使用SDK适用于 Java 2.x 的 Amazon Redshift 示例 - AWS SDK代码示例

AWS 文档 AWS SDK示例 GitHub 存储库中还有更多SDK示例

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使用SDK适用于 Java 2.x 的 Amazon Redshift 示例

以下代码示例向您展示了如何在 Amazon Redshift 中 AWS SDK for Java 2.x 使用来执行操作和实现常见场景。

基础知识是向您展示如何在服务中执行基本操作的代码示例。

操作是大型程序的代码摘录,必须在上下文中运行。您可以通过操作了解如何调用单个服务函数,还可以通过函数相关场景的上下文查看操作。

场景是向您展示如何通过在一个服务中调用多个函数或与其他 AWS 服务结合来完成特定任务的代码示例。

每个示例都包含一个指向完整源代码的链接,您可以在其中找到有关如何在上下文中设置和运行代码的说明。

开始使用

以下代码示例展示了如何开始使用 Amazon Redshift。

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.redshift.RedshiftClient; import software.amazon.awssdk.services.redshift.paginators.DescribeClustersIterable; /** * Before running this Java V2 code example, set up your development * environment, including your credentials. * * For more information, see the following documentation topic: * * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html */ public class HelloRedshift { public static void main(String[] args) { Region region = Region.US_EAST_1; RedshiftClient redshiftClient = RedshiftClient.builder() .region(region) .build(); listClustersPaginator(redshiftClient); } public static void listClustersPaginator(RedshiftClient redshiftClient) { DescribeClustersIterable clustersIterable = redshiftClient.describeClustersPaginator(); clustersIterable.stream() .flatMap(r -> r.clusters().stream()) .forEach(cluster -> System.out .println(" Cluster identifier: " + cluster.clusterIdentifier() + " status = " + cluster.clusterStatus())); } }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 DescribeClusters” 中的。

基础知识

以下代码示例展示了如何使用学习 Amazon Redshift 的核心操作。 AWS SDK

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

运行一个交互式场景,演示 Amazon Redshift 的功能。

import com.example.redshift.User; import com.google.gson.Gson; import org.slf4j.Logger; import org.slf4j.LoggerFactory; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.redshift.model.ClusterAlreadyExistsException; import software.amazon.awssdk.services.redshift.model.CreateClusterResponse; import software.amazon.awssdk.services.redshift.model.DeleteClusterResponse; import software.amazon.awssdk.services.redshift.model.ModifyClusterResponse; import software.amazon.awssdk.services.redshift.model.RedshiftException; import software.amazon.awssdk.services.redshiftdata.model.ExecuteStatementResponse; import software.amazon.awssdk.services.redshiftdata.model.RedshiftDataException; import java.util.Scanner; import java.util.concurrent.CompletableFuture; import software.amazon.awssdk.services.secretsmanager.SecretsManagerClient; import software.amazon.awssdk.services.secretsmanager.model.GetSecretValueRequest; import software.amazon.awssdk.services.secretsmanager.model.GetSecretValueResponse; /** * Before running this Java V2 code example, set up your development * environment, including your credentials. * * For more information, see the following documentation topic: * * https://docs.aws.amazon.com/sdk-for-java/latest/developer-guide/get-started.html * * * This example requires an AWS Secrets Manager secret that contains the * database credentials. If you do not create a * secret that specifies user name and password, this example will not work. For details, see: * * https://docs.aws.amazon.com/secretsmanager/latest/userguide/integrating_how-services-use-secrets_RS.html * This Java example performs these tasks: * * 1. Prompts the user for a unique cluster ID or use the default value. * 2. Creates a Redshift cluster with the specified or default cluster Id value. * 3. Waits until the Redshift cluster is available for use. * 4. Lists all databases using a pagination API call. * 5. Creates a table named "Movies" with fields ID, title, and year. * 6. Inserts a specified number of records into the "Movies" table by reading the Movies JSON file. * 7. Prompts the user for a movie release year. * 8. Runs a SQL query to retrieve movies released in the specified year. * 9. Modifies the Redshift cluster. * 10. Prompts the user for confirmation to delete the Redshift cluster. * 11. If confirmed, deletes the specified Redshift cluster. */ public class RedshiftScenario { public static final String DASHES = new String(new char[80]).replace("\0", "-"); private static final Logger logger = LoggerFactory.getLogger(RedshiftScenario.class); static RedshiftActions redshiftActions = new RedshiftActions(); public static void main(String[] args) throws Exception { final String usage = """ Usage: <jsonFilePath> <secretName>\s Where: jsonFilePath - The path to the Movies JSON file (you can locate that file in ../../../resources/sample_files/movies.json) secretName - The name of the secret that belongs to Secret Manager that stores the user name and password used in this scenario. """; if (args.length != 2) { logger.info(usage); return; } String jsonFilePath = args[0]; String secretName = args[1]; Scanner scanner = new Scanner(System.in); logger.info(DASHES); logger.info("Welcome to the Amazon Redshift SDK Basics scenario."); logger.info(""" This Java program demonstrates how to interact with Amazon Redshift by using the AWS SDK for Java (v2).\s Amazon Redshift is a fully managed, petabyte-scale data warehouse service hosted in the cloud. The program's primary functionalities include cluster creation, verification of cluster readiness,\s list databases, table creation, data population within the table, and execution of SQL statements. Furthermore, it demonstrates the process of querying data from the Movie table.\s Upon completion of the program, all AWS resources are cleaned up. """); logger.info("Lets get started..."); logger.info(""" First, we will retrieve the user name and password from Secrets Manager. Using Amazon Secrets Manager to store Redshift credentials provides several security benefits. It allows you to securely store and manage sensitive information, such as passwords, API keys, and database credentials, without embedding them directly in your application code. More information can be found here: https://docs.aws.amazon.com/secretsmanager/latest/userguide/integrating_how-services-use-secrets_RS.html """); Gson gson = new Gson(); User user = gson.fromJson(String.valueOf(getSecretValues(secretName)), User.class); waitForInputToContinue(scanner); logger.info(DASHES); try { runScenario(user, scanner, jsonFilePath); } catch (RuntimeException e) { e.printStackTrace(); } catch (Throwable e) { throw new RuntimeException(e); } } private static void runScenario(User user, Scanner scanner, String jsonFilePath) throws Throwable { String databaseName = "dev"; System.out.println(DASHES); logger.info("Create a Redshift Cluster"); logger.info("A Redshift cluster refers to the collection of computing resources and storage that work together to process and analyze large volumes of data."); logger.info("Enter a cluster id value or accept the default by hitting Enter (default is redshift-cluster-movies): "); String userClusterId = scanner.nextLine(); String clusterId = userClusterId.isEmpty() ? "redshift-cluster-movies" : userClusterId; try { CompletableFuture<CreateClusterResponse> future = redshiftActions.createClusterAsync(clusterId, user.getUserName(), user.getUserPassword()); CreateClusterResponse response = future.join(); logger.info("Cluster successfully created. Cluster Identifier {} ", response.cluster().clusterIdentifier()); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof ClusterAlreadyExistsException) { logger.info("The Cluster {} already exists. Moving on...", clusterId); } else { logger.info("An unexpected error occurred: " + rt.getMessage()); } } logger.info(DASHES); logger.info(DASHES); logger.info("Wait until {} is available.", clusterId); waitForInputToContinue(scanner); try { CompletableFuture<Void> future = redshiftActions.waitForClusterReadyAsync(clusterId); future.join(); logger.info("Cluster is ready!"); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftException redshiftEx) { logger.info("Redshift error occurred: Error message: {}, Error code {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: " + rt.getMessage()); } throw cause; } logger.info(DASHES); logger.info(DASHES); String databaseInfo = """ When you created $clusteridD, the dev database is created by default and used in this scenario.\s To create a custom database, you need to have a CREATEDB privilege.\s For more information, see the documentation here: https://docs.aws.amazon.com/redshift/latest/dg/r_CREATE_DATABASE.html. """.replace("$clusteridD", clusterId); logger.info(databaseInfo); waitForInputToContinue(scanner); logger.info(DASHES); logger.info(DASHES); logger.info("List databases in {} ",clusterId); waitForInputToContinue(scanner); try { CompletableFuture<Void> future = redshiftActions.listAllDatabasesAsync(clusterId, user.getUserName(), "dev"); future.join(); logger.info("Databases listed successfully."); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.error("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.error("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } logger.info(DASHES); logger.info(DASHES); logger.info("Now you will create a table named Movies."); waitForInputToContinue(scanner); try { CompletableFuture<ExecuteStatementResponse> future = redshiftActions.createTableAsync(clusterId, databaseName, user.getUserName()); future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } logger.info(DASHES); logger.info(DASHES); logger.info("Populate the Movies table using the Movies.json file."); logger.info("Specify the number of records you would like to add to the Movies Table."); logger.info("Please enter a value between 50 and 200."); int numRecords; do { logger.info("Enter a value: "); while (!scanner.hasNextInt()) { logger.info("Invalid input. Please enter a value between 50 and 200."); logger.info("Enter a year: "); scanner.next(); } numRecords = scanner.nextInt(); } while (numRecords < 50 || numRecords > 200); try { redshiftActions.popTableAsync(clusterId, databaseName, user.getUserName(), jsonFilePath, numRecords).join(); // Wait for the operation to complete } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } waitForInputToContinue(scanner); logger.info(DASHES); logger.info(DASHES); logger.info("Query the Movies table by year. Enter a value between 2012-2014."); int movieYear; do { logger.info("Enter a year: "); while (!scanner.hasNextInt()) { logger.info("Invalid input. Please enter a valid year between 2012 and 2014."); logger.info("Enter a year: "); scanner.next(); } movieYear = scanner.nextInt(); scanner.nextLine(); } while (movieYear < 2012 || movieYear > 2014); String id; try { CompletableFuture<String> future = redshiftActions.queryMoviesByYearAsync(databaseName, user.getUserName(), movieYear, clusterId); id = future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } logger.info("The identifier of the statement is " + id); waitForInputToContinue(scanner); try { CompletableFuture<Void> future = redshiftActions.checkStatementAsync(id); future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } waitForInputToContinue(scanner); try { CompletableFuture<Void> future = redshiftActions.getResultsAsync(id); future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } waitForInputToContinue(scanner); logger.info(DASHES); logger.info(DASHES); logger.info("Now you will modify the Redshift cluster."); waitForInputToContinue(scanner); try { CompletableFuture<ModifyClusterResponse> future = redshiftActions.modifyClusterAsync(clusterId);; future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } waitForInputToContinue(scanner); logger.info(DASHES); logger.info(DASHES); logger.info("Would you like to delete the Amazon Redshift cluster? (y/n)"); String delAns = scanner.nextLine().trim(); if (delAns.equalsIgnoreCase("y")) { logger.info("You selected to delete {} ", clusterId); waitForInputToContinue(scanner); try { CompletableFuture<DeleteClusterResponse> future = redshiftActions.deleteRedshiftClusterAsync(clusterId);; future.join(); } catch (RuntimeException rt) { Throwable cause = rt.getCause(); if (cause instanceof RedshiftDataException redshiftEx) { logger.info("Redshift Data error occurred: {} Error code: {}", redshiftEx.getMessage(), redshiftEx.awsErrorDetails().errorCode()); } else { logger.info("An unexpected error occurred: {}", rt.getMessage()); } throw cause; } } else { logger.info("The {} was not deleted", clusterId); } logger.info(DASHES); logger.info(DASHES); logger.info("This concludes the Amazon Redshift SDK Basics scenario."); logger.info(DASHES); } private static SecretsManagerClient getSecretClient() { Region region = Region.US_EAST_1; return SecretsManagerClient.builder() .region(region) .build(); } private static void waitForInputToContinue(Scanner scanner) { while (true) { System.out.println(""); System.out.println("Enter 'c' followed by <ENTER> to continue:"); String input = scanner.nextLine(); if (input.trim().equalsIgnoreCase("c")) { System.out.println("Continuing with the program..."); System.out.println(""); break; } else { // Handle invalid input. System.out.println("Invalid input. Please try again."); } } } // Get the Amazon Redshift credentials from AWS Secrets Manager. private static String getSecretValues(String secretName) { SecretsManagerClient secretClient = getSecretClient(); GetSecretValueRequest valueRequest = GetSecretValueRequest.builder() .secretId(secretName) .build(); GetSecretValueResponse valueResponse = secretClient.getSecretValue(valueRequest); return valueResponse.secretString(); } }

亚马逊 SDK Redshift 方法的包装器类。

public class RedshiftActions { private static final Logger logger = LoggerFactory.getLogger(RedshiftActions.class); private static RedshiftDataAsyncClient redshiftDataAsyncClient; private static RedshiftAsyncClient redshiftAsyncClient; private static RedshiftAsyncClient getAsyncClient() { if (redshiftAsyncClient == null) { SdkAsyncHttpClient httpClient = NettyNioAsyncHttpClient.builder() .maxConcurrency(100) .connectionTimeout(Duration.ofSeconds(60)) .readTimeout(Duration.ofSeconds(60)) .writeTimeout(Duration.ofSeconds(60)) .build(); ClientOverrideConfiguration overrideConfig = ClientOverrideConfiguration.builder() .apiCallTimeout(Duration.ofMinutes(2)) .apiCallAttemptTimeout(Duration.ofSeconds(90)) .retryStrategy(RetryMode.STANDARD) .build(); redshiftAsyncClient = RedshiftAsyncClient.builder() .httpClient(httpClient) .overrideConfiguration(overrideConfig) .credentialsProvider(EnvironmentVariableCredentialsProvider.create()) .build(); } return redshiftAsyncClient; } private static RedshiftDataAsyncClient getAsyncDataClient() { if (redshiftDataAsyncClient == null) { SdkAsyncHttpClient httpClient = NettyNioAsyncHttpClient.builder() .maxConcurrency(100) .connectionTimeout(Duration.ofSeconds(60)) .readTimeout(Duration.ofSeconds(60)) .writeTimeout(Duration.ofSeconds(60)) .build(); ClientOverrideConfiguration overrideConfig = ClientOverrideConfiguration.builder() .apiCallTimeout(Duration.ofMinutes(2)) .apiCallAttemptTimeout(Duration.ofSeconds(90)) .retryStrategy(RetryMode.STANDARD) .build(); redshiftDataAsyncClient = RedshiftDataAsyncClient.builder() .httpClient(httpClient) .overrideConfiguration(overrideConfig) .credentialsProvider(EnvironmentVariableCredentialsProvider.create()) .build(); } return redshiftDataAsyncClient; } /** * Creates a new Amazon Redshift cluster asynchronously. * @param clusterId the unique identifier for the cluster * @param username the username for the administrative user * @param userPassword the password for the administrative user * @return a CompletableFuture that represents the asynchronous operation of creating the cluster * @throws RuntimeException if the cluster creation fails */ public CompletableFuture<CreateClusterResponse> createClusterAsync(String clusterId, String username, String userPassword) { CreateClusterRequest clusterRequest = CreateClusterRequest.builder() .clusterIdentifier(clusterId) .masterUsername(username) .masterUserPassword(userPassword) .nodeType("ra3.4xlarge") .publiclyAccessible(true) .numberOfNodes(2) .build(); return getAsyncClient().createCluster(clusterRequest) .whenComplete((response, exception) -> { if (response != null) { logger.info("Created cluster "); } else { throw new RuntimeException("Failed to create cluster: " + exception.getMessage(), exception); } }); } /** * Waits asynchronously for the specified cluster to become available. * @param clusterId the identifier of the cluster to wait for * @return a {@link CompletableFuture} that completes when the cluster is ready */ public CompletableFuture<Void> waitForClusterReadyAsync(String clusterId) { DescribeClustersRequest clustersRequest = DescribeClustersRequest.builder() .clusterIdentifier(clusterId) .build(); logger.info("Waiting for cluster to become available. This may take a few minutes."); long startTime = System.currentTimeMillis(); // Recursive method to poll the cluster status. return checkClusterStatusAsync(clustersRequest, startTime); } private CompletableFuture<Void> checkClusterStatusAsync(DescribeClustersRequest clustersRequest, long startTime) { return getAsyncClient().describeClusters(clustersRequest) .thenCompose(clusterResponse -> { List<Cluster> clusterList = clusterResponse.clusters(); boolean clusterReady = false; for (Cluster cluster : clusterList) { if ("available".equals(cluster.clusterStatus())) { clusterReady = true; break; } } if (clusterReady) { logger.info(String.format("Cluster is available!")); return CompletableFuture.completedFuture(null); } else { long elapsedTimeMillis = System.currentTimeMillis() - startTime; long elapsedSeconds = elapsedTimeMillis / 1000; long minutes = elapsedSeconds / 60; long seconds = elapsedSeconds % 60; System.out.printf("\rElapsed Time: %02d:%02d - Waiting for cluster...", minutes, seconds); System.out.flush(); // Wait 1 second before the next status check return CompletableFuture.runAsync(() -> { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { throw new RuntimeException("Error during sleep: " + e.getMessage(), e); } }).thenCompose(ignored -> checkClusterStatusAsync(clustersRequest, startTime)); } }).exceptionally(exception -> { throw new RuntimeException("Failed to get cluster status: " + exception.getMessage(), exception); }); } /** * Lists all databases asynchronously for the specified cluster, database user, and database. * @param clusterId the identifier of the cluster to list databases for * @param dbUser the database user to use for the list databases request * @param database the database to list databases for * @return a {@link CompletableFuture} that completes when the database listing is complete, or throws a {@link RuntimeException} if there was an error */ public CompletableFuture<Void> listAllDatabasesAsync(String clusterId, String dbUser, String database) { ListDatabasesRequest databasesRequest = ListDatabasesRequest.builder() .clusterIdentifier(clusterId) .dbUser(dbUser) .database(database) .build(); // Asynchronous paginator for listing databases. ListDatabasesPublisher databasesPaginator = getAsyncDataClient().listDatabasesPaginator(databasesRequest); CompletableFuture<Void> future = databasesPaginator.subscribe(response -> { response.databases().forEach(db -> { logger.info("The database name is {} ", db); }); }); // Return the future for asynchronous handling. return future.exceptionally(exception -> { throw new RuntimeException("Failed to list databases: " + exception.getMessage(), exception); }); } /** * Creates an asynchronous task to execute a SQL statement for creating a new table. * * @param clusterId the identifier of the Amazon Redshift cluster * @param databaseName the name of the database to create the table in * @param userName the username to use for the database connection * @return a {@link CompletableFuture} that completes with the result of the SQL statement execution * @throws RuntimeException if there is an error creating the table */ public CompletableFuture<ExecuteStatementResponse> createTableAsync(String clusterId, String databaseName, String userName) { ExecuteStatementRequest createTableRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .dbUser(userName) .database(databaseName) .sql("CREATE TABLE Movies (" + "id INT PRIMARY KEY, " + "title VARCHAR(100), " + "year INT)") .build(); return getAsyncDataClient().executeStatement(createTableRequest) .whenComplete((response, exception) -> { if (exception != null) { throw new RuntimeException("Error creating table: " + exception.getMessage(), exception); } else { logger.info("Table created: Movies"); } }); } /** * Asynchronously pops a table from a JSON file. * * @param clusterId the ID of the cluster * @param databaseName the name of the database * @param userName the username * @param fileName the name of the JSON file * @param number the number of records to process * @return a CompletableFuture that completes with the number of records added to the Movies table */ public CompletableFuture<Integer> popTableAsync(String clusterId, String databaseName, String userName, String fileName, int number) { return CompletableFuture.supplyAsync(() -> { try { JsonParser parser = new JsonFactory().createParser(new File(fileName)); JsonNode rootNode = new ObjectMapper().readTree(parser); Iterator<JsonNode> iter = rootNode.iterator(); return iter; } catch (IOException e) { throw new RuntimeException("Failed to read or parse JSON file: " + e.getMessage(), e); } }).thenCompose(iter -> processNodesAsync(clusterId, databaseName, userName, iter, number)) .whenComplete((result, exception) -> { if (exception != null) { logger.info("Error {} ", exception.getMessage()); } else { logger.info("{} records were added to the Movies table." , result); } }); } private CompletableFuture<Integer> processNodesAsync(String clusterId, String databaseName, String userName, Iterator<JsonNode> iter, int number) { return CompletableFuture.supplyAsync(() -> { int t = 0; try { while (iter.hasNext()) { if (t == number) break; JsonNode currentNode = iter.next(); int year = currentNode.get("year").asInt(); String title = currentNode.get("title").asText(); // Use SqlParameter to avoid SQL injection. List<SqlParameter> parameterList = new ArrayList<>(); String sqlStatement = "INSERT INTO Movies VALUES( :id , :title, :year);"; SqlParameter idParam = SqlParameter.builder() .name("id") .value(String.valueOf(t)) .build(); SqlParameter titleParam = SqlParameter.builder() .name("title") .value(title) .build(); SqlParameter yearParam = SqlParameter.builder() .name("year") .value(String.valueOf(year)) .build(); parameterList.add(idParam); parameterList.add(titleParam); parameterList.add(yearParam); ExecuteStatementRequest insertStatementRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .sql(sqlStatement) .database(databaseName) .dbUser(userName) .parameters(parameterList) .build(); getAsyncDataClient().executeStatement(insertStatementRequest); logger.info("Inserted: " + title + " (" + year + ")"); t++; } } catch (RedshiftDataException e) { throw new RuntimeException("Error inserting data: " + e.getMessage(), e); } return t; }); } /** * Checks the status of an SQL statement asynchronously and handles the completion of the statement. * * @param sqlId the ID of the SQL statement to check * @return a {@link CompletableFuture} that completes when the SQL statement's status is either "FINISHED" or "FAILED" */ public CompletableFuture<Void> checkStatementAsync(String sqlId) { DescribeStatementRequest statementRequest = DescribeStatementRequest.builder() .id(sqlId) .build(); return getAsyncDataClient().describeStatement(statementRequest) .thenCompose(response -> { String status = response.statusAsString(); logger.info("... Status: {} ", status); if ("FAILED".equals(status)) { throw new RuntimeException("The Query Failed. Ending program"); } else if ("FINISHED".equals(status)) { return CompletableFuture.completedFuture(null); } else { // Sleep for 1 second and recheck status return CompletableFuture.runAsync(() -> { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { throw new RuntimeException("Error during sleep: " + e.getMessage(), e); } }).thenCompose(ignore -> checkStatementAsync(sqlId)); // Recursively call until status is FINISHED or FAILED } }).whenComplete((result, exception) -> { if (exception != null) { // Handle exceptions logger.info("Error: {} ", exception.getMessage()); } else { logger.info("The statement is finished!"); } }); } /** * Asynchronously retrieves the results of a statement execution. * * @param statementId the ID of the statement for which to retrieve the results * @return a {@link CompletableFuture} that completes when the statement result has been processed */ public CompletableFuture<Void> getResultsAsync(String statementId) { GetStatementResultRequest resultRequest = GetStatementResultRequest.builder() .id(statementId) .build(); return getAsyncDataClient().getStatementResult(resultRequest) .handle((response, exception) -> { if (exception != null) { logger.info("Error getting statement result {} ", exception.getMessage()); throw new RuntimeException("Error getting statement result: " + exception.getMessage(), exception); } // Extract and print the field values using streams if the response is valid. response.records().stream() .flatMap(List::stream) .map(Field::stringValue) .filter(value -> value != null) .forEach(value -> System.out.println("The Movie title field is " + value)); return response; }).thenAccept(response -> { // Optionally add more logic here if needed after handling the response }); } /** * Asynchronously queries movies by a given year from a Redshift database. * * @param database the name of the database to query * @param dbUser the user to connect to the database with * @param year the year to filter the movies by * @param clusterId the identifier of the Redshift cluster to connect to * @return a {@link CompletableFuture} containing the response ID of the executed SQL statement */ public CompletableFuture<String> queryMoviesByYearAsync(String database, String dbUser, int year, String clusterId) { String sqlStatement = "SELECT * FROM Movies WHERE year = :year"; SqlParameter yearParam = SqlParameter.builder() .name("year") .value(String.valueOf(year)) .build(); ExecuteStatementRequest statementRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .database(database) .dbUser(dbUser) .parameters(yearParam) .sql(sqlStatement) .build(); return CompletableFuture.supplyAsync(() -> { try { ExecuteStatementResponse response = getAsyncDataClient().executeStatement(statementRequest).join(); // Use join() to wait for the result return response.id(); } catch (RedshiftDataException e) { throw new RuntimeException("Error executing statement: " + e.getMessage(), e); } }).exceptionally(exception -> { logger.info("Error: {}", exception.getMessage()); return ""; }); } /** * Modifies an Amazon Redshift cluster asynchronously. * * @param clusterId the identifier of the cluster to be modified * @return a {@link CompletableFuture} that completes when the cluster modification is complete */ public CompletableFuture<ModifyClusterResponse> modifyClusterAsync(String clusterId) { ModifyClusterRequest modifyClusterRequest = ModifyClusterRequest.builder() .clusterIdentifier(clusterId) .preferredMaintenanceWindow("wed:07:30-wed:08:00") .build(); return getAsyncClient().modifyCluster(modifyClusterRequest) .whenComplete((clusterResponse, exception) -> { if (exception != null) { if (exception.getCause() instanceof RedshiftException) { logger.info("Error: {} ", exception.getMessage()); } else { logger.info("Unexpected error: {} ", exception.getMessage()); } } else { logger.info("The modified cluster was successfully modified and has " + clusterResponse.cluster().preferredMaintenanceWindow() + " as the maintenance window"); } }); } /** * Deletes a Redshift cluster asynchronously. * * @param clusterId the identifier of the Redshift cluster to be deleted * @return a {@link CompletableFuture} that represents the asynchronous operation of deleting the Redshift cluster */ public CompletableFuture<DeleteClusterResponse> deleteRedshiftClusterAsync(String clusterId) { DeleteClusterRequest deleteClusterRequest = DeleteClusterRequest.builder() .clusterIdentifier(clusterId) .skipFinalClusterSnapshot(true) .build(); return getAsyncClient().deleteCluster(deleteClusterRequest) .whenComplete((response, exception) -> { if (exception != null) { // Handle exceptions if (exception.getCause() instanceof RedshiftException) { logger.info("Error: {}", exception.getMessage()); } else { logger.info("Unexpected error: {}", exception.getMessage()); } } else { // Handle successful response logger.info("The status is {}", response.cluster().clusterStatus()); } }); } }

操作

以下代码示例演示如何使用 CreateCluster

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

创建集群。

/** * Creates a new Amazon Redshift cluster asynchronously. * @param clusterId the unique identifier for the cluster * @param username the username for the administrative user * @param userPassword the password for the administrative user * @return a CompletableFuture that represents the asynchronous operation of creating the cluster * @throws RuntimeException if the cluster creation fails */ public CompletableFuture<CreateClusterResponse> createClusterAsync(String clusterId, String username, String userPassword) { CreateClusterRequest clusterRequest = CreateClusterRequest.builder() .clusterIdentifier(clusterId) .masterUsername(username) .masterUserPassword(userPassword) .nodeType("ra3.4xlarge") .publiclyAccessible(true) .numberOfNodes(2) .build(); return getAsyncClient().createCluster(clusterRequest) .whenComplete((response, exception) -> { if (response != null) { logger.info("Created cluster "); } else { throw new RuntimeException("Failed to create cluster: " + exception.getMessage(), exception); } }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 CreateCluster” 中的。

以下代码示例演示如何使用 DeleteCluster

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

请删除集群。

/** * Deletes a Redshift cluster asynchronously. * * @param clusterId the identifier of the Redshift cluster to be deleted * @return a {@link CompletableFuture} that represents the asynchronous operation of deleting the Redshift cluster */ public CompletableFuture<DeleteClusterResponse> deleteRedshiftClusterAsync(String clusterId) { DeleteClusterRequest deleteClusterRequest = DeleteClusterRequest.builder() .clusterIdentifier(clusterId) .skipFinalClusterSnapshot(true) .build(); return getAsyncClient().deleteCluster(deleteClusterRequest) .whenComplete((response, exception) -> { if (exception != null) { // Handle exceptions if (exception.getCause() instanceof RedshiftException) { logger.info("Error: {}", exception.getMessage()); } else { logger.info("Unexpected error: {}", exception.getMessage()); } } else { // Handle successful response logger.info("The status is {}", response.cluster().clusterStatus()); } }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 DeleteCluster” 中的。

以下代码示例演示如何使用 DescribeClusters

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

描述集群。

/** * Waits asynchronously for the specified cluster to become available. * @param clusterId the identifier of the cluster to wait for * @return a {@link CompletableFuture} that completes when the cluster is ready */ public CompletableFuture<Void> waitForClusterReadyAsync(String clusterId) { DescribeClustersRequest clustersRequest = DescribeClustersRequest.builder() .clusterIdentifier(clusterId) .build(); logger.info("Waiting for cluster to become available. This may take a few minutes."); long startTime = System.currentTimeMillis(); // Recursive method to poll the cluster status. return checkClusterStatusAsync(clustersRequest, startTime); } private CompletableFuture<Void> checkClusterStatusAsync(DescribeClustersRequest clustersRequest, long startTime) { return getAsyncClient().describeClusters(clustersRequest) .thenCompose(clusterResponse -> { List<Cluster> clusterList = clusterResponse.clusters(); boolean clusterReady = false; for (Cluster cluster : clusterList) { if ("available".equals(cluster.clusterStatus())) { clusterReady = true; break; } } if (clusterReady) { logger.info(String.format("Cluster is available!")); return CompletableFuture.completedFuture(null); } else { long elapsedTimeMillis = System.currentTimeMillis() - startTime; long elapsedSeconds = elapsedTimeMillis / 1000; long minutes = elapsedSeconds / 60; long seconds = elapsedSeconds % 60; System.out.printf("\rElapsed Time: %02d:%02d - Waiting for cluster...", minutes, seconds); System.out.flush(); // Wait 1 second before the next status check return CompletableFuture.runAsync(() -> { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { throw new RuntimeException("Error during sleep: " + e.getMessage(), e); } }).thenCompose(ignored -> checkClusterStatusAsync(clustersRequest, startTime)); } }).exceptionally(exception -> { throw new RuntimeException("Failed to get cluster status: " + exception.getMessage(), exception); }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 DescribeClusters” 中的。

以下代码示例演示如何使用 DescribeStatement

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

/** * Checks the status of an SQL statement asynchronously and handles the completion of the statement. * * @param sqlId the ID of the SQL statement to check * @return a {@link CompletableFuture} that completes when the SQL statement's status is either "FINISHED" or "FAILED" */ public CompletableFuture<Void> checkStatementAsync(String sqlId) { DescribeStatementRequest statementRequest = DescribeStatementRequest.builder() .id(sqlId) .build(); return getAsyncDataClient().describeStatement(statementRequest) .thenCompose(response -> { String status = response.statusAsString(); logger.info("... Status: {} ", status); if ("FAILED".equals(status)) { throw new RuntimeException("The Query Failed. Ending program"); } else if ("FINISHED".equals(status)) { return CompletableFuture.completedFuture(null); } else { // Sleep for 1 second and recheck status return CompletableFuture.runAsync(() -> { try { TimeUnit.SECONDS.sleep(1); } catch (InterruptedException e) { throw new RuntimeException("Error during sleep: " + e.getMessage(), e); } }).thenCompose(ignore -> checkStatementAsync(sqlId)); // Recursively call until status is FINISHED or FAILED } }).whenComplete((result, exception) -> { if (exception != null) { // Handle exceptions logger.info("Error: {} ", exception.getMessage()); } else { logger.info("The statement is finished!"); } }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 DescribeStatement” 中的。

以下代码示例演示如何使用 ExecuteStatement

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

执行一条创建数据库表的SQL语句。

/** * Creates an asynchronous task to execute a SQL statement for creating a new table. * * @param clusterId the identifier of the Amazon Redshift cluster * @param databaseName the name of the database to create the table in * @param userName the username to use for the database connection * @return a {@link CompletableFuture} that completes with the result of the SQL statement execution * @throws RuntimeException if there is an error creating the table */ public CompletableFuture<ExecuteStatementResponse> createTableAsync(String clusterId, String databaseName, String userName) { ExecuteStatementRequest createTableRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .dbUser(userName) .database(databaseName) .sql("CREATE TABLE Movies (" + "id INT PRIMARY KEY, " + "title VARCHAR(100), " + "year INT)") .build(); return getAsyncDataClient().executeStatement(createTableRequest) .whenComplete((response, exception) -> { if (exception != null) { throw new RuntimeException("Error creating table: " + exception.getMessage(), exception); } else { logger.info("Table created: Movies"); } }); }

执行一条将数据插入数据库表的SQL语句。

/** * Asynchronously pops a table from a JSON file. * * @param clusterId the ID of the cluster * @param databaseName the name of the database * @param userName the username * @param fileName the name of the JSON file * @param number the number of records to process * @return a CompletableFuture that completes with the number of records added to the Movies table */ public CompletableFuture<Integer> popTableAsync(String clusterId, String databaseName, String userName, String fileName, int number) { return CompletableFuture.supplyAsync(() -> { try { JsonParser parser = new JsonFactory().createParser(new File(fileName)); JsonNode rootNode = new ObjectMapper().readTree(parser); Iterator<JsonNode> iter = rootNode.iterator(); return iter; } catch (IOException e) { throw new RuntimeException("Failed to read or parse JSON file: " + e.getMessage(), e); } }).thenCompose(iter -> processNodesAsync(clusterId, databaseName, userName, iter, number)) .whenComplete((result, exception) -> { if (exception != null) { logger.info("Error {} ", exception.getMessage()); } else { logger.info("{} records were added to the Movies table." , result); } }); } private CompletableFuture<Integer> processNodesAsync(String clusterId, String databaseName, String userName, Iterator<JsonNode> iter, int number) { return CompletableFuture.supplyAsync(() -> { int t = 0; try { while (iter.hasNext()) { if (t == number) break; JsonNode currentNode = iter.next(); int year = currentNode.get("year").asInt(); String title = currentNode.get("title").asText(); // Use SqlParameter to avoid SQL injection. List<SqlParameter> parameterList = new ArrayList<>(); String sqlStatement = "INSERT INTO Movies VALUES( :id , :title, :year);"; SqlParameter idParam = SqlParameter.builder() .name("id") .value(String.valueOf(t)) .build(); SqlParameter titleParam = SqlParameter.builder() .name("title") .value(title) .build(); SqlParameter yearParam = SqlParameter.builder() .name("year") .value(String.valueOf(year)) .build(); parameterList.add(idParam); parameterList.add(titleParam); parameterList.add(yearParam); ExecuteStatementRequest insertStatementRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .sql(sqlStatement) .database(databaseName) .dbUser(userName) .parameters(parameterList) .build(); getAsyncDataClient().executeStatement(insertStatementRequest); logger.info("Inserted: " + title + " (" + year + ")"); t++; } } catch (RedshiftDataException e) { throw new RuntimeException("Error inserting data: " + e.getMessage(), e); } return t; }); }

执行查询数据库表的SQL语句。

/** * Asynchronously queries movies by a given year from a Redshift database. * * @param database the name of the database to query * @param dbUser the user to connect to the database with * @param year the year to filter the movies by * @param clusterId the identifier of the Redshift cluster to connect to * @return a {@link CompletableFuture} containing the response ID of the executed SQL statement */ public CompletableFuture<String> queryMoviesByYearAsync(String database, String dbUser, int year, String clusterId) { String sqlStatement = "SELECT * FROM Movies WHERE year = :year"; SqlParameter yearParam = SqlParameter.builder() .name("year") .value(String.valueOf(year)) .build(); ExecuteStatementRequest statementRequest = ExecuteStatementRequest.builder() .clusterIdentifier(clusterId) .database(database) .dbUser(dbUser) .parameters(yearParam) .sql(sqlStatement) .build(); return CompletableFuture.supplyAsync(() -> { try { ExecuteStatementResponse response = getAsyncDataClient().executeStatement(statementRequest).join(); // Use join() to wait for the result return response.id(); } catch (RedshiftDataException e) { throw new RuntimeException("Error executing statement: " + e.getMessage(), e); } }).exceptionally(exception -> { logger.info("Error: {}", exception.getMessage()); return ""; }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 ExecuteStatement” 中的。

以下代码示例演示如何使用 GetStatementResult

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

检查语句结果。

/** * Asynchronously retrieves the results of a statement execution. * * @param statementId the ID of the statement for which to retrieve the results * @return a {@link CompletableFuture} that completes when the statement result has been processed */ public CompletableFuture<Void> getResultsAsync(String statementId) { GetStatementResultRequest resultRequest = GetStatementResultRequest.builder() .id(statementId) .build(); return getAsyncDataClient().getStatementResult(resultRequest) .handle((response, exception) -> { if (exception != null) { logger.info("Error getting statement result {} ", exception.getMessage()); throw new RuntimeException("Error getting statement result: " + exception.getMessage(), exception); } // Extract and print the field values using streams if the response is valid. response.records().stream() .flatMap(List::stream) .map(Field::stringValue) .filter(value -> value != null) .forEach(value -> System.out.println("The Movie title field is " + value)); return response; }).thenAccept(response -> { // Optionally add more logic here if needed after handling the response }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 GetStatementResult” 中的。

以下代码示例演示如何使用 ListDatabases

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

/** * Lists all databases asynchronously for the specified cluster, database user, and database. * @param clusterId the identifier of the cluster to list databases for * @param dbUser the database user to use for the list databases request * @param database the database to list databases for * @return a {@link CompletableFuture} that completes when the database listing is complete, or throws a {@link RuntimeException} if there was an error */ public CompletableFuture<Void> listAllDatabasesAsync(String clusterId, String dbUser, String database) { ListDatabasesRequest databasesRequest = ListDatabasesRequest.builder() .clusterIdentifier(clusterId) .dbUser(dbUser) .database(database) .build(); // Asynchronous paginator for listing databases. ListDatabasesPublisher databasesPaginator = getAsyncDataClient().listDatabasesPaginator(databasesRequest); CompletableFuture<Void> future = databasesPaginator.subscribe(response -> { response.databases().forEach(db -> { logger.info("The database name is {} ", db); }); }); // Return the future for asynchronous handling. return future.exceptionally(exception -> { throw new RuntimeException("Failed to list databases: " + exception.getMessage(), exception); }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 ListDatabases” 中的。

以下代码示例演示如何使用 ModifyCluster

SDK适用于 Java 2.x
注意

还有更多相关信息 GitHub。查找完整示例,学习如何在 AWS 代码示例存储库中进行设置和运行。

修改集群。

/** * Modifies an Amazon Redshift cluster asynchronously. * * @param clusterId the identifier of the cluster to be modified * @return a {@link CompletableFuture} that completes when the cluster modification is complete */ public CompletableFuture<ModifyClusterResponse> modifyClusterAsync(String clusterId) { ModifyClusterRequest modifyClusterRequest = ModifyClusterRequest.builder() .clusterIdentifier(clusterId) .preferredMaintenanceWindow("wed:07:30-wed:08:00") .build(); return getAsyncClient().modifyCluster(modifyClusterRequest) .whenComplete((clusterResponse, exception) -> { if (exception != null) { if (exception.getCause() instanceof RedshiftException) { logger.info("Error: {} ", exception.getMessage()); } else { logger.info("Unexpected error: {} ", exception.getMessage()); } } else { logger.info("The modified cluster was successfully modified and has " + clusterResponse.cluster().preferredMaintenanceWindow() + " as the maintenance window"); } }); }
  • 有关API详细信息,请参阅 “AWS SDK for Java 2.x API参考 ModifyCluster” 中的。

场景

以下代码示例演示如何使用 Amazon Redshift 数据库创建用于跟踪和报告工作项的 Web 应用程序。

SDK适用于 Java 2.x

展示如何创建 Web 应用程序来跟踪与报告存储与 Amazon Redshift 数据库的工作项。

有关如何设置查询 Amazon Redshift 数据RESTAPI的 Spring 以及供 React 应用程序使用的完整源代码和说明,请参阅上的完整示例。GitHub

本示例中使用的服务
  • Amazon Redshift

  • Amazon SES