New in v19.2: 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, seeIMPORT
.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 theVALIDATE CONSTRAINT
statement.IMPORT INTO
cannot be used to insert data into a column for an existing row. To do this, useINSERT
.
Required privileges
Only members of the admin
role can run IMPORT INTO
. By default, the root
user belongs to the admin
role.
Synopsis
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 file containing the table data. This can be a comma-separated list of URLs to CSV files. For an example, see Import into an existing table from multiple CSV files below. |
<option> [= <value>] |
Control your import's behavior with these 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 |
Empty or nodeID 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 |
If you write to nodelocal
storage in a multi-node cluster, individual data files will be written to the extern
directories of arbitrary nodes and will likely not work as intended. To work correctly, each node must have the --external-io-dir
flag point to the same NFS mount or other network-backed, shared storage.
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.
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.
1 If the
AUTH
parameter is not provided, AWS connections default tospecified
and the access keys must be provided in the URI parameters. If theAUTH
parameter isimplicit
, the access keys can be omitted and the credentials will be loaded from the environment.2 If the
AUTH
parameter is not specified, thecloudstorage.gs.default.key
cluster setting will be used if it is non-empty, otherwise theimplicit
behavior is used. If theAUTH
parameter isimplicit
, all GCS connections use Google's default authentication strategy. If theAUTH
parameter isdefault
, thecloudstorage.gs.default.key
cluster setting must be set to the contents of a service account file which will be used during authentication. If theAUTH
parameter isspecified
, GCS connections are authenticated on a per-statement basis, which allows the JSON key object to be sent in theCREDENTIALS
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 todisabled
, then imports from local directories and NFS drives are disabled.5 The host component of NFS/Local can either be empty or the
nodeID
. If thenodeID
is specified, it is currently ignored (i.e., any node can be sent work and it will look in its local input/output directory); however, thenodeID
will likely be required in the future.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:///path/employees , nodelocal://2/path/employees Note: If you write to nodelocal storage in a multi-node cluster, individual data files will be written to the extern directories of arbitrary nodes and will likely not work as intended. To work correctly, each node must have the --external-io-dir flag point to the same NFS mount or other network-backed, shared storage. |
Import options
You can control the IMPORT
process's behavior using any of the following key-value pairs as a <option> [= <value>]
.
Key | Value | Required? | Example |
---|---|---|---|
delimiter |
The unicode character that delimits columns in your rows. Default: , . |
No | 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. | No | IMPORT INTO foo (..) CSV DATA ('file.csv') WITH comment = '#' |
nullif |
The string that should be converted to NULL. | No | 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' . |
No | 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. |
No | 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
.
Requirements
Prerequisites
Before using IMPORT INTO
, you should have:
- An existing table to import into (use
CREATE TABLE
). - The CSV 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.
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.
Local files are supported; however, they must be accessible to all nodes in the cluster using identical Import file URLs.
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 each local node's store:
- Create an
extern
directory on each node's store. The pathname will differ depending on the--store
flag passed tocockroach start
(if any), but will look something like/path/to/cockroach-data/extern/
. - Copy the file to each node's
extern
directory. - Assuming the file is called
data.sql
, you can access it in yourIMPORT
statement using the following import file URL:'nodelocal:///data.sql'
.
- Create an
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
.
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).
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:
> 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:
> 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:
> IMPORT INTO customers (id, name)
CSV DATA (
'gs://acme-co/customers.csv'
);
Import into an existing table from multiple CSV files
Amazon S3:
> 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:
> 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:
> 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',
);
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 thekv.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:> SET CLUSTER SETTING kv.bulk_io_write.max_rate = '10MB';
IMPORT INTO
cannot be used on a table with aDEFAULT
expression for any of its columns.