updated logic

Author: scmacdon

javav2/example_code/entityresolution/src/main/java/com/example/entity/scenario/EntityResScenario.java

@@ -28,7 +28,6 @@ public class EntityResScenario {
     private static String workflowName = "workflow-"+ UUID.randomUUID();
 
     public static void main(String[] args) throws InterruptedException {
-
         String jsonSchemaMappingName = "jsonschema-" + UUID.randomUUID();
         String jsonSchemaMappingArn = null;
         String csvSchemaMappingName = "csv-" + UUID.randomUUID();
@@ -126,13 +125,14 @@ Amazon Web Services (AWS) that helps organizations extract, link, and
             and uses machine learning to link related entities, enabling a 
             consolidated, accurate view for improved data quality and decision-making.
                         
-            In this example, the schema mapping lines up with the fields in the JSON objects. That is, 
+            In this example, the schema mapping lines up with the fields in the JSON ans CSV objects. That is, 
             it contains these fields: id, name, and email. 
             """);
         waitForInputToContinue(scanner);
         try {
             CreateSchemaMappingResponse response = actions.createSchemaMappingAsync(jsonSchemaMappingName).join();
             jsonSchemaMappingArn = response.schemaArn();
+            logger.info("The JSON schema mapping ARN is "+jsonSchemaMappingArn);
         } catch (CompletionException ce) {
             Throwable cause = ce.getCause();
             logger.info("Failed to create JSON schema mapping: " + (cause != null ? cause.getMessage() : ce.getMessage()));
@@ -141,12 +141,11 @@ Amazon Web Services (AWS) that helps organizations extract, link, and
         try {
             CreateSchemaMappingResponse response = actions.createSchemaMappingAsync(csvSchemaMappingName).join();
             csvSchemaMappingArn = response.schemaArn();
+            logger.info("The CSV schema mapping ARN is "+csvSchemaMappingArn);
         } catch (CompletionException ce) {
             Throwable cause = ce.getCause();
             logger.info("Failed to create CSV schema mapping: " + (cause != null ? cause.getMessage() : ce.getMessage()));
         }
-
-
         waitForInputToContinue(scanner);
         logger.info(DASHES);
 
@@ -231,19 +230,19 @@ Amazon Web Services (AWS) that helps organizations extract, link, and
         logger.info(DASHES);
 
         logger.info(DASHES);
-        logger.info("8. Delete the AWS Entity Resolution Workflow.");
+        logger.info("8. View the results of the AWS Entity Resolution Workflow.");
         logger.info("""
-            You cannot delete a workflow that is in a running state.  
-            Would you like to wait for the workflow that we started in step 3 to complete.
+            You cannot view the result of the workflow that is in a running state.  
+            In order to view the results, you need to wait for the workflow that we started in step 3 to complete.
             
-            If you choose not to wait, you will need to delete the workflow manually 
-            in the AWS Management Console.
+            If you choose not to wait, you cannot view the results or delete the workflow. You would have to 
+            perform both tasks manually in the AWS Management Console.
            
             This can take up to 30 mins (y/n).
             """);
-        String delAns = scanner.nextLine().trim();
-        if (delAns.equalsIgnoreCase("y")) {
-            logger.info("You selected to delete Entity Resolution Workflow.");
+        String viewAns = scanner.nextLine().trim();
+        if (viewAns.equalsIgnoreCase("y")) {
+            logger.info("You selected to view the Entity Resolution Workflow results.");
             waitForInputToContinue(scanner);
             countdownWithWorkflowCheck(actions, 1800, jobId, workflowName);
             JobMetrics metrics = actions.getJobInfo(workflowName, jobId).join();
@@ -272,30 +271,38 @@ Amazon Web Services (AWS) that helps organizations extract, link, and
                     the confidence level is lower for the differing email addresses.
                     
                     """);
-            try {
-                actions.deleteMatchingWorkflowAsync(workflowName).join();
-                logger.info("Workflow deleted successfully!");
-            } catch (CompletionException ce) {
-                Throwable cause = ce.getCause();
-                logger.info("Failed to delete workflow: " + (cause != null ? cause.getMessage() : ce.getMessage()));
-            }
-        }
-        waitForInputToContinue(scanner);
-        logger.info(DASHES);
 
-        logger.info(DASHES);
-        logger.info("""
+            logger.info("Do you want to delete the resources, including workflow?");
+            String delAns = scanner.nextLine().trim();
+            if (delAns.equalsIgnoreCase("y")) {
+                try {
+                    actions.deleteMatchingWorkflowAsync(workflowName).join();
+                    logger.info("Workflow deleted successfully!");
+                } catch (CompletionException ce) {
+                    Throwable cause = ce.getCause();
+                    logger.info("Failed to delete workflow: " + (cause != null ? cause.getMessage() : ce.getMessage()));
+                }
+                waitForInputToContinue(scanner);
+                logger.info(DASHES);
+                logger.info("""
                 Now we delete the CloudFormation stack, which deletes 
                 the resources that were created at the beginning
                 """);
+                waitForInputToContinue(scanner);
+                logger.info(DASHES);
+                try {
+                    deleteResources();
+                } catch (CompletionException ce) {
+                    Throwable cause = ce.getCause();
+                    logger.error("Failed to delete Glue Table: {}", cause != null ? cause.getMessage() : ce.getMessage());
+                }
+
+            } else {
+                logger.info("You can delete the Workflow later in the AWS Management console.");
+            }
+        }
         waitForInputToContinue(scanner);
         logger.info(DASHES);
-        try {
-            deleteResources();
-        } catch (CompletionException ce) {
-            Throwable cause = ce.getCause();
-            logger.error("Failed to delete Glue Table: {}", cause != null ? cause.getMessage() : ce.getMessage());
-        }
 
         logger.info(DASHES);
         logger.info("This concludes the AWS Entity Resolution scenario.");
@@ -336,13 +343,13 @@ public static void countdownWithWorkflowCheck(EntityResActions actions, int tota
             // Check workflow status every 60 seconds
             if (secondsElapsed % 60 == 0 || remainingTime <= 0) {
                 if (actions.checkWorkflowStatusCompleteAsync(jobId, workflowName).join()) {
-                    logger.info(""); // Move to the next line after countdown
+                    logger.info(""); // Move to the next line after countdown.
                     logger.info("Countdown complete: Workflow is in SUCCEEDED state!");
                     break;
                 }
             }
 
-            // If countdown reaches zero, reset it for continuous countdown
+            // If countdown reaches zero, reset it for continuous countdown.
             if (remainingTime <= 0) {
                 secondsElapsed = 0;
             }
@@ -352,7 +359,6 @@ private static void deleteResources(){
         CloudFormationHelper.emptyS3Bucket(glueBucketName);
         CloudFormationHelper.destroyCloudFormationStack(STACK_NAME);
         logger.info("Resources deleted successfully!");
-
     }
 }
 // snippet-end:[entityres.java2_scenario.main]

javav2/example_code/entityresolution/src/test/java/EntityResTests.java

@@ -75,11 +75,16 @@ public static void setUp() {
               }
             ]
             """;
-        if (!actions.doesObjectExist(dataS3bucket)) {
-            actions.uploadInputData(dataS3bucket, json);
-        } else {
-            System.out.println("The JSON exists in " + dataS3bucket);
-        }
+
+        String csv = """
+                id,name,email,phone
+                1,Alice B. Johnson,[email protected],746-876-9846
+                2,Bob Smith Jr.,[email protected],987-654-3210
+                3,Charlie Black,[email protected],345-567-1234
+                7,Jane E. Doe,[email protected],111-222-3333
+                """;
+
+        actions.uploadInputData(dataS3bucket, json, csv);
     }
 
     @Test
@@ -99,7 +104,8 @@ public void testCreateMapping() {
     @Order(2)
     public void testCreateMappingWorkflow() {
         assertDoesNotThrow(() -> {
-            workflowArn = actions.createMatchingWorkflowAsync(roleARN, workflowName, outputBucket, inputGlueTableArn, schemaName).join();
+            //workflowArn = actions.actions.createMatchingWorkflowAsync(roleARN, workflowName, glueBucketName, jsonGlueTableArn
+            //    , jsonSchemaMappingName, csvGlueTableArn, csvSchemaMappingName).join();
             assertNotNull(workflowArn);
         });
         logger.info("Test 2 passed");

scenarios/basics/entity_resolution/README.md

@@ -1,27 +1,41 @@
+# AWS Entity Resolution Java Program
+
 ## Overview
-This AWS Entity Resolution basic scenario demonstrates how to interact with the AWS Entity Resolution service using an AWS SDK. The scenario covers various operations such as creating a schema mapping, creating a matching workflow, starting a matching job, and so on. 
+This AWS Entity Resolution basic scenario demonstrates how to interact with the AWS Entity Resolution service using an AWS SDK. This Java application demonstrates how to use AWS Entity Resolution to integrate and deduplicate data from multiple sources using machine learning-based matching. The program walks through setting up AWS resources, uploading structured data, defining schema mappings, creating a matching workflow, and running a matching job.
 
-## Key Operations
 
-1. **Create an AWS Entity Resolution schema mapping**:
-   - This step creates an AWS Entity Resolution schema mapping by invoking the `createSchemaMapping` method.
+**Note:** See the [specification document](SPECIFICATION.md) for a complete list of operations. 
 
-2. **Create an AWS Entity Resolution workflow**:
-   - This step creates an AWS Entity Resolution matching workflow by invoking the `createMatchingWorkflow` method.
+## Features
 
-3. **Start a matching aorkflow**:
-   - This step starts the AWS Entity Resolution matching workflow by invoking the `startMatchingJob` method.
+1. Uses AWS CloudFormation to create necessary resources:
 
-4. **Get workflow job details**:
-   - This step gets workflow job details by invoking the `getMatchingJob` method.
+- AWS Glue Data Catalog table
 
+- AWS IAM role
 
-**Note:** See the [specification document](SPECIFICATION.md) for a complete list of operations. 
+- AWS S3 bucket
+
+- AWS Entity Resolution Schema
+
+2. Uploads sample JSON and CSV data to S3
+
+3. Creates schema mappings for JSON and CSV datasets
+
+4. Creates and starts an Entity Resolution matching workflow
+
+5. Retrieves job details and schema mappings
+
+6. Lists available schema mappings
+
+7. Tags AWS resources for better organization
+
+8. Views the results of the workflow
 
 ## Resources
 
 This Basics scenario requires an IAM role that has permissions to work with the AWS Entity Resolution service, 
-an AWS Glue database, and two S3 buckets. A CDK script is provided to create these resources. 
+an AWS Glue database, and an S3 bucket. A CDK script is provided to create these resources. 
 See the resources [Readme](../../../resources/cdk/entityresolution_resources/README.md) file.
 
 ## Implementations