the Glue Data Catalog.

Here’s a step-by-step guide:

Step 1: Set Up Your Spring Boot Application

Start by creating a new Spring Boot project. You can use Spring Initializr (https://start.spring.io/) to generate a basic Spring Boot project with the necessary dependencies.

Step 2: Add Dependencies

Add the necessary dependencies to your pom.xml file:


<dependencies> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter</artifactId> </dependency> <dependency> <groupId>org.springframework.boot</groupId> <artifactId>spring-boot-starter-web</artifactId> </dependency> <dependency> <groupId>software.amazon.awssdk</groupId> <artifactId>glue</artifactId> </dependency> <dependency> <groupId>software.amazon.awssdk</groupId> <artifactId>auth</artifactId> </dependency> </dependencies>

Step 3: Configure AWS Credentials and Region

Create an application.yml or application.properties file to configure your AWS credentials and region.

yaml
aws: region: us-west-2 accessKeyId: YOUR_ACCESS_KEY_ID secretAccessKey: YOUR_SECRET_ACCESS_KEY

Step 4: Create AWS Configuration Class

Create a configuration class to set up the AWS Glue client.

java

import org.springframework.beans.factory.annotation.Value; import org.springframework.context.annotation.Bean; import org.springframework.context.annotation.Configuration; import software.amazon.awssdk.auth.credentials.AwsBasicCredentials; import software.amazon.awssdk.auth.credentials.StaticCredentialsProvider; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.glue.GlueClient; @Configuration public class AwsConfig { @Value("${aws.accessKeyId}") private String accessKeyId; @Value("${aws.secretAccessKey}") private String secretAccessKey; @Value("${aws.region}") private String region; @Bean public GlueClient glueClient() { return GlueClient.builder() .region(Region.of(region)) .credentialsProvider(StaticCredentialsProvider.create(AwsBasicCredentials.create(accessKeyId, secretAccessKey))) .build(); } }

Step 5: Create a Service Class

Create a service class to interact with the Glue Data Catalog.

java
import org.springframework.beans.factory.annotation.Autowired; import org.springframework.stereotype.Service; import software.amazon.awssdk.services.glue.GlueClient; import software.amazon.awssdk.services.glue.model.GetDatabasesRequest; import software.amazon.awssdk.services.glue.model.GetDatabasesResponse; @Service public class GlueService { private final GlueClient glueClient; @Autowired public GlueService(GlueClient glueClient) { this.glueClient = glueClient; } public GetDatabasesResponse getDatabases() { GetDatabasesRequest request = GetDatabasesRequest.builder().build(); return glueClient.getDatabases(request); } }

Step 6: Create a Controller Class

Create a controller class to expose an endpoint for the service.


import org.springframework.beans.factory.annotation.Autowired; import org.springframework.web.bind.annotation.GetMapping; import org.springframework.web.bind.annotation.RequestMapping; import org.springframework.web.bind.annotation.RestController; import software.amazon.awssdk.services.glue.model.GetDatabasesResponse; @RestController @RequestMapping("/glue") public class GlueController { private final GlueService glueService; @Autowired public GlueController(GlueService glueService) { this.glueService = glueService; } @GetMapping("/databases") public GetDatabasesResponse getDatabases() { return glueService.getDatabases(); } }


PLEASE NOTE: if you do not have access to AWS accessKeyId and secretAccessKey,. you can get an
instance of glueClient using following code snippet

GlueClient glueClient = GlueClient.builder() .region(region) .build();


To access a cross account DB, please use the folloiwng Example
SELECT statement:

SELECT * FROM "glue:arn:aws:glue:us-east-1:999999999999:catalog".tpch1000.customer

Step 7: Run the Application

Run your Spring Boot application. You can access the Glue Data Catalog databases by navigating to http://localhost:8080/glue/databases.

This setup provides a basic Spring Boot service that reads from the AWS Glue Data Catalog. You can extend this to handle more Glue operations as needed

Friday, September 22, 2023

Manage Identities in Amazon Cognito

Amazon Cognito is a service provided by AWS (Amazon Web Services) for managing user identities and authentication in your applications. To create identities in Amazon Cognito using Java, you can use the AWS SDK for Java. Below is an example of Java code to create identities in Amazon Cognito:


Before you start, make sure you have set up an Amazon Cognito User Pool and Identity Pool in your AWS account.


1. Add the AWS SDK for Java to your project. You can use Maven or Gradle to manage dependencies. Here's an example using Maven:



<dependency>

    <groupId>com.amazonaws</groupId>

    <artifactId>aws-java-sdk-cognitoidentity</artifactId>

    <version>1.11.1069</version> <!-- Replace with the latest version -->

</dependency>

 


2. Write Java code to create identities in Amazon Cognito:


```java

import com.amazonaws.auth.AWSStaticCredentialsProvider;

import com.amazonaws.auth.BasicAWSCredentials;

import com.amazonaws.services.cognitoidentity.AmazonCognitoIdentity;

import com.amazonaws.services.cognitoidentity.AmazonCognitoIdentityClient;

import com.amazonaws.services.cognitoidentity.model.GetIdRequest;

import com.amazonaws.services.cognitoidentity.model.GetIdResult;

import com.amazonaws.services.cognitoidentity.model.GetOpenIdTokenRequest;

import com.amazonaws.services.cognitoidentity.model.GetOpenIdTokenResult;

import com.amazonaws.services.cognitoidentity.model.IdentityPoolConfigurationException;


public class ManageCognitoIdentity {

    public static void main(String[] args) {

        // Replace these with your own values

        String identityPoolId = "your-identity-pool-id";

        String accessKeyId = "your-access-key-id";

        String secretAccessKey = "your-secret-access-key";

        

        // Initialize the AWS credentials and Cognito Identity client

        BasicAWSCredentials awsCredentials = new BasicAWSCredentials(accessKeyId, secretAccessKey);

        AmazonCognitoIdentity identityClient = AmazonCognitoIdentityClient.builder()

                .withRegion("your-region") // Replace with your AWS region

                .withCredentials(new AWSStaticCredentialsProvider(awsCredentials))

                .build();

        

        // Get an identity ID

        GetIdRequest getIdRequest = new GetIdRequest().withIdentityPoolId(identityPoolId);

        try {

            GetIdResult idResult = identityClient.getId(getIdRequest);

            String identityId = idResult.getIdentityId();

            System.out.println("Identity ID: " + identityId);

            

            // Get an OpenID token for the identity

            GetOpenIdTokenRequest getTokenRequest = new GetOpenIdTokenRequest().withIdentityId(identityId);

            GetOpenIdTokenResult tokenResult = identityClient.getOpenIdToken(getTokenRequest);

            String openIdToken = tokenResult.getToken();

            System.out.println("OpenID Token: " + openIdToken);

        } catch (IdentityPoolConfigurationException e) {

            System.err.println("Error: Identity pool configuration is invalid.");

            e.printStackTrace();

        }

    }

}

```


Make sure to replace `"your-identity-pool-id"`, `"your-access-key-id"`, `"your-secret-access-key"`, and `"your-region"` with your actual Amazon Cognito Identity Pool ID, AWS access key, secret access key, and the AWS region you're using.


This code first gets an identity ID for a user from the Cognito Identity Pool and then retrieves an OpenID token associated with that identity.

Monday, July 24, 2023

AWS Database Migration Service (DMS) tasks

To automate AWS Database Migration Service (DMS) tasks, you can use the AWS Command Line Interface (CLI), SDKs (such as Boto3 for Python), or AWS CloudFormation to create scripts or templates for automated deployment and management.


Here are steps to automate AWS DMS tasks using the CLI:


1. Install and Configure AWS CLI: 

   Ensure you have the AWS CLI installed and configured with the necessary credentials and permissions.


2. Create a Replication Instance:

   Use the AWS CLI to create a replication instance:

  

   aws dms create-replication-instance --replication-instance-identifier my-replication-instance --replication-instance-class dms.t2.micro --allocated-storage 20 --region us-west-2

 


3.  Create a Replication Task: 

   Create a task to specify what data to migrate:

   

   aws dms create-replication-task --replication-task-identifier my-replication-task --source-endpoint-arn source-endpoint-arn --target-endpoint-arn target-endpoint-arn --migration-type full-load

   


4.  Start/Stop Replication Task: 

   You can start or stop a replication task using the AWS CLI:

 

   aws dms start-replication-task --replication-task-arn replication-task-arn

   aws dms stop-replication-task --replication-task-arn replication-task-arn

 


5.  Monitor Replication Task: 

   To monitor the task's progress or status:

  

   aws dms describe-replication-tasks --filters Name="replication-task-id",Values="my-replication-task"

  


6.  Modify Replication Task: 

   To modify an existing task:

  

   aws dms modify-replication-task --replication-task-arn replication-task-arn --replication-task-settings file://task-settings.json

  


7.  Delete Resources: 

   After migration, delete resources to avoid unnecessary costs:

    

   aws dms delete-replication-task --replication-task-arn replication-task-arn

   aws dms delete-replication-instance --replication-instance-arn replication-instance-arn

    


Remember to substitute placeholders like `my-replication-instance`, `my-replication-task`, `source-endpoint-arn`, `target-endpoint-arn`, `replication-task-arn`, etc., with your specific resource identifiers.


You can also combine these commands into scripts (e.g., Bash, Python) for more complex automation or incorporate them into infrastructure-as-code (IaC) tools like AWS CloudFormation or AWS CDK for better management and version control.

Wednesday, June 28, 2023

Using Chat GPT APIs With Microservices

 The ChatGPT API, developed by OpenAI, is a robust tool for language processing. Built upon the GPT model, it has been trained extensively on vast amounts of text data to produce text that closely resembles human language. By integrating the API into their applications, developers can leverage the power of GPT to create advanced language-based functionalities such as natural language understanding, text generation, and chatbot capabilities.

The ChatGPT API excels in comprehending and responding to natural language input, making it an excellent choice for chatbot applications. It can understand user queries and provide responses that feel natural and human-like. Additionally, the API has the ability to generate text, enabling the automation of responses, summaries, and even entire articles. This feature proves particularly valuable in content creation and summarization scenarios.

Scalability is another key advantage of the ChatGPT API. It can effortlessly handle large volumes of data and seamlessly integrate with other systems and platforms. Furthermore, developers have the flexibility to fine-tune the model according to their specific requirements, leading to improved accuracy and relevance of the generated text.

The ChatGPT API is designed to be user-friendly, with comprehensive documentation and ease of use. It caters to developers of all skill levels and offers a range of software development kits (SDKs) and libraries to simplify integration into applications.


To utilize the ChatGPT API, you will need to follow a few steps:

  • Obtain an API key: To begin using the ChatGPT API, sign up for an API key on the OpenAI website. This key will grant you access to the API's functionalities.
  • Choose a programming language: The ChatGPT API provides SDKs and libraries in various programming languages, including Python, Java, and JavaScript. Select the one that you are most comfortable working with.
  • Install the SDK: After selecting your preferred programming language, install the corresponding SDK or library. You can typically accomplish this using a package manager like pip or npm.
  • Create an API instance: Once you have the SDK installed, create a new instance of the API by providing your API key and any additional required configuration options.
  • Make API requests: With an instance of the API set up, you can start making requests to it. For instance, you can use the "generate" method to generate text based on a given prompt.
  • Process the API response: After receiving a response from the API, process it as necessary. For example, you might extract the generated text from the response and display it within your application.


import org.springframework.http.HttpEntity; import org.springframework.http.HttpHeaders; import org.springframework.http.HttpMethod; import org.springframework.http.MediaType; import org.springframework.http.ResponseEntity; import org.springframework.stereotype.Service; import org.springframework.web.client.RestTemplate; @Service public class ChatGptService { private final String API_URL = "https://api.openai.com/v1/engines/davinci-codex/completions"; private final String API_KEY = "YOUR_API_KEY"; public String getChatResponse(String prompt) { RestTemplate restTemplate = new RestTemplate(); HttpHeaders headers = new HttpHeaders(); headers.setContentType(MediaType.APPLICATION_JSON); headers.setBearerAuth(API_KEY); String requestBody = "{\"prompt\": \"" + prompt + "\", \"max_tokens\": 50}"; HttpEntity<String> request = new HttpEntity<>(requestBody, headers); ResponseEntity<ChatGptResponse> response = restTemplate.exchange( API_URL, HttpMethod.POST, request, ChatGptResponse.class ); if (response.getStatusCode().is2xxSuccessful()) { ChatGptResponse responseBody = response.getBody(); if (responseBody != null) { return responseBody.choices.get(0).text; } } return "Failed to get a response from the Chat GPT API."; } }


In the above code, replace "YOUR_API_KEY" with your actual API key obtained from OpenAI. The getChatResponse method takes a prompt as input and sends a POST request to the Chat GPT API to get a response. The response is then extracted and returned as a string.

Note that you need to have the necessary dependencies added to your Spring Boot project, including spring-boot-starter-web and spring-web. Additionally, make sure your project is configured with the necessary versions of Java and Spring Boot.

You can then inject the ChatGptService into your controllers or other Spring components to use the getChatResponse method and retrieve responses from the Chat GPT API.


Sunday, June 11, 2023

Title: Uploading CCB and C2M Data files Files from Oracle Object Store to Oracle Utilities Customer Cloud Service (CCS) using Oracle Integration Cloud (OIC)

 Title: Uploading  CCB/C2M Data files from Oracle Object Store to Oracle Utilities Customer Cloud Service (CCS) using Oracle Integration Cloud (OIC)


Introduction:

As the digital landscape continues to evolve, businesses are adopting cloud-based solutions to streamline their operations. In this blog entry, we will explore how to upload files, such as images or documents, from Oracle Object Store to Oracle Utilities Customer Cloud Service (CCS) using Oracle Integration Cloud (OIC). This integration enables you to seamlessly transfer files from Object Store to CCS, ensuring that your blog entries are enriched with relevant and engaging multimedia content.


Prerequisites:

Before you proceed with the integration, ensure you have the following prerequisites in place:


1. An active Oracle Object Store instance with the files you want to upload.

2. Access to Oracle Utilities Customer Cloud Service (CCS) with the necessary permissions to manage files.

3. Access to Oracle Integration Cloud (OIC) with the required permissions to create integrations.


Step 1: Create an Integration in Oracle Integration Cloud (OIC):

1. Log in to your Oracle Integration Cloud account.

2. Create a new integration by selecting "Create Integration" from the OIC dashboard.

3. Provide a name and description for your integration and select the appropriate package.

4. Choose the integration style that best fits your requirements and click "Create."


Step 2: Configure the Source Connection (Oracle Object Store):

1. Within the integration canvas, click on the plus (+) icon to add a connection.

2. Select "Oracle Storage" from the list of available connections.

3. Provide the necessary details to configure the connection, including the Object Store details, authentication method, and credentials.

4. Test the connection to ensure it is set up correctly.


Step 3: Configure the Target Connection (Oracle Utilities Customer Cloud Service - CCS):

1. Similar to Step 2, add a new connection by clicking on the plus (+) icon.

2. Select "Oracle Utilities" from the connection list.

3. Provide the required details to establish the connection, including the CCS instance URL, authentication method, and credentials.

4. Test the connection to verify its functionality.


Step 4: Design the Integration Flow:

1. On the integration canvas, drag and drop the appropriate start activity, depending on your integration style (e.g., "Scheduled Orchestration," "Event-Driven," etc.).

2. Add a "File Read" activity from the component palette and configure it to read the files from the Oracle Object Store.

3. Connect the "File Read" activity to a "File Write" activity representing the target connection to CCS.

4. Configure the "File Write" activity to upload the files to the desired location in CCS.

5. Optionally, you can add additional activities or transformations to modify the file or metadata during the integration flow.

6. Save the integration.


Step 5: Configure the Trigger (if using Event-Driven style):

1. If you chose the "Event-Driven" style, configure the trigger by selecting the appropriate event (e.g., file upload event) that will initiate the integration.

2. Set up the event parameters, such as the Object Store bucket and event filters.

3. Save the trigger configuration.


Step 6: Activate and Monitor the Integration:

1. Activate the integration by clicking the "Activate" button in the top-right corner of the OIC interface.

2. Monitor the integration runs and logs to ensure the successful transfer of files from Object Store to CCS.

3. Test the integration by manually triggering it or performing the event that initiates the integration.


Conclusion:

By integrating Oracle Object Store with Oracle Utilities Customer Cloud Service (CCS) using Oracle Integration Cloud (OIC), you can effortlessly upload blog entry files, enriching your content with multimedia

Monday, June 5, 2023

Creating a partition index in AWS Glue

Creating a partition index in AWS Glue can help speed up queries that rely on specific partition columns. This blog thread illustrates creating a partition index on an AWS Glue table.

Let's assume you have a table called sales_data in AWS Glue, which is partitioned by year, month, and day. If you frequently query the data by year and month, you can create a partition index on these columns to improve performance.

Example: Creating a Partition Index

  1. Set up the Table and Partitions (if not already set): Ensure your table is set up in AWS Glue Data Catalog and is partitioned by year, month, and day.

    python
    import boto3 glue = boto3.client('glue') response = glue.create_table( DatabaseName='my_database', TableInput={ 'Name': 'sales_data', 'PartitionKeys': [ {'Name': 'year', 'Type': 'int'}, {'Name': 'month', 'Type': 'int'}, {'Name': 'day', 'Type': 'int'} ], 'StorageDescriptor': { 'Columns': [ {'Name': 'product_id', 'Type': 'string'}, {'Name': 'quantity', 'Type': 'int'}, {'Name': 'price', 'Type': 'double'} ], 'Location': 's3://my-bucket/sales_data/' } } )
  2. Create a Partition Index: To create a partition index for the year and month columns, use the following example code:

    python
    response = glue.create_partition_index( DatabaseName='my_database', TableName='sales_data', PartitionIndex={ 'Keys': ['year', 'month'], # Specify the columns to index 'IndexName': 'year_month_index' # Name the index } ) print("Partition Index Created:", response)
  3. Verifying the Partition Index: To check that the partition index was created successfully, you can use the get_partition_indexes method:

    python
    response = glue.get_partition_indexes( DatabaseName='my_database', TableName='sales_data' ) print("Partition Indexes:", response['PartitionIndexList'])

Explanation of the Code

  • DatabaseName and TableName specify the database and table in Glue Data Catalog.
  • PartitionIndex includes:
    • Keys: A list of partition columns to index, in this case, ['year', 'month'].
    • IndexName: A unique name for the index, like year_month_index.

Creating this index will allow AWS Glue and any service querying the table, such as Athena, to quickly locate partitions based on year and month, improving performance on queries filtering by these columns.

Sunday, June 4, 2023

Null Pointer at com.sforce.ws.codegen.Compiler.(Compiler.java:48)

When compiling enterprise.wsdl with  force-wsc-58.0.0-uber.jar I was getting the following exception:


$ java -classpath force-wsc-58.0.0-uber.jar com.sforce.ws.tools.wsdlc enterprise-58-0.wsdl enterprise-58-0.0.jar

[WSC][wsdlc.main:72]Generating Java files from schema ...

[WSC][wsdlc.main:72]Generated 2724 java files.

Exception in thread "main" java.lang.NullPointerException

        at com.sforce.ws.codegen.Compiler.<init>(Compiler.java:48)

        at com.sforce.ws.codegen.Generator.compileTypes(Generator.java:137)

        at com.sforce.ws.tools.wsdlc.run(wsdlc.java:129)

        at com.sforce.ws.tools.wsdlc.run(wsdlc.java:163)

        at com.sforce.ws.tools.wsdlc.main(wsdlc.java:72)


To resolve this issue, I pointed to Oracle JDK and that resolved the issue:

$ /c/jdk1-8-0_202/bin/java -classpath force-wsc-58.0.0-uber.jar com.sforce.ws.tools.wsdlc enterprise-58-0.wsdl enterprise-58-0.0.jar
[WSC][wsdlc.main:72]Generating Java files from schema ...
[WSC][wsdlc.main:72]Generated 2724 java files.
[WSC][wsdlc.main:72]Compiled 2728 java files.
[WSC][wsdlc.main:72]Generating jar file ... enterprise-58-0.0.jar
[WSC][wsdlc.main:72]Generated jar file enterprise-58-0.0.jar

How IdP Groups Are Tied to Databricks Groups (Unity Catalog)

  🔗 How IdP Groups Are Tied to Databricks Groups (Unity Catalog) 🔑 Key Principle (Read This First) Databricks does NOT “map” IdP groups...