namespace

Related topics

• namespace is part of Cloud Data Fusion From the official documentation: “RBAC provides namespace-level isolation within a single Cloud Data Fusion instance.”
• namespace is part of Lakehouse runtime catalog From the official documentation: “Creating a namespace in a catalog (such as an Apache Iceberg REST catalog or Apache Hive catalog) helps you organize your tables within the *Lakehouse runtime catalog*.”
• BigQuery works with Lakehouse runtime catalog From the official documentation: “When querying Lakehouse runtime catalog tables from BigQuery, you use a four-part naming structure, often referred to as **P.C.N.T**:”
• Cloud Data Fusion works with Managed Service for Apache Spark From the official documentation: “Deployed Cloud Data Fusion pipelines run on Managed Service for Apache Spark clusters by default.”
• BigQuery works with Managed Service for Apache Spark From the official documentation: “This means you can quickly read and write BigQuery data to and from Managed Service for Apache Spark.”
• Lakehouse runtime catalog works with Managed Service for Apache Spark From the official documentation: “Managed Service for Apache Spark supports only PySpark jobs with borderless Lakehouse Metastore.”
• BigQuery is an alternative to Managed Service for Apache Spark From the official documentation: “Run queries against your federated data using BigQuery or Managed Service for Apache Spark.”
• BigQuery works with Cloud Data Fusion From the official documentation: “Cloud Data Fusion pulls data from the storage bucket and writes it to BigQuery.”
• BigQuery depends on Lakehouse runtime catalog From the official documentation: “BigQuery federates queries to these endpoints using the Google Cloud Lakehouse runtime catalog connection.”
• Cloud Data Fusion depends on Managed Service for Apache Spark From the official documentation: “Cloud Data Fusion uses Managed Service for Apache Spark as the execution environment for pipelines.”