AWS SDK와 ExecuteStatement 함께 사용

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다음 코드 예시에서는 ExecuteStatement을 사용하는 방법을 보여 줍니다.

작업 예제는 대규모 프로그램에서 발췌한 코드이며 컨텍스트에 맞춰 실행해야 합니다. 다음 코드 예제에서 컨텍스트 내 이 작업을 확인할 수 있습니다.

• 기본 사항 알아보기

Java

SDK for Java 2.x

참고

GitHub에 더 많은 내용이 있습니다. AWS 코드 예시 리포지토리에서 전체 예시를 찾고 설정 및 실행하는 방법을 배워보세요.

SQL 스테이트먼트를 실행하여 데이터베이스 테이블을 만듭니다.

    /**
     * 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");
                }
            });
    }

SQL 스테이트먼트를 실행하여 데이터베이스 테이블에 데이터를 삽입합니다.

    /**
     * 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;
        });
    }

SQL 스테이트먼트를 실행하여 데이터베이스 테이블을 쿼리합니다.

    /**
     * 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 "";
        });
    }

• API 세부 정보는 AWS SDK for Java 2.x API 참조의 ExecuteStatement를 참조하세요.