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Google Cloud feature
batch SQL translation
Topic in 1 exam domain
- batch SQL translation · Feature · BigQuery feature
- Batch SQL translation · Feature · BigQuery migration
Also called: batch SQL translation API, batch SQL translator, translator
A tool used to migrate SQL scripts from other dialects to BigQuery in bulk.
Where this appears on the exam
1 objective in 1 of 5 domains
Related topics
FoundationsBuilding blocksBuilding blocksThis topicWorks alongsideApplication Default CredentialsFeatureCloud StorageServiceSensitive Data ProtectionServiceCloud LoggingServiceCloud SQLServiceBigQueryServiceDataflowService
batch SQL translationFeature
interactive SQL translatorFeatureDatastreamServicePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- batch SQL translation depends on Cloud Storage From the official documentation: “If you are performing a batch SQL translation, place the configuration YAML in the same Cloud Storage bucket as the input SQL files.”
- batch SQL translation is part of BigQuery From the official documentation: “This document describes how to use the batch SQL translator in BigQuery to translate scripts written in other SQL dialects into GoogleSQL queries.”
- batch SQL translation works with interactive SQL translator From the official documentation: “You can use the BigQuery interactive SQL translator to review or debug a SQL query using the same metadata or object mapping information as your source database. After you complete a batch translation job, BigQuery generates a translation configuration ID that contains…”
- 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.”
- Dataflow depends on Application Default Credentials From the official documentation: “To authenticate to Dataflow, set up Application Default Credentials.”
- 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 secures Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
- BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
- Cloud Storage works with Datastream From the official documentation: “When you stream to Cloud Storage, Datastream organizes data by object name and timestamp.”
- Application Default Credentials works with Dataflow From the official documentation: “To authenticate to Dataflow, 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.”
- Cloud Storage depends on Application Default Credentials From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Cloud SQL works with Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”
- Application Default Credentials works with Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
- Cloud Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
- Cloud Logging works with Cloud SQL From the official documentation: “Cloud SQL uses Cloud Logging.”
- Application Default Credentials secures Dataflow From the official documentation: “To authenticate to Dataflow, set up Application Default Credentials.”
- 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.”
- Cloud SQL works with Datastream From the official documentation: “This page describes an example NAT VM configuration that lets Datastream privately connect to a Cloud SQL instance.”
- Cloud SQL works with Sensitive Data Protection From the official documentation: “Sensitive Data Protection starts identifying your Cloud SQL instances and creating a default connection for each instance.”
- BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- Application Default Credentials configures Sensitive Data Protection From the official documentation: “To authenticate to Sensitive Data Protection, set up Application Default Credentials.”
- Cloud Logging works with Dataflow From the official documentation: “Information stored in [Cloud Logging](/logging/docs/region-support) is primarily generated by the code in your Dataflow program.”
- Dataflow depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
- Dataflow works with Datastream From the official documentation: “In addition, Datastream supports writing the change event stream into Cloud Storage, and offers streamlined integration with Dataflow templates to build custom workflows for loading data into a wide range of destinations, such as Cloud SQL and Spanner.”
- Dataflow works with Sensitive Data Protection From the official documentation: “Use Dataflow and Sensitive Data Protection to securely tokenize and import data from a relational database to BigQuery.”
- 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 works with Cloud SQL From the official documentation: “Application Default Credentials are part of the client libraries you can use to access Cloud SQL.”
- 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.”
- BigQuery is an alternative to Dataflow From the official documentation: “To automate the EDA process, use BigQuery or a managed data processing service like Dataflow.”
- 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 SQL depends on Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”
- 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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