{"version":"1.0","type":"rich","provider_name":"techandbusiness.org","provider_url":"https://techandbusiness.org","title":"Databricks benchmark finds early pipeline checks reduce wasted compute","author_name":"techandbusiness.org · AI, Infrastructure","thumbnail_url":"https://www.databricks.com/sites/default/files/2026-10/2026-10-Blog-Built-for-Agents-The-Case-for-Spark-Declarative-Pipelines-OG-1200x628-2x.png","width":600,"height":400,"html":"<blockquote class=\"tb-newswire-embed\" style=\"max-width:600px;border-left:3px solid #22d3ee;padding:12px 16px;margin:0;font-family:-apple-system,system-ui,sans-serif;background:#09090b;border-radius:0 8px 8px 0;\">\n      <p style=\"margin:0 0 8px;font-size:10px;font-weight:600;letter-spacing:0.1em;color:#71717a;\">techandbusiness.org · AI, Infrastructure</p>\n      <p style=\"margin:0 0 8px;font-size:18px;font-weight:700;line-height:1.3;color:#fff;\"><a href=\"https://techandbusiness.org/newswire/e2tNbPgLPgNTXbxhi6Ww3k\" style=\"color:#fff;text-decoration:none;\">Databricks benchmark finds early pipeline checks reduce wasted compute</a></p>\n      <p style=\"margin:0;font-size:14px;color:#a1a1aa;line-height:1.5;\">Databricks says its benchmark of agent-written data pipelines used 17 executor-seconds with Spark Declarative Pipelines, compared with 596 for procedural PySpark. The test covered 22 tasks and 264 bui...</p>\n    </blockquote>"}