DatasyncS

Here’s how to rewrite the synchronization code using Spring Data and JdbcTemplate for cleaner and more maintainable code.


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Spring Data/JdbcTemplate Implementation

1. Configuration: Define a Spring configuration for your data sources (Oracle and SQL Server).


2. Repository Layer: Use JdbcTemplate for interacting with the databases.


3. Service Layer: Implement the synchronization logic with transaction management.


4. Main Application: Orchestrate the process.




---

1. Spring Configuration

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.jdbc.datasource.DriverManagerDataSource;

import javax.sql.DataSource;

@Configuration
public class DataSourceConfig {

    @Bean
    public DataSource oracleDataSource() {
        DriverManagerDataSource dataSource = new DriverManagerDataSource();
        dataSource.setDriverClassName("oracle.jdbc.driver.OracleDriver");
        dataSource.setUrl("jdbc:oracle:thin:@//host:port/service");
        dataSource.setUsername("oracle_user");
        dataSource.setPassword("oracle_password");
        return dataSource;
    }

    @Bean
    public DataSource sqlServerDataSource() {
        DriverManagerDataSource dataSource = new DriverManagerDataSource();
        dataSource.setDriverClassName("com.microsoft.sqlserver.jdbc.SQLServerDriver");
        dataSource.setUrl("jdbc:sqlserver://host:port;databaseName=yourDB");
        dataSource.setUsername("sqlserver_user");
        dataSource.setPassword("sqlserver_password");
        return dataSource;
    }

    @Bean
    public JdbcTemplate oracleJdbcTemplate(DataSource oracleDataSource) {
        return new JdbcTemplate(oracleDataSource);
    }

    @Bean
    public JdbcTemplate sqlServerJdbcTemplate(DataSource sqlServerDataSource) {
        return new JdbcTemplate(sqlServerDataSource);
    }
}


---

2. Repository Layer

Oracle Repository:

import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Repository;

import java.sql.Timestamp;
import java.util.List;

@Repository
public class OracleRepository {
    private final JdbcTemplate jdbcTemplate;

    public OracleRepository(JdbcTemplate oracleJdbcTemplate) {
        this.jdbcTemplate = oracleJdbcTemplate;
    }

    public List<Record> fetchSourceData(Timestamp lastUpdate) {
        String query = "SELECT id, col1, col2, last_update FROM source_table WHERE last_update > ?";
        return jdbcTemplate.query(query, new Object[]{lastUpdate}, (rs, rowNum) -> 
            new Record(
                rs.getInt("id"),
                rs.getString("col1"),
                rs.getString("col2"),
                rs.getTimestamp("last_update")
            )
        );
    }
}

SQL Server Repository:

import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Repository;

import java.sql.Timestamp;

@Repository
public class SqlServerRepository {
    private final JdbcTemplate jdbcTemplate;

    public SqlServerRepository(JdbcTemplate sqlServerJdbcTemplate) {
        this.jdbcTemplate = sqlServerJdbcTemplate;
    }

    public Timestamp fetchMaxLastUpdate() {
        String query = "SELECT MAX(last_update) FROM target_table";
        return jdbcTemplate.queryForObject(query, Timestamp.class);
    }

    public void executeMergeQuery(String mergeQuery) {
        jdbcTemplate.execute(mergeQuery);
    }
}


---

3. Service Layer

import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

import java.sql.Timestamp;
import java.util.List;

@Service
public class DataSyncService {

    private final OracleRepository oracleRepository;
    private final SqlServerRepository sqlServerRepository;

    public DataSyncService(OracleRepository oracleRepository, SqlServerRepository sqlServerRepository) {
        this.oracleRepository = oracleRepository;
        this.sqlServerRepository = sqlServerRepository;
    }

    @Transactional
    public void syncData() {
        // Fetch max last_update from SQL Server
        Timestamp maxLastUpdate = sqlServerRepository.fetchMaxLastUpdate();
        if (maxLastUpdate == null) {
            maxLastUpdate = new Timestamp(0); // Default to epoch
        }

        // Fetch source data from Oracle
        List<Record> sourceRecords = oracleRepository.fetchSourceData(maxLastUpdate);

        // Process records in chunks
        int batchSize = 500;
        for (int i = 0; i < sourceRecords.size(); i += batchSize) {
            List<Record> batch = sourceRecords.subList(i, Math.min(i + batchSize, sourceRecords.size()));

            // Generate the dynamic CTE and execute the MERGE statement
            String mergeQuery = generateMergeQuery(batch);
            sqlServerRepository.executeMergeQuery(mergeQuery);
        }
    }

    private String generateMergeQuery(List<Record> records) {
        StringBuilder cteBuilder = new StringBuilder("WITH SourceCTE (id, col1, col2, last_update) AS (VALUES ");

        for (int i = 0; i < records.size(); i++) {
            Record record = records.get(i);
            cteBuilder.append("(")
                      .append(record.getId()).append(", ")
                      .append("'").append(record.getCol1().replace("'", "''")).append("', ")
                      .append("'").append(record.getCol2().replace("'", "''")).append("', ")
                      .append("'").append(record.getLastUpdate()).append("')");
            if (i < records.size() - 1) {
                cteBuilder.append(", ");
            }
        }
        cteBuilder.append(") ");

        return cteBuilder.append("""
            MERGE INTO target_table AS target
            USING SourceCTE AS source
            ON target.id = source.id
            WHEN MATCHED THEN
                UPDATE SET 
                    target.col1 = source.col1,
                    target.col2 = source.col2,
                    target.last_update = source.last_update
            WHEN NOT MATCHED THEN
                INSERT (id, col1, col2, last_update)
                VALUES (source.id, source.col1, source.col2, source.last_update);
        """).toString();
    }
}


---

4. Main Application

import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DataSyncApplication implements CommandLineRunner {

    private final DataSyncService dataSyncService;

    public DataSyncApplication(DataSyncService dataSyncService) {
        this.dataSyncService = dataSyncService;
    }

    public static void main(String[] args) {
        SpringApplication.run(DataSyncApplication.class, args);
    }

    @Override
    public void run(String... args) {
        dataSyncService.syncData();
    }
}


---

Benefits of Using Spring Data/JdbcTemplate

1. Simplified Configuration and Boilerplate: JDBC setup is handled declaratively.


2. Transaction Management: Spring ensures atomicity across chunks with @Transactional.


3. Dependency Injection: Makes it easier to test and maintain the code.


4. Clean Code: Separates concerns across configuration, repository, service, and main layers.



Would you like me to add more features, such as logging or error handling?

CREATE TABLE #SourceData (
    id INT,
    col1 NVARCHAR(255),
    col2 NVARCHAR(255),
    last_update DATETIME
);

-- Insert source data from Oracle into #SourceData
-- This can be done using JDBC or a bulk insert mechanism.
INSERT INTO #SourceData (id, col1, col2, last_update)
VALUES
    (1, 'Value1', 'Value2', '2024-11-20 10:00:00'),
    (2, 'Value3', 'Value4', '2024-11-20 11:00:00');

WITH SourceCTE AS (
    SELECT id, col1, col2, last_update
    FROM #SourceData
)


MERGE INTO target_table AS target
USING SourceCTE AS source
ON target.id = source.id
WHEN MATCHED THEN
    UPDATE SET 
        target.col1 = source.col1,
        target.col2 = source.col2,
        target.last_update = source.last_update
WHEN NOT MATCHED THEN
    INSERT (id, col1, col2, last_update)
    VALUES (source.id, source.col1, source.col2, source.last_update);

Yes, transforming the source table data into a Common Table Expression (CTE) in SQL Server and then using it in a MERGE statement for an upsert operation is a powerful and efficient approach. You can achieve this by querying the source data and passing it to SQL Server via a staging mechanism or a direct connection (e.g., JDBC).

Here’s how you can implement this:


---

Steps to Transform and Merge Using a CTE:

1. Fetch Source Data: Query the source Oracle table for the records that need to be synchronized (last_update > max_last_update).


2. Prepare the CTE in SQL Server:

Use the fetched data from the source as the basis for the CTE.

This can be done by:

Inserting the data into a staging table in SQL Server, or

Directly embedding the data in the SQL Server query.




3. Merge the CTE with the Target Table:

Use a MERGE statement to insert new records and update existing ones.





---

SQL Server Implementation Example:

Using a Temporary Table or Staging Table

1. Fetch and load the data into a temporary table:

CREATE TABLE #SourceData (
    id INT,
    col1 NVARCHAR(255),
    col2 NVARCHAR(255),
    last_update DATETIME
);

-- Insert source data from Oracle into #SourceData
-- This can be done using JDBC or a bulk insert mechanism.
INSERT INTO #SourceData (id, col1, col2, last_update)
VALUES
    (1, 'Value1', 'Value2', '2024-11-20 10:00:00'),
    (2, 'Value3', 'Value4', '2024-11-20 11:00:00');


2. Define a CTE based on the temporary table:

WITH SourceCTE AS (
    SELECT id, col1, col2, last_update
    FROM #SourceData
)


3. Merge the CTE with the target table:

MERGE INTO target_table AS target
USING SourceCTE AS source
ON target.id = source.id
WHEN MATCHED THEN
    UPDATE SET 
        target.col1 = source.col1,
        target.col2 = source.col2,
        target.last_update = source.last_update
WHEN NOT MATCHED THEN
    INSERT (id, col1, col2, last_update)
    VALUES (source.id, source.col1, source.col2, source.last_update);


4. Clean up:

DROP TABLE #SourceData;




---

Directly Embedding Source Data in a CTE

If the fetched source data is small and can be embedded directly in the SQL query:

WITH SourceCTE AS (
    SELECT *
    FROM (VALUES
        (1, 'Value1', 'Value2', '2024-11-20 10:00:00'),
        (2, 'Value3', 'Value4', '2024-11-20 11:00:00')
    ) AS SourceData (id, col1, col2, last_update)
)
MERGE INTO target_table AS target
USING SourceCTE AS source
ON target.id = source.id
WHEN MATCHED THEN
    UPDATE SET 
        target.col1 = source.col1,
        target.col2 = source.col2,
        target.last_update = source.last_update
WHEN NOT MATCHED THEN
    INSERT (id, col1, col2, last_update)
    VALUES (source.id, source.col1, source.col2, source.last_update);


---

Advantages of Using CTE with MERGE:

1. Readability: The CTE structure makes your SQL query easier to understand and maintain.


2. Performance: CTEs allow you to define reusable datasets, and MERGE ensures efficient upsert operations.


3. Flexibility: Works well for both small datasets (direct embedding) and large datasets (via staging).


4. Transactional Consistency: The MERGE statement is atomic, reducing the risk of partial updates.




---

Key Considerations:

1. Error Handling in MERGE:

Ensure proper handling of potential conflicts, e.g., duplicate keys.

Wrap the MERGE statement in a transaction for rollback capability.



2. Staging Table Management:

Use temporary tables (#TempTable) for transient data or permanent staging tables for larger datasets.



3. Performance Optimization:

Index the target table and #SourceData (or equivalent) on join keys (id).

For large batches, consider batching the MERGE statement itself.





---

Would you like help implementing this in Java, such as generating the CTE dynamically based on fetched data?



To implement this in Java, you can dynamically construct and execute the SQL Server MERGE statement with a CTE based on data fetched from the Oracle source table. Here’s how you can do it:


---

Java Implementation

1. Fetch Data from Oracle

Fetch records from the Oracle source table using JDBC, based on the last_update column:

import java.sql.*;
import java.util.ArrayList;
import java.util.List;

class Record {
    int id;
    String col1;
    String col2;
    Timestamp lastUpdate;

    // Constructor, getters, and setters
    public Record(int id, String col1, String col2, Timestamp lastUpdate) {
        this.id = id;
        this.col1 = col1;
        this.col2 = col2;
        this.lastUpdate = lastUpdate;
    }
}

public List<Record> fetchSourceData(Connection oracleConnection, Timestamp lastUpdate) throws SQLException {
    String query = "SELECT id, col1, col2, last_update FROM source_table WHERE last_update > ?";
    List<Record> records = new ArrayList<>();

    try (PreparedStatement pstmt = oracleConnection.prepareStatement(query)) {
        pstmt.setTimestamp(1, lastUpdate);
        try (ResultSet rs = pstmt.executeQuery()) {
            while (rs.next()) {
                records.add(new Record(
                    rs.getInt("id"),
                    rs.getString("col1"),
                    rs.getString("col2"),
                    rs.getTimestamp("last_update")
                ));
            }
        }
    }

    return records;
}


---

2. Dynamically Construct the CTE and Merge Query

Using the fetched data, dynamically build a SQL MERGE statement with a CTE:

public String generateMergeQuery(List<Record> records) {
    StringBuilder cteBuilder = new StringBuilder("WITH SourceCTE (id, col1, col2, last_update) AS (VALUES ");
    StringBuilder mergeBuilder = new StringBuilder();

    // Build CTE dynamically
    for (int i = 0; i < records.size(); i++) {
        Record record = records.get(i);
        cteBuilder.append("(")
                  .append(record.id).append(", ")
                  .append("'").append(record.col1.replace("'", "''")).append("', ")
                  .append("'").append(record.col2.replace("'", "''")).append("', ")
                  .append("'").append(record.lastUpdate).append("')");
        if (i < records.size() - 1) {
            cteBuilder.append(", ");
        }
    }
    cteBuilder.append(")");

    // Build the MERGE query
    mergeBuilder.append(cteBuilder)
                .append(" MERGE INTO target_table AS target ")
                .append(" USING SourceCTE AS source ")
                .append(" ON target.id = source.id ")
                .append(" WHEN MATCHED THEN ")
                .append(" UPDATE SET ")
                .append(" target.col1 = source.col1, ")
                .append(" target.col2 = source.col2, ")
                .append(" target.last_update = source.last_update ")
                .append(" WHEN NOT MATCHED THEN ")
                .append(" INSERT (id, col1, col2, last_update) ")
                .append(" VALUES (source.id, source.col1, source.col2, source.last_update);");

    return mergeBuilder.toString();
}


---

3. Execute the Query in SQL Server

Send the dynamically generated query to SQL Server via JDBC:

public void executeMergeQuery(Connection sqlServerConnection, String mergeQuery) throws SQLException {
    try (PreparedStatement pstmt = sqlServerConnection.prepareStatement(mergeQuery)) {
        pstmt.executeUpdate();
    }
}


---

4. Putting It All Together

Here’s the complete workflow:

import java.sql.*;
import java.util.List;

public class DataSyncUtility {

    public static void main(String[] args) {
        try (Connection oracleConnection = DriverManager.getConnection("jdbc:oracle:thin:@//host:port/service", "user", "password");
             Connection sqlServerConnection = DriverManager.getConnection("jdbc:sqlserver://host:port;databaseName=yourDB", "user", "password")) {

            // Fetch the latest update timestamp from the target table
            Timestamp maxLastUpdate = fetchMaxLastUpdate(sqlServerConnection);

            // Fetch data from Oracle
            List<Record> sourceRecords = fetchSourceData(oracleConnection, maxLastUpdate);

            if (!sourceRecords.isEmpty()) {
                // Generate the merge query
                String mergeQuery = generateMergeQuery(sourceRecords);

                // Execute the merge query in SQL Server
                executeMergeQuery(sqlServerConnection, mergeQuery);

                System.out.println("Data synchronization complete.");
            } else {
                System.out.println("No new data to synchronize.");
            }

        } catch (SQLException e) {
            e.printStackTrace();
        }
    }

    private static Timestamp fetchMaxLastUpdate(Connection sqlServerConnection) throws SQLException {
        String query = "SELECT MAX(last_update) FROM target_table";
        try (PreparedStatement pstmt = sqlServerConnection.prepareStatement(query);
             ResultSet rs = pstmt.executeQuery()) {
            if (rs.next()) {
                return rs.getTimestamp(1);
            }
        }
        return new Timestamp(0); // Default to epoch if no records exist
    }

    // Include the fetchSourceData, generateMergeQuery, and executeMergeQuery methods here
}


---

Considerations:

1. Sanitize Inputs: Ensure that values like col1 and col2 are properly sanitized to avoid SQL injection.


2. Batch Processing: For large datasets, divide records into batches and execute multiple merge operations.


3. Error Handling: Wrap the operations in a transaction to ensure consistency in case of errors.


4. Logging: Log the synchronization process for monitoring and debugging.



Let me know if you need additional clarification or enhancements!



Here’s how to rewrite the synchronization code using Spring Data and JdbcTemplate for cleaner and more maintainable code.


---

Spring Data/JdbcTemplate Implementation

1. Configuration: Define a Spring configuration for your data sources (Oracle and SQL Server).


2. Repository Layer: Use JdbcTemplate for interacting with the databases.


3. Service Layer: Implement the synchronization logic with transaction management.


4. Main Application: Orchestrate the process.




---

1. Spring Configuration

import org.springframework.context.annotation.Bean;
import org.springframework.context.annotation.Configuration;
import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.jdbc.datasource.DriverManagerDataSource;

import javax.sql.DataSource;

@Configuration
public class DataSourceConfig {

    @Bean
    public DataSource oracleDataSource() {
        DriverManagerDataSource dataSource = new DriverManagerDataSource();
        dataSource.setDriverClassName("oracle.jdbc.driver.OracleDriver");
        dataSource.setUrl("jdbc:oracle:thin:@//host:port/service");
        dataSource.setUsername("oracle_user");
        dataSource.setPassword("oracle_password");
        return dataSource;
    }

    @Bean
    public DataSource sqlServerDataSource() {
        DriverManagerDataSource dataSource = new DriverManagerDataSource();
        dataSource.setDriverClassName("com.microsoft.sqlserver.jdbc.SQLServerDriver");
        dataSource.setUrl("jdbc:sqlserver://host:port;databaseName=yourDB");
        dataSource.setUsername("sqlserver_user");
        dataSource.setPassword("sqlserver_password");
        return dataSource;
    }

    @Bean
    public JdbcTemplate oracleJdbcTemplate(DataSource oracleDataSource) {
        return new JdbcTemplate(oracleDataSource);
    }

    @Bean
    public JdbcTemplate sqlServerJdbcTemplate(DataSource sqlServerDataSource) {
        return new JdbcTemplate(sqlServerDataSource);
    }
}


---

2. Repository Layer

Oracle Repository:

import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Repository;

import java.sql.Timestamp;
import java.util.List;

@Repository
public class OracleRepository {
    private final JdbcTemplate jdbcTemplate;

    public OracleRepository(JdbcTemplate oracleJdbcTemplate) {
        this.jdbcTemplate = oracleJdbcTemplate;
    }

    public List<Record> fetchSourceData(Timestamp lastUpdate) {
        String query = "SELECT id, col1, col2, last_update FROM source_table WHERE last_update > ?";
        return jdbcTemplate.query(query, new Object[]{lastUpdate}, (rs, rowNum) -> 
            new Record(
                rs.getInt("id"),
                rs.getString("col1"),
                rs.getString("col2"),
                rs.getTimestamp("last_update")
            )
        );
    }
}

SQL Server Repository:

import org.springframework.jdbc.core.JdbcTemplate;
import org.springframework.stereotype.Repository;

import java.sql.Timestamp;

@Repository
public class SqlServerRepository {
    private final JdbcTemplate jdbcTemplate;

    public SqlServerRepository(JdbcTemplate sqlServerJdbcTemplate) {
        this.jdbcTemplate = sqlServerJdbcTemplate;
    }

    public Timestamp fetchMaxLastUpdate() {
        String query = "SELECT MAX(last_update) FROM target_table";
        return jdbcTemplate.queryForObject(query, Timestamp.class);
    }

    public void executeMergeQuery(String mergeQuery) {
        jdbcTemplate.execute(mergeQuery);
    }
}


---

3. Service Layer

import org.springframework.stereotype.Service;
import org.springframework.transaction.annotation.Transactional;

import java.sql.Timestamp;
import java.util.List;

@Service
public class DataSyncService {

    private final OracleRepository oracleRepository;
    private final SqlServerRepository sqlServerRepository;

    public DataSyncService(OracleRepository oracleRepository, SqlServerRepository sqlServerRepository) {
        this.oracleRepository = oracleRepository;
        this.sqlServerRepository = sqlServerRepository;
    }

    @Transactional
    public void syncData() {
        // Fetch max last_update from SQL Server
        Timestamp maxLastUpdate = sqlServerRepository.fetchMaxLastUpdate();
        if (maxLastUpdate == null) {
            maxLastUpdate = new Timestamp(0); // Default to epoch
        }

        // Fetch source data from Oracle
        List<Record> sourceRecords = oracleRepository.fetchSourceData(maxLastUpdate);

        // Process records in chunks
        int batchSize = 500;
        for (int i = 0; i < sourceRecords.size(); i += batchSize) {
            List<Record> batch = sourceRecords.subList(i, Math.min(i + batchSize, sourceRecords.size()));

            // Generate the dynamic CTE and execute the MERGE statement
            String mergeQuery = generateMergeQuery(batch);
            sqlServerRepository.executeMergeQuery(mergeQuery);
        }
    }

    private String generateMergeQuery(List<Record> records) {
        StringBuilder cteBuilder = new StringBuilder("WITH SourceCTE (id, col1, col2, last_update) AS (VALUES ");

        for (int i = 0; i < records.size(); i++) {
            Record record = records.get(i);
            cteBuilder.append("(")
                      .append(record.getId()).append(", ")
                      .append("'").append(record.getCol1().replace("'", "''")).append("', ")
                      .append("'").append(record.getCol2().replace("'", "''")).append("', ")
                      .append("'").append(record.getLastUpdate()).append("')");
            if (i < records.size() - 1) {
                cteBuilder.append(", ");
            }
        }
        cteBuilder.append(") ");

        return cteBuilder.append("""
            MERGE INTO target_table AS target
            USING SourceCTE AS source
            ON target.id = source.id
            WHEN MATCHED THEN
                UPDATE SET 
                    target.col1 = source.col1,
                    target.col2 = source.col2,
                    target.last_update = source.last_update
            WHEN NOT MATCHED THEN
                INSERT (id, col1, col2, last_update)
                VALUES (source.id, source.col1, source.col2, source.last_update);
        """).toString();
    }
}


---

4. Main Application

import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;

@SpringBootApplication
public class DataSyncApplication implements CommandLineRunner {

    private final DataSyncService dataSyncService;

    public DataSyncApplication(DataSyncService dataSyncService) {
        this.dataSyncService = dataSyncService;
    }

    public static void main(String[] args) {
        SpringApplication.run(DataSyncApplication.class, args);
    }

    @Override
    public void run(String... args) {
        dataSyncService.syncData();
    }
}


---

Benefits of Using Spring Data/JdbcTemplate

1. Simplified Configuration and Boilerplate: JDBC setup is handled declaratively.


2. Transaction Management: Spring ensures atomicity across chunks with @Transactional.


3. Dependency Injection: Makes it easier to test and maintain the code.


4. Clean Code: Separates concerns across configuration, repository, service, and main layers.



Would you like me to add more features, such as logging or error handling?



-- Step 1: Create the staging table (if not exists)
CREATE TABLE #staging_table (
    id INT,
    col1 NVARCHAR(255),
    col2 NVARCHAR(255),
    last_update DATETIME
);

-- Step 2: Load data into the staging table
INSERT INTO #staging_table (id, col1, col2, last_update)
VALUES (1, 'value1', 'value2', '2024-11-21 10:00:00');

-- Step 3: Perform the MERGE operation
MERGE INTO target_table AS target
USING #staging_table AS source
ON target.id = source.id
WHEN MATCHED THEN
    UPDATE SET 
        target.col1 = source.col1,
        target.col2 = source.col2,
        target.last_update = source.last_update
WHEN NOT MATCHED THEN
    INSERT (id, col1, col2, last_update)
    VALUES (source.id, source.col1, source.col2, source.last_update);

-- Step 4: Truncate or drop the staging table
TRUNCATE TABLE #staging_table;