Build and operate the data processing systems behind analytics and ML on Google Cloud, including BigQuery, Dataflow, and Pub/Sub, and track your readiness for the Professional Data Engineer exam.
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Google Cloud feature
clustered tables
Topic in 9 exam domains
Also called: BigQuery clustering, clustering
Tables organized by clustering frequently used columns to minimize the data scanned during queries.
Where this appears on the exam
6 objectives in 3 of 5 domains
~22% of exam
Domain 3
Storing the data~20% of exam
~15% of exam
Related topics
FoundationsBuilding blocksBuilding blocksThis topicWorks alongsideApplication Default CredentialsFeatureSpannerServiceBigtableServiceCloud StorageServiceSensitive Data ProtectionServiceCloud LoggingServiceGoogleSQLFeatureBigQueryService
clustered tablesFeature
partitioned tablesFeatureDatastreamServicePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- clustered tables is part of BigQuery From the official documentation: “BigQuery supports clustering for both partitioned and non-partitioned tables.”
- Cloud Storage works with clustered tables From the official documentation: “Load data from a CSV file on Cloud Storage to a clustered table.”
- clustered tables depends on GoogleSQL From the official documentation: “Only GoogleSQL is supported for querying clustered tables and for writing query results to clustered tables.”
- clustered tables works with partitioned tables From the official documentation: “You can combine table clustering with [table partitioning](/bigquery/docs/partitioned-tables) to achieve finely-grained sorting for further query optimization.”
- clustered tables is an alternative to partitioned tables From the official documentation: “If you exceed<br>this limit, consider using [clustering](/bigquery/docs/clustered-tables) in addition to, or instead of, partitioning.”
- Application Default Credentials works with Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Sensitive Data Protection depends on Application Default Credentials From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- Application Default Credentials secures BigQuery From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
- BigQuery depends on Application Default Credentials From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
- BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
- BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
- BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
- Application Default Credentials works with BigQuery From the official documentation: “Create a BigQuery client using application default credentials.”
- BigQuery works with Datastream From the official documentation: “Permissions needed for datastream to write to BigQuery.”
- Application Default Credentials works with Bigtable From the official documentation: “To authenticate to Bigtable, set up Application Default Credentials.”
- Application Default Credentials secures Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- Application Default Credentials secures Bigtable From the official documentation: “To authenticate to Bigtable, set up Application Default Credentials.”
- Cloud Storage works with Datastream From the official documentation: “When you stream to Cloud Storage, Datastream organizes data by object name and timestamp.”
- Bigtable depends on Application Default Credentials From the official documentation: “To authenticate to Bigtable, set up Application Default Credentials.”
- Application Default Credentials secures Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Application Default Credentials secures Spanner From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- Cloud Storage depends on Application Default Credentials From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Application Default Credentials works with Spanner From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- Spanner depends on Application Default Credentials From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- BigQuery works with Bigtable From the official documentation: “External BigQuery data source backed by Bigtable”
- Application Default Credentials works with Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- BigQuery works with Spanner From the official documentation: “Reverse ETL (BigQuery to Spanner)”
- Cloud Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
- partitioned tables is part of BigQuery From the official documentation: “There are two types of partitioned tables in BigQuery:”
- Cloud Logging depends on Application Default Credentials From the official documentation: “To authenticate to Logging, set up Application Default Credentials.”
- Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
- BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- Datastream works with Spanner From the official documentation: “Learn how Datastream ingests data from [Spanner](/datastream/docs/sources-spanner).”
- Application Default Credentials configures Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- BigQuery works with GoogleSQL From the official documentation: “GoogleSQL is a query language used by multiple Google Cloud services, including Spanner and BigQuery.”
- Bigtable is an alternative to Cloud Storage From the official documentation: “If the joining data is in the gigabyte or terabyte range, use either Bigtable or Cloud Storage to merge the joining data to the driving data, depending on the nature of the data.”
- GoogleSQL is part of Spanner From the official documentation: “When creating a Spanner database, you can choose between two SQL dialects: GoogleSQL and PostgreSQL.”
- Application Default Credentials configures BigQuery From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
- Application Default Credentials works with Cloud Logging From the official documentation: “To authenticate to Logging, set up Application Default Credentials.”
- Application Default Credentials configures Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials. For more information, see [Set up authentication for client libraries](/storage/docs/authentication#client-libs).”
- BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
- Bigtable works with Cloud Logging From the official documentation: “You can audit the requests that Bigtable sends to Cloud KMS on your behalf in [Cloud Logging](/kms/docs/audit-logging), if you have [enabled Cloud KMS audit logs](/logging/docs/audit/configure-data-access#config-console-enable) for the Cloud KMS API in your project.”
- Bigtable works with Cloud Storage From the official documentation: “Another way you can back up Bigtable is to use a managed data export to Cloud Storage.”
- Bigtable works with GoogleSQL From the official documentation: “**GoogleSQL**: a query language used by multiple Google Cloud services, including Spanner, BigQuery, and Bigtable.”
- Cloud Logging is an alternative to Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs either in Cloud Logging or in a user-created Cloud Storage bucket.”
- Cloud Logging works with Spanner From the official documentation: “Both Spanner and Agent Platform provide monitoring dashboards and write logs to Cloud Logging, which can contain additional details.”
- Cloud Storage works with Spanner From the official documentation: “Move Spanner databases to and from Avro or CSV files stored in Cloud Storage.”
- Datastream works with partitioned tables From the official documentation: “Datastream supports replicating partitioned tables for PostgreSQL source databases.”
- GoogleSQL works with Spanner From the official documentation: “GoogleSQL is a query language used by multiple Google Cloud services, including Spanner and BigQuery.”
- Sensitive Data Protection secures BigQuery From the official documentation: “To help meet compliance requirements, use Sensitive Data Protection to inspect your BigQuery tables and to help protect your sensitive data.”
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