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Spark

AI-POWERED SPARK APPLICATION TROUBLESHOOTING AND TUNING

Unravel makes Spark perform better and more reliably. Unravel's Spark application tuning tool complements Spark web UI and automatically troubleshoots and tunes your Spark jobs. Avoid errors, slowdowns, and costly resource usage. Unravel provides deep insights and intelligence for Spark pipelines and jobs running on Databricks, Amazon EMR, Cloudera, Google Dataproc, Azure HDInsight and Apache open source Spark versions.

Unravel delivers peak performance, reliability, and cost optimization for your Spark data pipelines.

The Unravel application for Spark tuning provides a comprehensive full-stack, intelligent, and automated approach to Spark operations and performance management on your modern data architecture. The Unravel platform helps you analyze, troubleshoot, and optimize Spark queries, applications, and pipelines within a seamless, intuitive user experience.

Run Spark like a boss with a tool that’s more than just a Spark apm.

Less time troubleshooting and tuning Spark applications; more time for everything else.

Unravel’s platform is so much more than just a Spark apm tool. It uses advanced analytical techniques, machine learning models, and a built-in AI engine to provide insights, recommendations, and auto-tuning for Spark applications and pipelines. Unravel enables:

  • Automatic root cause analysis (RCA), with detailed explanations telling you what happened, and why.
  • Recommendations and tweaks to get your Spark jobs running at optimal levels.
  • Auto-tuning and fixes to speed up jobs and get rid of errors, reducing resource consumption and cost.

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Get wide and deep

End-to-end Spark observability means you don’t miss anything.

Unravel automatically links your Spark jobs to the pipeline that they run under. Unravel also connects other services, data sources, containers, and hosts, giving you end-to-end observability. This allows you to:

  • See how other services such as Ingestion, NoSQL, Data Warehousing, etc. interact with your Spark code end-to-end.
  • Drill down into bottlenecks, slowdowns, failures, resource consumption, and data usage.
  • Get actionable insights into misconfiguration, parallelism, partitioning, garbage collection, RDD caching, resource contention, container resource utilization, and more.

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Supercharge your data environment

Unravel is easy to set up and integrates with all your favorite tools.

Unravel works with all your Spark code – Java, Scala, R, Python – Spark Streaming, SparkSQL, MLib, and GraphX:

  • Unravel also optimizes the rest of your data stack, including Kafka, Presto, NoSQL databases, Hadoop, BigQuery and more.
  • Integrates with all notebooks and orchestrators.
  • Works seamlessly with your favorite work tools, like Slack, Pagerduty, JIRA and more.
  • Connects to your Spark environment with a few clicks using Unravel SaaS or the AWS, Azure, and Google cloud marketplaces.

CONNECT UNRAVEL TO YOUR SPARK JOBS NOW

Diagram: Unravel integrations

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Uncover what is crippling your Spark data pipelines.

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