The IMPORT INTO statement imports CSV data into an existing table. IMPORT INTO appends new rows onto the table.

Considerations

  • IMPORT INTO only works for existing tables. For information on how to import data into new tables, see IMPORT.
  • IMPORT INTO cannot be used within a transaction or during a rolling upgrade.
  • IMPORT INTO invalidates all foreign keys on the target table. To validate the foreign key(s), use the VALIDATE CONSTRAINT statement.
  • IMPORT INTO cannot be used to insert data into a column for an existing row. To do this, use INSERT.

Required privileges

Only members of the admin role can run IMPORT INTO. By default, the root user belongs to the admin role.

Synopsis

IMPORT INTO table_name ( column_name , ) CSV AVRO DATA ( file_location , ) WITH option = value ,
Note:

While importing into an existing table, the table is taken offline.

Parameters

Parameter Description
table_name The name of the table you want to import into.
column_name The table columns you want to import.

Note: Currently, target columns are not enforced.
file_location The URL of a CSV or Avro file containing the table data. This can be a comma-separated list of URLs. For an example, see Import into an existing table from multiple CSV files below.
<option> [= <value>] Control your import's behavior with CSV import options or Avro import options.

Import file URLs

URLs for the files you want to import must use the format shown below. For examples, see Example file URLs.

[scheme]://[host]/[path]?[parameters]
Location Scheme Host Parameters
Amazon s3 Bucket name AUTH 1 (optional; can be implicit or specified), AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN
Azure azure N/A (see Example file URLs AZURE_ACCOUNT_KEY, AZURE_ACCOUNT_NAME
Google Cloud 2 gs Bucket name AUTH (optional; can be default, implicit, or specified), CREDENTIALS
HTTP 3 http Remote host N/A
NFS/Local 4 nodelocal nodeID or self 5 (see Example file URLs) N/A
S3-compatible services 6 s3 Bucket name AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, AWS_SESSION_TOKEN, AWS_REGION 7 (optional), AWS_ENDPOINT
Note:

The location parameters often contain special characters that need to be URI-encoded. Use Javascript's encodeURIComponent function or Go language's url.QueryEscape function to URI-encode the parameters. Other languages provide similar functions to URI-encode special characters.

Note:

If your environment requires an HTTP or HTTPS proxy server for outgoing connections, you can set the standard HTTP_PROXY and HTTPS_PROXY environment variables when starting CockroachDB.

New in v20.1: If you cannot run a full proxy, you can disable external HTTP(S) access (as well as custom HTTP(S) endpoints) when performing bulk operations (e.g., BACKUP, RESTORE, etc.) by using the --external-io-disable-http flag. You can also disable the use of implicit credentials when accessing external cloud storage services for various bulk operations by using the --external-io-disable-implicit-credentials flag.

  • 1 If the AUTH parameter is not provided, AWS connections default to specified and the access keys must be provided in the URI parameters. If the AUTH parameter is implicit, the access keys can be ommitted and the credentials will be loaded from the environment.

  • 2 If the AUTH parameter is not specified, the cloudstorage.gs.default.key cluster setting will be used if it is non-empty, otherwise the implicit behavior is used. If the AUTH parameter is implicit, all GCS connections use Google's default authentication strategy. If the AUTH parameter is default, the cloudstorage.gs.default.key cluster setting must be set to the contents of a service account file which will be used during authentication. If the AUTH parameter is specified, GCS connections are authenticated on a per-statement basis, which allows the JSON key object to be sent in the CREDENTIALS parameter. The JSON key object should be base64-encoded (using the standard encoding in RFC 4648).

  • 3 You can create your own HTTP server with Caddy or nginx. A custom root CA can be appended to the system's default CAs by setting the cloudstorage.http.custom_ca cluster setting, which will be used when verifying certificates from HTTPS URLs.

  • 4 The file system backup location on the NFS drive is relative to the path specified by the --external-io-dir flag set while starting the node. If the flag is set to disabled, then imports from local directories and NFS drives are disabled.

  • 5 New in v20.1: Using a nodeID is required and the data files will be in the extern directory of the specified node. In most cases (including single-node clusters), using nodelocal://1/<path> is sufficient. Use self if you do not want to specify a nodeID, and the individual data files will be in the extern directories of arbitrary nodes; however, to work correctly, each node must have the --external-io-dir flag point to the same NFS mount or other network-backed, shared storage.

  • 6 A custom root CA can be appended to the system's default CAs by setting the cloudstorage.http.custom_ca cluster setting, which will be used when verifying certificates from an S3-compatible service.

  • 7 The AWS_REGION parameter is optional since it is not a required parameter for most S3-compatible services. Specify the parameter only if your S3-compatible service requires it.

Example file URLs

Location Example
Amazon S3 s3://acme-co/employees.sql?AWS_ACCESS_KEY_ID=123&AWS_SECRET_ACCESS_KEY=456
Azure azure://employees.sql?AZURE_ACCOUNT_KEY=123&AZURE_ACCOUNT_NAME=acme-co
Google Cloud gs://acme-co/employees.sql
HTTP http://localhost:8080/employees.sql
NFS/Local nodelocal://1/path/employees, nodelocal://self/nfsmount/backups/employees 5

CSV import options

You can control the IMPORT process's behavior using any of the following key-value pairs as a <option> [= <value>].

Option Value Example
delimiter The unicode character that delimits columns in your rows.

Default: ,.
To use tab-delimited values: IMPORT INTO foo (..) CSV DATA ('file.csv') WITH delimiter = e'\t';
comment The unicode character that identifies rows to skip. IMPORT INTO foo (..) CSV DATA ('file.csv') WITH comment = '#';
nullif The string that should be converted to NULL. To use empty columns as NULL: IMPORT INTO foo (..) CSV DATA ('file.csv') WITH nullif = '';
skip The number of rows to be skipped while importing a file.

Default: '0'.
To import CSV files with column headers: IMPORT INTO ... CSV DATA ('file.csv') WITH skip = '1';
decompress The decompression codec to be used: gzip, bzip, auto, or none.

Default: 'auto', which guesses based on file extension (.gz, .bz, .bz2). none disables decompression.
IMPORT INTO ... WITH decompress = 'bzip';

For examples showing how to use these options, see the IMPORT - Examples section.

For instructions and working examples showing how to migrate data from other databases and formats, see the Migration Overview. For information on how to import data into new tables, see IMPORT.

Avro import options

Option Description Example
strict_validation Rejects Avro records that do not have a one-to-one mapping between Avro fields to the target CockroachDB schema. By default, CockroachDB ignores unknown Avro fields and sets missing SQL fields to NULL. CockroachDB will also attempt to convert the Avro field to the CockroachDB data type; otherwise, it will report an error. IMPORT INTO foo (..) AVRO DATA ('file.avro') WITH strict_validation;
records_terminated_by The unicode character to indicate new lines in the input binary or JSON file. This is not needed for Avro OCF.

Default: \n
To use tab-terminated records: IMPORT INTO foo (..) AVRO DATA ('file.csv') WITH records_terminated_by = e'\t';
data_as_binary_records Use when importing a binary file containing Avro records. The schema is not included in the file, so you need to specify the schema with either the schema or schema_uri option. IMPORT INTO foo (..) AVRO DATA ('file.bjson') WITH data_as_binary_records, schema_uri='..';
data_as_json_records Use when importing a JSON file containing Avro records. The schema is not included in the file, so you need to specify the schema with either the schema or schema_uri option. IMPORT INTO foo (..) AVRO DATA ('file.bjson') WITH data_as_json_records, schema='{ "type": "record",..}';
schema The schema of the Avro records included in the binary or JSON file. This is not needed for Avro OCF. See data_as_json_records example above.
schema_uri The URI of the file containing the schema of the Avro records include in the binary or JSON file. This is not needed for Avro OCF. See data_as_binary_records example above.

Requirements

Prerequisites

Before using IMPORT INTO, you should have:

  • An existing table to import into (use CREATE TABLE).
  • The CSV or Avro data you want to import, preferably hosted on cloud storage. This location must be equally accessible to all nodes using the same import file location. This is necessary because the IMPORT INTO statement is issued once by the client, but is executed concurrently across all nodes of the cluster. For more information, see the Import file location section below.
Warning:

Column values cannot be generated by DEFAULT when importing; an import must include a value for every column specified in the IMPORT INTO statement. To use DEFAULT values, your file must contain values for the column upon import, or you can add the column or alter the column after the table has been imported.

Available storage

Each node in the cluster is assigned an equal part of the imported data, and so must have enough temp space to store it. In addition, data is persisted as a normal table, and so there must also be enough space to hold the final, replicated data. The node's first-listed/default store directory must have enough available storage to hold its portion of the data.

On cockroach start, if you set --max-disk-temp-storage, it must also be greater than the portion of the data a node will store in temp space.

Import file location

We strongly recommend using cloud/remote storage (Amazon S3, Google Cloud Platform, etc.) for the data you want to import, but local files are supported as well.

To import a local file, you have the following options:

  • Option 1. Run a local file server to make the file accessible from all nodes.

  • Option 2. Make the file accessible from a local node's store. You can do this by using cockroach nodelocal upload or by manually placing the file in the extern directory:

    1. Create an extern directory on a node's store. The pathname will differ depending on the --store flag passed to cockroach start (if any), but will look something like /path/to/cockroach-data/extern/.
    2. Copy the file to a node's extern directory.
    3. Assuming the file is called data.sql and you uploaded it to node 1, you can access it in your IMPORT statement using the following import file URL: 'nodelocal://1/data.sql'.

Performance

All nodes are used during the import job, which means all nodes' CPU and RAM will be partially consumed by the IMPORT task in addition to serving normal traffic.

Viewing and controlling import jobs

After CockroachDB successfully initiates an import into an existing table, it registers the import as a job, which you can view with SHOW JOBS.

After the import has been initiated, you can control it with PAUSE JOB, RESUME JOB, and CANCEL JOB.

Note:

If initiated correctly, the statement returns when the import is finished or if it encounters an error. In some cases, the import can continue after an error has been returned (the error message will tell you that the import has resumed in background).

Warning:

Pausing and then resuming an IMPORT INTO job will cause it to restart from the beginning.

Examples

Import into an existing table from a CSV file

Amazon S3:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      's3://acme-co/customers.csv?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder]&AWS_SESSION_TOKEN=[placeholder]'
    );

Azure:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      'azure://acme-co/customer-import-data.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co'
    );

Google Cloud:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      'gs://acme-co/customers.csv'
    );

Import into an existing table from multiple CSV files

Amazon S3:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      's3://acme-co/customers.csv?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder]',
      's3://acme-co/customers2.csv?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder',
      's3://acme-co/customers3.csv?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder]',
      's3://acme-co/customers4.csv?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder]',
    );

Azure:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      'azure://acme-co/customer-import-data1.1.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co',
      'azure://acme-co/customer-import-data1.2.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co',
      'azure://acme-co/customer-import-data1.3.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co',
      'azure://acme-co/customer-import-data1.4.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co',
      'azure://acme-co/customer-import-data1.5.csv?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co',    
    );

Google Cloud:

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> IMPORT INTO customers (id, name)
    CSV DATA (
      'gs://acme-co/customers.csv',
      'gs://acme-co/customers2.csv',
      'gs://acme-co/customers3.csv',
      'gs://acme-co/customers4.csv',
    );

Import into an existing table from an Avro file

New in v20.1: Avro OCF data, JSON records, or binary records can be imported. The following are examples of importing Avro OCF data.

To specify the table schema in-line:

Amazon S3:

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> IMPORT INTO customers
    AVRO DATA (
      's3://acme-co/customers.avro?AWS_ACCESS_KEY_ID=[placeholder]&AWS_SECRET_ACCESS_KEY=[placeholder]&AWS_SESSION_TOKEN=[placeholder]'
    );

Azure:

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> IMPORT INTO customers
    AVRO DATA (
      'azure://acme-co/customers.avro?AZURE_ACCOUNT_KEY=hash&AZURE_ACCOUNT_NAME=acme-co'
    );

Google Cloud:

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> IMPORT INTO customers
    AVRO DATA (
      'gs://acme-co/customers.avro'
    );

For more detailed information about importing data from Avro and examples, see Migrate from Avro.

Known limitations

  • While importing into an existing table, the table is taken offline.
  • After importing into an existing table, constraints will be un-validated and need to be re-validated.
  • Imported rows must not conflict with existing rows in the table or any unique secondary indexes.
  • IMPORT INTO works for only a single existing table, and the table must not be interleaved.
  • IMPORT INTO cannot be used within a transaction.
  • IMPORT INTO can sometimes fail with a "context canceled" error, or can restart itself many times without ever finishing. If this is happening, it is likely due to a high amount of disk contention. This can be mitigated by setting the kv.bulk_io_write.max_rate cluster setting to a value below your max disk write speed. For example, to set it to 10MB/s, execute:

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    > SET CLUSTER SETTING kv.bulk_io_write.max_rate = '10MB';
    

See also



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