Optimizing Multithreaded Data Insertion into SAP Data Lake: Seeking Guidance and Best Practices

[Cosmin1]

I am working on a project where I need to insert data into SAP Data Lake using a multithreaded Java application. This application uses JDBC to batch-insert log entries into a specific table in the Data Lake. My goal is to optimize the performance of these batch inserts, ensuring that resources are used efficiently while minimizing errors or conflicts, such as constraint violations.

Technical Implementation:

1. Multithreaded Design:

   • The application uses an ExecutorService to manage multiple threads that execute batch insert operations concurrently. Each thread runs a Callable task that establishes a database connection and performs the batch insert.
   • To prevent conflicts between threads during data insertion, I use table-level locking (LOCK TABLE ... IN EXCLUSIVE MODE). I also manage transactions manually to ensure that batches are either fully committed or rolled back in case of errors.

2. Metrics and Logging:

   • I’ve implemented detailed logging to capture task execution details, including thread name, group, and processing time.
   • After all threads have completed their tasks, I execute a summary SQL query to count the number of entries inserted since the start of the current run, using a timestamp filter.
   • I also calculate statistics, such as the number of entries inserted per second by each thread, to assess individual thread performance.

3. SQL Operations:

   • The application includes SQL statements to retrieve distinct entries based on a specific index column and to count the number of occurrences for each index.
   • I run a summary query post-execution to determine the total number of entries inserted during the current application run.

Challenges Encountered:

• Performance Considerations: While the application performs as expected, I want to evaluate its efficiency, particularly in terms of processing time, resource utilization, and its ability to handle large-scale data inserts.

Questions for the SAP Data Lake Team:

1. Best Practices for Locking and Concurrency:

   • Is my current approach of using LOCK TABLE ... IN EXCLUSIVE MODE for handling concurrent inserts considered best practice in SAP Data Lake? Are there more efficient methods or alternatives that you would recommend?

2. Optimizing Batch Size and Retry Logic:

   • What batch sizes and retry mechanisms do you recommend in SAP Data Lake to enhance performance and reduce error rates?

3. Connection Management:

   • Does the SAP Data Lake JDBC driver support connection pooling, and how should I configure it to optimize performance?

4. Performance of SQL Queries:

   • Are there specific indexes or other optimizations I should apply to the table to improve the performance of counting and filtering operations, especially given the high volume of data being inserted?

5. Recommended Isolation Levels:

   • Considering the use of transactions, what isolation level would you recommend to balance performance and data integrity in SAP Data Lake?

6. Logging and Monitoring:

   • What tools or practices do you recommend for monitoring and logging the performance of batch inserts?

7. Threading Model Optimization:

   • Do you have any advice on optimizing the threading model, possibly using SAP Data Lake-specific features or configurations, to improve the performance of the application?

Request for Guidance:

I am seeking advice on the best approach to test the performance of SAP Data Lake. I would appreciate recommendations on how to conduct effective performance testing and whether my current approach aligns with best practices. Any guidance on improving my implementation would be invaluable, especially insights into potential pitfalls and optimization strategies.