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Part 15: Enterprise Date & Time Best Practices – Java, Spring Boot, Oracle, JPA, REST APIs, and Microservices

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction In the previous article, we explored every major class in the Java 8 Date & Time API and learned the purpose of classes such as LocalDate, LocalTime, LocalDateTime, Instant,…

  • java
  • JavaEvolutionSeries
  • programming

Part 14: Understanding Every Java Date & Time Class – Choosing the Right Type for Every Situation

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction In the previous article, we explored why Java replaced the legacy Date and Calendar APIs with the modern Java Date & Time API (JSR-310). We learned about the shortcomings…

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  • JavaEvolutionSeries
  • programming

Part 13: Java Date & Time API (JSR-310) – Building Time-Safe Enterprise Applications

  • Rahul Mittal
  • July 4, 2026
  • 6 min read

Introduction Ask any experienced Java developer about the most frustrating APIs in Java before version 8, and one answer appears almost every time: Date and Time handling. For nearly two…

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  • JavaEvolutionSeries
  • programming

Part 12: Parallel Streams and Spliterator – Understanding How the Stream API Executes Work

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction One of the most impressive capabilities introduced in Java 8 was the ability to process collections in parallel with almost no changes to application code. Changing this: employees.stream() to…

  • java
  • JavaEvolutionSeries
  • programming

Part 12: Parallel Streams and Spliterator – Understanding How the Stream API Executes Work

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction One of the most impressive capabilities introduced in Java 8 was the ability to process collections in parallel with almost no changes to application code. Changing this: employees.stream() to…

  • java
  • JavaEvolutionSeries
  • programming

Part 11: Custom Collectors – Building Your Own Aggregation Engine

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction Throughout this Stream API series, we've used many built-in collectors: toList() toSet() groupingBy() partitioningBy() mapping() joining() counting() summingInt() averagingDouble() maxBy() minBy() These collectors solve most day-to-day programming problems. But…

  • java
  • JavaEvolutionSeries
  • programming

Part 10: Collectors.partitioningBy() – Splitting Data into Two Logical Groups

  • Rahul Mittal
  • July 4, 2026
  • 6 min read

Introduction In the previous articles, we explored Collectors.groupingBy() and discovered how it can transform large collections into meaningful reports, dashboards, and analytical summaries. groupingBy() is ideal when data needs to…

  • java
  • JavaEvolutionSeries
  • programming

Part 9: Downstream Collectors – Building Enterprise Reports with groupingBy()

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction In the previous article, we explored Collectors.groupingBy() and learned how to group Stream elements into logical categories such as departments, cities, and transaction dates. While grouping data is useful,…

  • java
  • JavaEvolutionSeries
  • programming

Part 8: Mastering Collectors.groupingBy() – Building Enterprise Reports and Dashboards

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction In the previous article, we learned that Collectors provide the aggregation engine for the Stream API. We explored how they accumulate Stream elements into collections, maps, and other complex…

  • java
  • JavaEvolutionSeries
  • programming

Part 7: Understanding Collectors – The Backbone of Stream Aggregation

  • Rahul Mittal
  • July 4, 2026
  • 7 min read

Introduction So far in this series, we've learned how to: Build Stream pipelines. Filter data. Transform objects. Flatten nested collections. Sort results. Execute pipelines using terminal operations. These capabilities are…

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