Enhancements to Managed Service for Apache Spark clusters
At Google Cloud, our goal is to let you run large-scale analytical and data science workloads with maximum efficiency so you can process big data pipelines, machine learning, and ETL tasks.
We recently announced that the Dataproc service is now Managed Service for Apache Spark, reflecting our deep integration with the Agentic Data Cloud.
To support the diverse architectural needs of today’s modern data teams, we offer the service in two distinct deployment modes: serverless and managed clusters. The serverless deployment mode completely abstracts infrastructure management for ephemeral or ad-hoc jobs, while the managed clusters deployment mode is designed for teams that require fine-grained infrastructure customization, persistent environments, long-running stateful processing, or native integration with custom Compute Engine hardware configurations.
When it comes to managed cluster deployments, we’ve re-imagined the experience from the ground up, focusing on three core pillars: making Spark faster by supercharging execution speeds, easier...
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