Exception: Invalid: Cannot Read in Location: Us-west1

This page explains the concept of data location and the different locations where y'all tin can create datasets. To learn how to set the location for your dataset, see Creating datasets.

For information on regional pricing for BigQuery, come across the Pricing page.

Key concepts

Locations or region types

There are two types of locations:

• A region is a specific geographic place, such as London.

• A multi-region is a large geographic area, such every bit the United States, that contains 2 or more geographic places.

Dataset location

You specify a location for storing your BigQuery data when yous create a dataset. After you create the dataset, the location cannot be inverse, but you can copy the dataset to a different location, or manually move (recreate) the dataset in a different location.

BigQuery processes queries in the same location equally the dataset that contains the tables you lot're querying.

BigQuery stores your data in the selected location in accordance with the Service Specific Terms.

Supported regions

BigQuery datasets can exist stored in the following regions and multi-regions. For more than information nigh regions and zones, see Geography and regions.

Regions

The post-obit table lists the regions in the Americas where BigQuery is available.

Region description	Region name	Details
Iowa	u.s.a.-central1	Depression CO2
Las Vegas	the states-west4
Los Angeles	us-west2
Montréal	northamerica-northeast1	Low CO2
Northern Virginia	us-east4
Oregon	us-west1	Low COii
Table salt Lake City	u.s.-west3
São Paulo	southamerica-east1	Low CO2
Santiago	southamerica-west1
South Carolina	united states of america-east1
Toronto	northamerica-northeast2

The following table lists the regions in Asia Pacific where BigQuery is available.

Region description	Region name	Details
Delhi	asia-south2
Hong Kong	asia-east2
Jakarta	asia-southeast2
Melbourne	australia-southeast2
Mumbai	asia-south1
Osaka	asia-northeast2
Seoul	asia-northeast3
Singapore	asia-southeast1
Sydney	australia-southeast1
Taiwan	asia-east1
Tokyo	asia-northeast1

The following tabular array lists the regions in Europe where BigQuery is available.

Region description	Region name	Details
Kingdom of belgium	europe-west1	Low CO2
Finland	europe-north1	Depression COii
Frankfurt	europe-west3
London	europe-west2
Netherlands	europe-west4
Warsaw	europe-central2
Zürich	europe-west6	Low CO2

Multi-regions

The following table lists the multi-regions where BigQuery is available.

Multi-region description	Multi-region name
Data centers within member states of the European Union1	EU
Data centers in the Us	US

¹ Data located in the European union multi-region is not stored in the europe-west2 (London) or europe-west6 (Zürich) information centers.

Specify locations

When loading information, querying data, or exporting data, BigQuery determines the location to run the job based on the datasets referenced in the request. For example, if a query references a tabular array in a dataset stored in the asia-northeast1 region, the query task will run in that region. If a query does not reference any tables or other resources contained within datasets, and no destination table is provided, the query job volition run in the US multi-region. If the project has a flat-charge per unit reservation in a region other than the Usa and the query does not reference whatsoever tables or other resources contained within datasets, then you must explicitly specify the location of the flat-charge per unit reservation when submitting the task.

You can specify the location to run a task explicitly in the following ways:

• When you lot query information using the Deject Console, click More than > Query settings, and for Processing Location, click Motorcar-select and cull your data'due south location.
• When you use the bq command-line tool, supply the --location global flag and fix the value to your location.
• When you use the API, specify your region in the location property in the jobReference section of the job resource.

BigQuery returns an fault if the specified location does not match the location of the datasets in the asking. The location of every dataset involved in the request, including those read from and those written to, must friction match the location of the chore equally inferred or specified.

Single-region locations do not match multi-region locations, even when the single-region location is associated with the multi-region location. Therefore, a job volition always neglect if the fix of associated locations includes both a unmarried-region location and a multi-region location. For case, if a chore's location is set to U.s.a., the job will fail if it references a dataset in us-central1. Likewise, a job that references i dataset in US and another dataset in us-central1 volition neglect.

Location considerations

When you choose a location for your data, consider the following:

• Colocate your BigQuery dataset when using external information sources.
• Cloud Storage: When yous query information in Deject Storage through a BigQuery external table, the data you query must exist in the aforementioned location as your BigQuery dataset, in either a regional or dual-region bucket. For case:
• Unmarried region: If your BigQuery dataset is in the Warsaw (EUROPE-CENTRAL2) regional location, the corresponding Cloud Storage bucket must also be in the Warsaw region because in that location is currently no Cloud Storage dual-region location that includes Warsaw.
• Dual-region: If your BigQuery dataset is in the Tokyo (ASIA-NORTHEAST1) region, the corresponding Cloud Storage bucket must be a bucket in the Tokyo region or the ASIA1 dual-region (which includes Tokyo).
• Multi-region: Considering external query functioning depends on minimal latency and optimal network bandwidth, using multi-region dataset locations with multi-region Cloud Storage buckets is not recommended for external tables.
• Cloud Bigtable: If your external information source is in Cloud Bigtable, your dataset must exist in either the Usa or the Eu multi-regional location. Your Deject Bigtable data must be in one of the supported Cloud Bigtable locations.
• Google Drive: Location considerations do not use to Google Bulldoze external information sources.
• Colocate your Cloud Storage buckets for loading information.
• If your BigQuery dataset is in a multi-regional location, the Cloud Storage bucket containing the data you're loading must be in a regional or multi-regional saucepan in the same location. For example, if your BigQuery dataset is in the EU, the Cloud Storage bucket must exist in a regional or multi-regional bucket in the European union.
• If your dataset is in a regional location, your Deject Storage bucket must be a regional saucepan in the aforementioned location. For example, if your dataset is in the Tokyo region, your Deject Storage bucket must be a regional bucket in Tokyo.
• Exception: If your dataset is in the US multi-regional location, you lot can load data from a Deject Storage bucket in any regional or multi-regional location.
• Colocate your Cloud Storage buckets for exporting data.
• When you lot consign information, the regional or multi-regional Cloud Storage bucket must be in the aforementioned location as the BigQuery dataset. For example, if your BigQuery dataset is in the European union multi-regional location, the Cloud Storage saucepan containing the information you're exporting must be in a regional or multi-regional location in the European union.
• If your dataset is in a regional location, your Deject Storage bucket must be a regional bucket in the same location. For instance, if your dataset is in the Tokyo region, your Cloud Storage bucket must be a regional bucket in Tokyo.
• Exception: If your dataset is in the U.s.a. multi-regional location, you tin can consign data into a Cloud Storage saucepan in any regional or multi-regional location.
• Develop a data management plan.
• If you lot choose a regional storage resource such as a BigQuery dataset or a Cloud Storage bucket, develop a program for geographically managing your data.

For more data on Cloud Storage locations, run into Bucket locations in the Cloud Storage documentation.

Restrict locations

You can restrict the locations in which your datasets tin be created by using the Organization Policy Service. For more than information, see Restricting resource locations and Resource locations supported services.

Dataset security

To control access to datasets in BigQuery, run across Controlling admission to datasets. For information about data encryption, see Encryption at residuum.

Side by side steps

• Learn how to create datasets.
• Learn almost loading data into BigQuery.
• Learn about BigQuery pricing.
• View all the Google Cloud services available in locations worldwide.
• Explore additional location-based concepts, such as zones, that apply to other Google Cloud services.

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Source: https://cloud.google.com/bigquery/docs/locations

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