All BigQuery code samples

BigQuery code samples

Add a column using a load job

Add a new column to a BigQuery table while appending rows using a load job.

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• Modifying table schemas

Add a column using a query job

Add a new column to a BigQuery table while appending rows using a query job with an explicit destination table.

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• Modifying table schemas

Add a label

Add a label to a table.

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• Adding labels to resources
• Updating labels

Add an empty column

Manually add an empty column.

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• Modifying table schemas

Array parameters

Run a query with array parameters.

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• Running parameterized queries

Cancel a job

Attempt to cancel a job.

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• Managing jobs

Check dataset existence

A function to check whether a dataset exists.

Java Python

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• Managing datasets

Clustered table

Load data from a CSV file on Cloud Storage to a clustered table.

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• Creating and using clustered tables

Column-based time partitioning

Create a table that uses column-based time partitioning.

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• Creating and using time-unit column-partitioned tables

Copy a single-source table

Copy a single-source table to a given destination.

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• Managing tables

Copy a table

Copy a table with customer-managed encryption keys.

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• Protecting data with Cloud KMS keys

Copy multiple tables

Copy multiple source tables to a given destination.

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• Managing tables

Create a client with a service account key file

Create a BigQuery client using a service account key file.

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• Authenticating with a service account key file

Create a client with application default credentials

Create a BigQuery client using application default credentials.

Java Node.js PHP Python

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• Getting started with authentication

Create a dataset

Create a dataset within a project.

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• Creating datasets
• Getting started with authentication

Create a dataset

Create an AWS dataset.

Java

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Create a dataset with the BigQuery API

Creates a dataset named my_new_dataset.

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• Getting started with authentication

Create a job

Run a BigQuery job (query, load, extract, or copy) in a specified location with additional configuration.

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• Running jobs programmatically

Create a model

Create a model within an existing dataset.

Java Node.js

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Create a routine

Create a routine within an existing dataset.

Java Node.js Python

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Create a table

Create a table with customer-managed encryption keys.

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• Protecting data with Cloud KMS keys

Create a view

Create a view within a dataset.

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• Creating views

Create a view with DDL

Create a view using a DDL query.

Java Node.js Python

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• Using data definition language statements

Create an authorized view

Create an authorized view using GitHub public data.

Java Node.js Python

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• Creating an authorized view

Create an external table

Create an external AWS table.

Java

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Create an integer-range partitioned table

Create a new integer-range partitioned table in an existing dataset.

Java Node.js Python

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• Creating and using integer range partitioned tables

Create credentials with scopes

Create credentials with Drive and BigQuery API scopes.

Java Python

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• Querying Drive data

Delete a dataset

Delete a dataset from a project.

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• Managing datasets

Delete a dataset and its contents

Delete a dataset and its contents from a project.

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Delete a label from a dataset

Remove a label from a dataset.

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• Deleting labels

Delete a label from a table

Remove a label from a table.

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• Deleting labels

Delete a model

Delete a model from a dataset.

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• Deleting models

Delete a routine

Delete a routine from a dataset.

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Delete a table

Delete a table from a dataset.

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• Managing tables
• Managing views

Disable query cache

Query disables the use of the cache.

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• Using cached query results

Download public table data to DataFrame

Use the BigQuery Storage API to speed up downloads of large tables to DataFrame.

Python

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Download public table data to DataFrame from the sandbox

Use the BigQuery Storage API to download query results to DataFrame.

Python

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Download query results to DataFrame

Get query results as a Pandas DataFrame.

Python

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Dry run query

Run a dry run query.

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• Controlling costs in BigQuery
• Estimating storage and query costs
• Issuing a query dry run

Enable large results

Query enables large result sets using legacy SQL.

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• Writing query results

Export a model

Export an existing model to an existing Cloud Storage bucket.

Java

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• Exporting models

Export a table to a compressed file

Exports a table to a compressed file in a Cloud Storage bucket.

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• Exporting table data

Export a table to a CSV file

Exports a table to a CSV file in a Cloud Storage bucket.

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• Exporting table data

Export a table to a JSON file

Exports a table to a newline-delimited JSON file in a Cloud Storage bucket.

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Export query results

Export query results to an Amazon S3 bucket.

Java

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Get a model

Get a model resource for a given model ID.

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• Getting model metadata

Get a routine

Get a routine resource for a given routine ID.

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Get dataset labels

Retrieve the labels of a dataset for a given dataset ID.

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• Viewing labels

Get dataset properties

Retrieve the properties of a dataset.

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• Getting information about datasets

Get job properties

Retrieve the properties of a job for a given job ID.

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• Managing jobs

Get table labels

Retrieve the labels of a table for a given table ID.

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• Viewing labels

Get table properties

Retrieve the properties of a table for a given table ID.

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• Creating and using tables

Get total rows

Run a query and get total rows.

Java Python

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Get view properties

Retrieve the properties of a view for a given view ID.

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• Getting information about views

Grant view access

Authorize and grant access to a view.

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• Creating authorized views

Import a local file

Import a local file into a table.

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• Batch loading data

Insert rows with no IDs

Insert rows without row IDs in a table.

Java Python

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• Streaming data into BigQuery

List by label

List datasets, filtering by labels.

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• Filtering resources using labels

List datasets

Lists all existing datasets in a project.

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• Listing datasets

List jobs

List all jobs in a project.

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• Managing jobs

List models

Lists all existing models in a dataset.

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• Listing models

List models using streaming

Lists all existing models in the dataset using streaming.

Node.js

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List routines

Lists all existing routines in a dataset.

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List tables

List tables in a given dataset.

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• Creating and using tables
• Listing views

Load a CSV file

Load a CSV file from Cloud Storage using an explicit schema.

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• Loading CSV data from Cloud Storage

Load a CSV file to replace a table

Load a CSV file from Cloud Storage, replacing a table.

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• Loading CSV data from Cloud Storage

Load a CSV file with autodetect schema

Load a CSV file from Cloud Storage using an autodetected schema.

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Load a JSON file

Loads a JSON file from Cloud Storage using an explicit schema.

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• Loading JSON data from Cloud Storage
• Specifying a schema

Load a JSON file to replace a table

Load a JSON file from Cloud Storage, replacing a table.

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• Loading JSON data from Cloud Storage

Load a JSON file with autodetect schema

Load a JSON file from Cloud Storage using autodetect schema.

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• Using schema auto-detection

Load a Parquet file

Load a Parquet file from Cloud Storage into a new table.

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• Loading Parquet data from Cloud Storage

Load a Parquet to replace a table

Load a Parquet file from Cloud Storage, replacing a table.

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• Loading Parquet data from Cloud Storage

Load a table in JSON format

Load a table with customer-managed encryption keys to Cloud Storage in JSON format.

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• Protecting data with Cloud KMS keys

Load an Avro file

Load an Avro file from Cloud Storage into a new table.

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• Loading Avro data from Cloud Storage

Load an Avro file to replace a table

Load an Avro file from Cloud Storage, replacing existing table data.

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• Loading Avro data from Cloud Storage

Load an ORC file

Load an ORC file from Cloud Storage into a new table.

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• Loading ORC data from Cloud Storage

Load an ORC file to replace a table

Load an ORC file from Cloud Storage, replacing a table.

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• Loading ORC data from Cloud Storage

Load data from DataFrame

Load contents of a pandas DataFrame to a table.

Python

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Load data into a column-based time partitioning table

Load data into a table that uses column-based time partitioning.

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• Loading CSV data from Cloud Storage
• Managing partitioned table data

Named parameters

Run a query with named parameters.

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• Running parameterized queries

Named parameters and provided types

Run a query with named parameters and provided parameter types.

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Nested repeated schema

Specify nested and repeated columns in schema.

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• Specifying nested and repeated columns

Positional parameters

Run a query with positional parameters.

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• Running parameterized queries

Positional parameters and provided types

Run a query with positional parameters and provided parameter types.

Java Node.js

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Preview table data

Retrieve selected row data from a table.

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• Managing table data
• Paging through table data

Query a clustered table

Query a table that has a clustering specification.

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• Querying clustered tables

Query a column-based time-partitioned table

Query a table that uses column-based time partitioning.

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Query a table

Query a table with customer-managed encryption keys.

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• Protecting data with Cloud KMS keys

Query an external data source

Query an external data source using a permanent table.

Java

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Query Bigtable using a permanent table

Query data from a Bigtable instance by creating a permanent table.

Java

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• Querying Cloud Bigtable data

Query Bigtable using a temporary table

Query data from a Bigtable instance by creating a temporary table.

Java

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• Querying Cloud Bigtable data

Query Cloud Storage with a permanent table

Query data from a file on Cloud Storage by creating a permanent table.

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• Querying Cloud Storage data

Query Cloud Storage with a temporary table

Query data from a file on Cloud Storage by creating a temporary table.

Java Python

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• Querying Cloud Storage data

Query script

Run a query script.

Java Python

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Query Sheets with a permanent table

Query data from a Google Sheets file by creating a permanent table.

Java Python

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• Querying Drive data

Query Sheets with a temporary table

Query data from a Google Sheets file by creating a temporary table.

Java Python

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• Querying Drive data

Query with the BigQuery API

Create a simple app with BigQuery.

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• Getting started with authentication
• Quickstart: Using client libraries

Read from the BigQuery Storage API

Read data from a table using a read stream.

Java Node.js

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Relax a column

Change columns from required to nullable.

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• Modifying table schemas

Relax a column in a load append job

Change a column from required to nullable in a load append job.

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• Modifying table schemas

Relax a column in a query append job

Change a column from required to nullable in a query append job.

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• Modifying table schemas

Run a query with batch priority

Run a query job using batch priority.

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• Running interactive and batch query jobs

Run a query with legacy SQL

Runs a query with legacy SQL.

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• Switching SQL dialects

Run a query with standard SQL

Run a query with standard SQL.

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• BigQuery API Client Libraries
• Running interactive and batch query jobs
• Switching SQL dialects

Save query results

Query saves results to a permanent table.

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• Creating and using tables
• Writing query results

Set user agent

Set a custom user agent on a BigQuery client.

Node.js

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Streaming insert

Inserts simple rows into a table using the streaming API (insertAll).

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• Streaming data into BigQuery

Streaming insert with complex data types

Insert data of various BigQuery-supported types into a table.

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Struct parameters

Run a query with struct parameters.

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• Running parameterized queries

Table exists

A function to check whether a table exists.

Java Python

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Timestamp parameters

Run a query with timestamp parameters.

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• Running parameterized queries

Undelete

Undelete a table.

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• Managing tables

Update a description

Update the description of an existing dataset resource.

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• Updating dataset properties

Update a label

Update an existing label on a dataset.

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• Adding labels to resources
• Updating labels

Update a materialized view

Use the API to change materialized view properties.

Python

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Update a model description

Update a model's description property for a given model ID.

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• Updating model metadata

Update a routine

Update an existing routine resource.

Java Node.js Python

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Update a table

Update a table with customer-managed encryption keys.

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• Protecting data with Cloud KMS keys

Update a table description

Update a table's description.

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• Managing tables
• Updating view properties

Update a view query

Update a view's query.

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• Updating view properties

Update an expiration time

Update a table's expiration time.

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• Managing tables
• Updating view properties

Update default table expiration times

Updates a dataset's default table expiration times.

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• Updating dataset properties

Update the require partition filter

Update the require partition filter on a table.

Java Python

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• Managing partitioned tables

Write to destination table

Run a query on the natality public dataset and write the results to a destination table.

Python

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BigQuery Connection code samples

Create a Cloud SQL connection

Add credentials to connect BigQuery to Cloud SQL.

Java

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• Cloud SQL federated queries

Create an AWS connection

Add credentials to connect BigQuery to AWS.

Java

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Delete a connection

Remove credentials to an external source from BigQuery.

Java

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• Working with connections

Get connection metadata

Retrieve connection metadata from BigQuery. Credential secrets are not returned.

Java

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• Working with connections

List connections

List all connection metadata in a project.

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• BigQuery Connection API Client Libraries

Share a connection

Set the IAM policy on a connection to share the connection with a user or group.

Java

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• Working with connections

Update connection metadata

Update the metadata for an existing connection.

Java

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• Working with connections

BigQuery Reservation code samples

Report capacity commitments and reservations

List all capacity commitments and reservations in a particular project and location. Print the results to the Cloud Console.

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• BigQuery Reservation API Client Libraries

BigQuery Storage code samples

Download table data in the Arrow data format

Download table data using the Arrow data format and deserialize the data into row objects.

Java

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• BigQuery Storage API Client Libraries

Download table data in the Avro data format

Download table data using the Avro data format and deserialize the data into row objects.

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• BigQuery Storage API Client Libraries