Export and import files in parallel

MySQL | PostgreSQL | SQL Server

This page describes exporting and importing files into Cloud SQL instances in parallel.

Before you begin

Before you begin an export or import operation:

Ensure that your database has adequate free space.

Export and import operations use database resources, but they don't interfere with typical database operations unless the instance is under-provisioned.

Follow the best practices for exporting and importing data.
After completing an import operation, verify the results.

Export data from Cloud SQL for MySQL to multiple files in parallel

The following sections contain information about exporting data from Cloud SQL for MySQL to multiple files in parallel.

Required roles and permissions for exporting data from Cloud SQL for MySQL to multiple files in parallel

To export data from Cloud SQL into Cloud Storage, the user initiating the export must have one of the following roles:

The Cloud SQL Editor role
A custom role, including the following permissions:
- cloudsql.instances.get
- cloudsql.instances.export

Additionally, the service account for the Cloud SQL instance must have one of the following roles:

The storage.objectAdmin Identity and Access Management (IAM) role
A custom role, including the following permissions:
- storage.objects.create
- storage.objects.list (for exporting files in parallel only)
- storage.objects.delete (for exporting files in parallel only)

For help with IAM roles, see Identity and Access Management.

Export data to multiple files in parallel

You can export data in parallel from multiple files that reside in Cloud SQL to Cloud Storage. To do this, use the dumpInstance utility.

After the files are in Cloud Storage, you can import them into another Cloud SQL database. If you want to access the data in the files locally, then download the data from Cloud Storage into your local environment.

If your files contain DEFINER clauses (views, triggers, stored_procedures, and so on), then depending on the order these statements are run, using these files for import can fail. Learn more about DEFINER usage and potential workarounds in Cloud SQL.

gcloud

To export data from Cloud SQL to multiple files in parallel, complete the following steps:

Create a Cloud Storage bucket.
Note: You don't have to create a folder in the bucket. If the folder doesn't exist, then Cloud SQL creates it for you as a part of the process of exporting multiple files in parallel. However, if the folder exists, then it must be empty or the export operation fails.
To find the service account for the Cloud SQL instance that you're exporting files from, use the
gcloud sql instances describe command.
```
gcloud sql instances describe INSTANCE_NAME
```

Replace INSTANCE_NAME with the name of your Cloud SQL instance.

In the output, look for the value that's associated with the serviceAccountEmailAddress field.

To grant the storage.objectAdmin IAM role to the service account, use the gcloud storage buckets add-iam-policy-binding command. For help with setting IAM permissions, see Use IAM permissions.
To export data from Cloud SQL to multiple files in parallel, use the gcloud sql export sql command:
```
gcloud sql export sql INSTANCE_NAME gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME \
--offload \
--parallel \
--threads=THREAD_NUMBER \
--database=DATABASE_NAME \
--table=TABLE_EXPRESSION
```
Make the following replacements:
- INSTANCE_NAME: the name of the Cloud SQL instance from which you're exporting files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the export files are stored.
- FOLDER_NAME: the folder where the export files are stored.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to export files in parallel. For example, if you want to export three files at a time in parallel, then specify 3 as the value for this parameter.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the export is made. If you don't specify any databases, then Cloud SQL exports all databases for the instance.
- TABLE_EXPRESSION: the tables to export from the specified database.
Note: If you want to use serverless exports for up to 2 threads, then use the offload parameter. If you want to export multiple files in parallel, then use the parallel parameter. Otherwise, remove these parameters from the command.

The export sql command doesn't contain triggers or stored procedures, but does contain views. To export triggers or stored procedures, use a single thread for the export. This thread uses the mysqldump tool.

After the export completes, you should have files in a folder in the Cloud Storage bucket in the MySQL Shell dump format.
If you don't need the IAM role that you set in Required roles and permissions for exporting from Cloud SQL for MySQL, then revoke it.

REST v1

To export data from Cloud SQL to multiple files in parallel, complete the following steps:

Create a Cloud Storage bucket:
```
gcloud storage buckets create gs://BUCKET_NAME --project=PROJECT_NAME --location=LOCATION_NAME
```
Make the following replacements:
- BUCKET_NAME: the name of the bucket, subject to naming requirements. For example, my-bucket.
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you're creating.
- LOCATION_NAME: the location of the bucket where you want to store the files you're exporting. For example, us-east1.
Note: You don't have to create a folder in the bucket. If the folder doesn't exist, then Cloud SQL creates it for you as a part of the process of exporting multiple files in parallel. However, if the folder exists, then it must be empty or the export operation fails.
Provide your instance with the legacyBucketWriter IAM role for your bucket. For help with setting IAM permissions, see Use IAM permissions.
Export data from Cloud SQL to multiple files in parallel:

Before using any of the request data, make the following replacements:
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you created.
- INSTANCE_NAME: the name of the Cloud SQL instance from which you're exporting files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the export files are stored.
- FOLDER_NAME: the folder where the export files are stored.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the export is made. If you don't specify any databases, then Cloud SQL exports all databases for the instance.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to export files in parallel. For example, if you want to export three files at a time in parallel, then specify 3 as the value for this parameter.
Note: The offload parameter enables you to use serverless exports for up to 2 threads. The parallel parameter enables you to export multiple files in parallel. To use these features, set the values of these parameters to TRUE. Otherwise, set their values to FALSE.

HTTP method and URL:
```
POST https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/export
```
Request JSON body:
```
{
 "exportContext":
   {
      "fileType": "SQL",
      "uri": "gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME",
      "databases": ["DATABASE_NAME"],
      "offload": [TRUE|FALSE],
      "sqlExportOptions": {
        "parallel": [TRUE|FALSE],
        "threads": [THREAD_NUMBER]
       }
   }
}
```
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/export"
```
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/export" | Select-Object -Expand Content
```
You should receive a JSON response similar to the following:
Response
```
{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/DESTINATION_INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-21T22:43:37.981Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/operations/OPERATION_ID",
  "targetProject": "PROJECT_NAME"
}
```

After the export completes, you should have files in a folder in the Cloud Storage bucket in the MySQL Shell dump format.

If you don't need the IAM role that you set in Required roles and permissions for exporting from Cloud SQL for MySQL, then revoke it.

For the complete list of parameters for the request, see the Cloud SQL Admin API page.

REST v1beta4

To export data from Cloud SQL to multiple files in parallel, complete the following steps:

Create a Cloud Storage bucket:
```
gcloud storage buckets create gs://BUCKET_NAME --project=PROJECT_NAME --location=LOCATION_NAME
```
Make the following replacements:
- BUCKET_NAME: the name of the bucket, subject to naming requirements. For example, my-bucket.
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you're creating.
- LOCATION_NAME: the location of the bucket where you want to store the files you're exporting. For example, us-east1.
Note: You don't have to create a folder in the bucket. If the folder doesn't exist, then Cloud SQL creates it for you as a part of the process of exporting multiple files in parallel. However, if the folder exists, then it must be empty or the export operation fails.
Provide your instance with the storage.objectAdmin IAM role for your bucket. For help with setting IAM permissions, see Use IAM permissions.
Export data from Cloud SQL to multiple files in parallel:

Before using any of the request data, make the following replacements:
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you created.
- INSTANCE_NAME: the name of the Cloud SQL instance from which you're exporting files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the export files are stored.
- FOLDER_NAME: the folder where the export files are stored.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the export is made. If you don't specify any databases, then Cloud SQL exports all databases for the instance.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to export files in parallel. For example, if you want to export three files at a time in parallel, then specify 3 as the value for this parameter.
Note: The offload parameter enables you to use serverless exports for up to 2 threads. The parallel parameter enables you to export multiple files in parallel. To use these features, set the values of these parameters to TRUE. Otherwise, set their values to FALSE.

HTTP method and URL:
```
POST https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/export
```
Request JSON body:
```
{
 "exportContext":
   {
      "fileType": "SQL",
      "uri": "gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME",
      "databases": ["DATABASE_NAME"],
      "offload": [TRUE|FALSE],
      "sqlExportOptions": {
        "parallel": [TRUE|FALSE],
        "threads": [THREAD_NUMBER]
       }
   }
}
```
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/export"
```
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/export" | Select-Object -Expand Content
```
You should receive a JSON response similar to the following:
Response
```
{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/DESTINATION_INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-21T22:43:37.981Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/operations/OPERATION_ID",
  "targetProject": "PROJECT_NAME"
}
```

After the export completes, you should have files in a folder in the Cloud Storage bucket in the MySQL Shell dump format.

If you don't need the IAM role that you set in Required roles and permissions for exporting from Cloud SQL for MySQL, then revoke it.

For the complete list of parameters for the request, see the Cloud SQL Admin API page.

Import data from multiple files in parallel to Cloud SQL for MySQL

The following sections contain information about importing data from multiple files in parallel to Cloud SQL for MySQL.

Required roles and permissions for importing data from multiple files in parallel to Cloud SQL for MySQL

To import data from Cloud Storage into Cloud SQL, the user initiating the import must have one of the following roles:

The Cloud SQL Admin role
A custom role, including the following permissions:
- cloudsql.instances.get
- cloudsql.instances.import

Additionally, the service account for the Cloud SQL instance must have one of the following roles:

The storage.objectAdmin IAM role
A custom role, including the following permissions:
- storage.objects.get
- storage.objects.list (for importing files in parallel only)

For help with IAM roles, see Identity and Access Management.

Import data to Cloud SQL for MySQL

You can import data in parallel from multiple files that reside in Cloud Storage to your database. To do this, use the loadDump utility.

gcloud

To import data from multiple files in parallel into Cloud SQL, complete the following steps:

Create a Cloud Storage bucket.
Upload the files to your bucket.

Note: Make sure that the files that you're uploading are in the MySQL Shell dump format. For more information, see Export data from multiple files in parallel.

For help with uploading files to buckets, see Upload objects from files.
To find the service account for the Cloud SQL instance that you're importing files to, use the
gcloud sql instances describe command.
```
gcloud sql instances describe INSTANCE_NAME
```

Replace INSTANCE_NAME with the name of your Cloud SQL instance.

In the output, look for the value that's associated with the serviceAccountEmailAddress field.

To grant the storage.objectAdmin IAM role to the service account, use the gcloud storage buckets add-iam-policy-binding utility. For help with setting IAM permissions, see Use IAM permissions.
To import data from multiple files in parallel into Cloud SQL, use the gcloud sql import sql command:
```
gcloud sql import sql INSTANCE_NAME gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME \
--offload \
--parallel \ 
--threads=THREAD_NUMBER \
--database=DATABASE_NAME
```
Make the following replacements:
- INSTANCE_NAME: the name of the Cloud SQL instance to which you're importing files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the import files are stored.
- FOLDER_NAME: the folder where the import files are stored.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to import files in parallel. For example, if you want to import three files at a time in parallel, then specify 3 as the value for this parameter.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the import is made. If you don't specify any databases, then Cloud SQL imports all databases for the instance.
Note: If you want to use serverless imports for up to 2 threads, then use the offload parameter. If you want to import multiple files in parallel, then use the parallel parameter.

Otherwise, remove these parameters from the command.

If the command returns an error like ERROR_RDBMS, then review the permissions; this error is often due to permissions issues.
If you don't need the IAM permissions that you set in Required roles and permissions for importing to Cloud SQL for MySQL, then use gcloud storage buckets remove-iam-policy-binding to remove them.

REST v1

To import data from multiple files in parallel into Cloud SQL, complete the following steps:

Create a Cloud Storage bucket:
```
gcloud storage buckets create gs://BUCKET_NAME --project=PROJECT_NAME --location=LOCATION_NAME
```
Make the following replacements:
- BUCKET_NAME: the name of the bucket, subject to naming requirements. For example, my-bucket.
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you're creating.
- LOCATION_NAME: the location of the bucket where you want to store the files you're importing. For example, us-east1.
Upload the files to your bucket.

Note: Make sure that the files that you're uploading are in the MySQL Shell dump format. For more information, see Export data from multiple files in parallel.

For help with uploading files to buckets, see Upload objects from files.
Provide your instance with the storage.objectAdmin IAM role for your bucket. For help with setting IAM permissions, see Use IAM permissions.
Import data from multiple files in parallel into Cloud SQL:

Before using any of the request data, make the following replacements:
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you created.
- INSTANCE_NAME: the name of the Cloud SQL instance to which you're importing files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the import files are stored.
- FOLDER_NAME: the folder where the import files are stored.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the import is made. If you don't specify any databases, then Cloud SQL imports all databases for the instance.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to import files in parallel. For example, if you want to import three files at a time in parallel, then specify 3 as the value for this parameter.
Note: The offload parameter enables you to use serverless imports for up to 2 threads. The parallel parameter enables you to import multiple files in parallel.

To use these features, set the values of these parameters to TRUE. Otherwise, set their values to FALSE.

HTTP method and URL:
```
POST https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/import
```
Request JSON body:
```
{
 "importContext":
   {
      "fileType": "SQL",
      "uri": "gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME",
      "databases": ["DATABASE_NAME"],
      "offload": [TRUE|FALSE],
      "sqlImportOptions": {
        "parallel": [TRUE|FALSE],
        "threads": [THREAD_NUMBER]
       }
   }
}
```
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/import"
```
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/INSTANCE_NAME/import" | Select-Object -Expand Content
```
You should receive a JSON response similar to the following:
Response
```
{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/instances/DESTINATION_INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-21T22:43:37.981Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/v1/projects/PROJECT_NAME/operations/OPERATION_ID",
  "targetProject": "PROJECT_NAME"
}
```
For the complete list of parameters for the request, see the Cloud SQL Admin API page.
If you don't need the IAM permissions that you set in Required roles and permissions for importing to Cloud SQL for MySQL, then use gcloud storage buckets remove-iam-policy-binding to remove them.

REST v1beta4

To import data from multiple files in parallel into Cloud SQL, complete the following steps:

Create a Cloud Storage bucket:
```
gcloud storage buckets create gs://BUCKET_NAME --project=PROJECT_NAME --location=LOCATION_NAME
```
Make the following replacements:
- BUCKET_NAME: the name of the bucket, subject to naming requirements. For example, my-bucket.
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you're creating.
- LOCATION_NAME: the location of the bucket where you want to store the files you're importing. For example, us-east1.
Upload the files to your bucket.

Note: Make sure that the files that you're uploading are in the MySQL Shell dump format. For more information, see Export data from multiple files in parallel.

For help with uploading files to buckets, see Upload objects from files.
Provide your instance with the storage.objectAdmin IAM role for your bucket. For help with setting IAM permissions, see Use IAM permissions.
Import data from multiple files in parallel into Cloud SQL:

Before using any of the request data, make the following replacements:
- PROJECT_NAME: the name of the Google Cloud project that contains the Cloud Storage bucket you created.
- INSTANCE_NAME: the name of the Cloud SQL instance from which you're importing files in parallel.
- BUCKET_NAME: the name of the Cloud Storage bucket.
- BUCKET_PATH: the path to the bucket where the import files are stored.
- FOLDER_NAME: the folder where the import files are stored.
- DATABASE_NAME (optional): the name of the databases inside of the Cloud SQL instance from which the import is made. If you don't specify any databases, then Cloud SQL imports all databases for the instance.
- THREAD_NUMBER: the number of threads that Cloud SQL uses to import files in parallel. For example, if you want to import three files at a time in parallel, then specify 3 as the value for this parameter.
Note: The offload parameter enables you to use serverless imports for up to 2 threads. The parallel parameter enables you to import multiple files in parallel.

To use these features, set the values of these parameters to TRUE. Otherwise, set their values to FALSE.

HTTP method and URL:
```
POST https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/import
```
Request JSON body:
```
{
  "importContext":
    {
       "fileType": "SQL",
       "uri": "gs://BUCKET_NAME/BUCKET_PATH/FOLDER_NAME",
       "databases": ["DATABASE_NAME"],
       "offload": [TRUE|FALSE],
       "sqlImportOptions": {
         "parallel": [TRUE|FALSE],
         "threads": [THREAD_NUMBER]
        }
    }
 }
 
```
To send your request, expand one of these options:
curl (Linux, macOS, or Cloud Shell)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login , or by using Cloud Shell, which automatically logs you into the gcloud CLI . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
curl -X POST \
     -H "Authorization: Bearer $(gcloud auth print-access-token)" \
     -H "Content-Type: application/json; charset=utf-8" \
     -d @request.json \
     "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/import"
```
PowerShell (Windows)

Note: The following command assumes that you have logged in to the gcloud CLI with your user account by running gcloud init or gcloud auth login . You can check the currently active account by running gcloud auth list.

Save the request body in a file named request.json, and execute the following command:
```
$cred = gcloud auth print-access-token
$headers = @{ "Authorization" = "Bearer $cred" }

Invoke-WebRequest `
    -Method POST `
    -Headers $headers `
    -ContentType: "application/json; charset=utf-8" `
    -InFile request.json `
    -Uri "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/INSTANCE_NAME/import" | Select-Object -Expand Content
```
You should receive a JSON response similar to the following:
Response
```
{
  "kind": "sql#operation",
  "targetLink": "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/instances/DESTINATION_INSTANCE_NAME",
  "status": "PENDING",
  "user": "user@example.com",
  "insertTime": "2020-01-21T22:43:37.981Z",
  "operationType": "UPDATE",
  "name": "OPERATION_ID",
  "targetId": "INSTANCE_NAME",
  "selfLink": "https://sqladmin.googleapis.com/sql/v1beta4/projects/PROJECT_NAME/operations/OPERATION_ID",
  "targetProject": "PROJECT_NAME"
}
```
For the complete list of parameters for the request, see the Cloud SQL Admin API page.
If you don't need the IAM permissions that you set in Required roles and permissions for importing to Cloud SQL for MySQL, then use gcloud storage buckets remove-iam-policy-binding to remove them.

Limitations

If you specify too many threads when you import or export data from multiple files in parallel, then you might use more memory than your Cloud SQL instance has. If this occurs, then an internal error message appears. Check the memory usage of your instance and increase the instance's size, as needed. For more information, see About instance settings.
When performing an export, commas in database names or table names in the databases or tables fields aren't supported.
Make sure that you have enough disk space for the initial dump file download. Otherwise, a no space left on disk error appears.
If your instance has only one virtual CPU (vCPU), then you can't import or export multiple files in parallel. The number of vCPUs for your instance can't be smaller than the number of threads that you're using for the import or export operation, and the number of threads must be at least two.
If you write data definition language (DDL) statements such as CREATE, DROP, or ALTER during an export operation, then the operation might fail or the exported data might be inconsistent with the point-in-time recovery snapshot.
If an import operation fails, then you might have partially imported data remaining. For DDL statements, MySQL commits automatically. If this occurs, then before you import the data again, clean up the partial data.

What's next

Learn how to check the status of import and export operations.
Learn how to cancel the import and export of data.
Learn about best practices for importing and exporting data.
Learn about known issues for imports and exports.

Export and import files in parallel

Before you begin

Export data from Cloud SQL for MySQL to multiple files in parallel

Required roles and permissions for exporting data from Cloud SQL for MySQL to multiple files in parallel

Export data to multiple files in parallel

gcloud

REST v1

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

Response

REST v1beta4

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

Response

Import data from multiple files in parallel to Cloud SQL for MySQL

Required roles and permissions for importing data from multiple files in parallel to Cloud SQL for MySQL

Import data to Cloud SQL for MySQL

gcloud

REST v1

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

Response

REST v1beta4

curl (Linux, macOS, or Cloud Shell)

PowerShell (Windows)

Response

Limitations

What's next