{
  "id": 12296199,
  "title": "Como aprendi Apache Spark: revisitando uma jornada pela Engenharia de Dados",
  "url": "https://urgent.news/2026/10/06/como-aprendi-apache-spark-revisitando-uma-jornada-pela-engenharia-de",
  "topic": "tech",
  "section": "Tech",
  "published": "2026-10-06T04:05:21.000Z",
  "source": {
    "name": "Dev.to",
    "slug": "dev-to",
    "url": "https://dev.to/renanpyd/como-aprendi-apache-spark-revisitando-uma-jornada-pela-engenharia-de-dados-l5g"
  },
  "original_language": "pt",
  "account": null,
  "summary": "This brief summarizes a personal journey through the evolution of Apache Spark, highlighting the changes and enduring concepts in the field of data engineering. The author, who is a professional in the field, revisits their past materials on Apache Spark to understand what has aged and what remains relevant today. The brief emphasizes that while the APIs and some abstractions have evolved, fundamental concepts like distributed processing, partitioning, transformations, and lazy evaluation continue to be essential. The author also notes that some of the content uses older versions of Spark and APIs that have since been replaced or significantly evolved, and they will clarify these differences by explaining the original functionality, the concept behind it, and the modern approach to the same problem. The piece concludes by acknowledging that legacy code is included to provide historical context, illustrating the journey from Hadoop MapReduce to Spark and the importance of understanding this evolution for modern data engineering practices.",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}