Loading data into an Amazon Aurora MySQL DB cluster from text files in an Amazon S3 bucket
You can use the LOAD DATA FROM S3
or LOAD XML FROM S3
statement to load data from files stored in an Amazon S3 bucket. In Aurora MySQL, the files are
first stored on the local disk, and then imported to the database. After the imports to the
database are done, the local files are deleted.
Note
Loading data into a table from text files isn't supported for Aurora Serverless v1. It is supported for Aurora Serverless v2.
Contents
Giving Aurora access to Amazon S3
Before you can load data from an Amazon S3 bucket, you must first give your Aurora MySQL DB cluster permission to access Amazon S3.
To give Aurora MySQL access to Amazon S3
-
Create an Amazon Identity and Access Management (IAM) policy that provides the bucket and object permissions that allow your Aurora MySQL DB cluster to access Amazon S3. For instructions, see Creating an IAM policy to access Amazon S3 resources.
Note
In Aurora MySQL version 3.05 and higher, you can load objects that are encrypted using customer-managed Amazon KMS keys. To do so, include the
kms:Decrypt
permission in your IAM policy. For more information, see Creating an IAM policy to access Amazon KMS resources.You don't need this permission to load objects that are encrypted using Amazon managed keys or Amazon S3 managed keys (SSE-S3).
-
Create an IAM role, and attach the IAM policy you created in Creating an IAM policy to access Amazon S3 resources to the new IAM role. For instructions, see Creating an IAM role to allow Amazon Aurora to access Amazon services.
-
Make sure the DB cluster is using a custom DB cluster parameter group.
For more information about creating a custom DB cluster parameter group, see Creating a DB cluster parameter group in Amazon Aurora.
-
For Aurora MySQL version 2, set either the
aurora_load_from_s3_role
oraws_default_s3_role
DB cluster parameter to the Amazon Resource Name (ARN) of the new IAM role. If an IAM role isn't specified foraurora_load_from_s3_role
, Aurora uses the IAM role specified inaws_default_s3_role
.For Aurora MySQL version 3, use
aws_default_s3_role
.If the cluster is part of an Aurora global database, set this parameter for each Aurora cluster in the global database. Although only the primary cluster in an Aurora global database can load data, another cluster might be promoted by the failover mechanism and become the primary cluster.
For more information about DB cluster parameters, see Amazon Aurora DB cluster and DB instance parameters.
-
To permit database users in an Aurora MySQL DB cluster to access Amazon S3, associate the role that you created in Creating an IAM role to allow Amazon Aurora to access Amazon services with the DB cluster. For an Aurora global database, associate the role with each Aurora cluster in the global database. For information about associating an IAM role with a DB cluster, see Associating an IAM role with an Amazon Aurora MySQL DB cluster.
-
Configure your Aurora MySQL DB cluster to allow outbound connections to Amazon S3. For instructions, see Enabling network communication from Amazon Aurora to other Amazon services.
If your DB cluster isn't publicly accessible and in a VPC public subnet, it is private. You can create an S3 gateway endpoint to access your S3 bucket. For more information, see Gateway endpoints for Amazon S3.
For an Aurora global database, enable outbound connections for each Aurora cluster in the global database.
Granting privileges to load data in Amazon Aurora MySQL
The database user that issues the LOAD DATA FROM S3
or LOAD XML FROM S3
statement must have a
specific role or privilege to issue either statement. In Aurora MySQL version 3, you grant the AWS_LOAD_S3_ACCESS
role. In Aurora MySQL version 2, you grant the LOAD FROM S3
privilege. The administrative user for a DB cluster is
granted the appropriate role or privilege by default. You can grant the privilege to another user by using one of the following
statements.
Use the following statement for Aurora MySQL version 3:
GRANT AWS_LOAD_S3_ACCESS TO '
user
'@'domain-or-ip-address
'
Tip
When you use the role technique in Aurora MySQL version 3, you can also activate the role by
using the SET ROLE
or role_name
SET ROLE
ALL
statement. If you aren't familiar with the MySQL 8.0 role system, you can
learn more in Role-based privilege model. For more details, see Using roles
This only applies to the current active session. When you reconnect, you must run the
SET ROLE
statement again to grant privileges. For more information, see
SET ROLE
statement
You can use the activate_all_roles_on_login
DB cluster parameter to
automatically activate all roles when a user connects to a DB instance. When this
parameter is set, you generally don't have to call the SET ROLE
statement
explicitly to activate a role. For more information, see activate_all_roles_on_login
However, you must call SET ROLE ALL
explicitly at the beginning of a
stored procedure to activate the role, when the stored procedure is called by a
different user.
Use the following statement for Aurora MySQL version 2:
GRANT LOAD FROM S3 ON *.* TO '
user
'@'domain-or-ip-address
'
The AWS_LOAD_S3_ACCESS
role and LOAD FROM S3
privilege are specific to Amazon Aurora and are not
available for external MySQL databases or RDS for MySQL DB instances. If you have set up replication between an Aurora DB cluster as
the replication source and a MySQL database as the replication client, then the GRANT
statement for the role or
privilege causes replication to stop with an error. You can safely skip the error to resume replication. To skip the error on an
RDS for MySQL instance, use the mysql_rds_skip_repl_error
procedure. To skip the error on an external MySQL database, use the slave_skip_errors
Note
The database user must have INSERT
privileges for the database into
which it's loading data.
Specifying the path (URI) to an Amazon S3 bucket
The syntax for specifying the path (URI) to files stored on an Amazon S3 bucket is as follows.
s3
-region
://amzn-s3-demo-bucket
/file-name-or-prefix
The path includes the following values:
-
region
(optional) – The Amazon Region that contains the Amazon S3 bucket to load from. This value is optional. If you don't specify aregion
value, then Aurora loads your file from Amazon S3 in the same region as your DB cluster. -
bucket-name
– The name of the Amazon S3 bucket that contains the data to load. Object prefixes that identify a virtual folder path are supported. -
file-name-or-prefix
– The name of the Amazon S3 text file or XML file, or a prefix that identifies one or more text or XML files to load. You can also specify a manifest file that identifies one or more text files to load. For more information about using a manifest file to load text files from Amazon S3, see Using a manifest to specify data files to load.
To copy the URI for files in an S3 bucket
Sign in to the Amazon Web Services Management Console and open the Amazon S3 console at https://console.amazonaws.cn/s3/
. -
In the navigation pane, choose Buckets, and then choose the bucket whose URI you want to copy.
-
Select the prefix or file that you want to load from S3.
-
Choose Copy S3 URI.
LOAD DATA FROM S3
You can use the LOAD DATA FROM S3
statement to load data from any text file format that is supported by the
MySQL LOAD DATA INFILE
Note
Make sure that your Aurora MySQL DB cluster allows outbound connections to S3. For more information, see Enabling network communication from Amazon Aurora to other Amazon services.
Syntax
LOAD DATA [FROM] S3 [FILE | PREFIX | MANIFEST] '
S3-URI
' [REPLACE | IGNORE] INTO TABLEtbl_name
[PARTITION (partition_name
,...)] [CHARACTER SETcharset_name
] [{FIELDS | COLUMNS} [TERMINATED BY 'string
'] [[OPTIONALLY] ENCLOSED BY 'char
'] [ESCAPED BY 'char
'] ] [LINES [STARTING BY 'string
'] [TERMINATED BY 'string
'] ] [IGNOREnumber
{LINES | ROWS}] [(col_name_or_user_var
,...)] [SETcol_name
=expr
,...]
Note
In Aurora MySQL version 3.05 and higher, the keyword FROM
is optional.
Parameters
The LOAD DATA FROM S3
statement uses the following required and optional parameters. You can find more
details about some of these parameters in LOAD DATA
Statement
- FILE | PREFIX | MANIFEST
-
Identifies whether to load the data from a single file, from all files that match a given prefix, or from all files in a specified manifest.
FILE
is the default. - S3-URI
-
Specifies the URI for a text or manifest file to load, or an Amazon S3 prefix to use. Specify the URI using the syntax described in Specifying the path (URI) to an Amazon S3 bucket.
- REPLACE | IGNORE
-
Determines what action to take if an input row has the same unique key values as an existing row in the database table.
-
Specify
REPLACE
if you want the input row to replace the existing row in the table. -
Specify
IGNORE
if you want to discard the input row.
-
- INTO TABLE
-
Identifies the name of the database table to load the input rows into.
- PARTITION
-
Requires that all input rows be inserted into the partitions identified by the specified list of comma-separated partition names. If an input row cannot be inserted into one of the specified partitions, then the statement fails and an error is returned.
- CHARACTER SET
-
Identifies the character set of the data in the input file.
- FIELDS | COLUMNS
-
Identifies how the fields or columns in the input file are delimited. Fields are tab-delimited by default.
- LINES
-
Identifies how the lines in the input file are delimited. Lines are delimited by a newline character (
'\n'
) by default. - IGNORE
number
LINES | ROWS -
Specifies to ignore a certain number of lines or rows at the start of the input file. For example, you can use
IGNORE 1 LINES
to skip over an initial header line containing column names, orIGNORE 2 ROWS
to skip over the first two rows of data in the input file. If you also usePREFIX
,IGNORE
skips a certain number of lines or rows at the start of the first input file. - col_name_or_user_var, ...
-
Specifies a comma-separated list of one or more column names or user variables that identify which columns to load by name. The name of a user variable used for this purpose must match the name of an element from the text file, prefixed with @. You can employ user variables to store the corresponding field values for subsequent reuse.
For example, the following statement loads the first column from the input file into the first column of
table1
, and sets the value of thetable_column2
column intable1
to the input value of the second column divided by 100.LOAD DATA FROM S3 's3://
amzn-s3-demo-bucket
/data.txt' INTO TABLE table1 (column1, @var1) SET table_column2 = @var1/100; - SET
-
Specifies a comma-separated list of assignment operations that set the values of columns in the table to values not included in the input file.
For example, the following statement sets the first two columns of
table1
to the values in the first two columns from the input file, and then sets the value of thecolumn3
intable1
to the current time stamp.LOAD DATA FROM S3 's3://
amzn-s3-demo-bucket
/data.txt' INTO TABLE table1 (column1, column2) SET column3 = CURRENT_TIMESTAMP;You can use subqueries in the right side of
SET
assignments. For a subquery that returns a value to be assigned to a column, you can use only a scalar subquery. Also, you cannot use a subquery to select from the table that is being loaded.
You can't use the LOCAL
keyword of the LOAD DATA FROM S3
statement if you're loading data
from an Amazon S3 bucket.
Using a manifest to specify data files to load
You can use the LOAD DATA FROM S3
statement with the MANIFEST
keyword to specify a manifest
file in JSON format that lists the text files to be loaded into a table in your DB cluster.
The following JSON schema describes the format and content of a manifest file.
{ "$schema": "http://json-schema.org/draft-04/schema#", "additionalProperties": false, "definitions": {}, "id": "Aurora_LoadFromS3_Manifest", "properties": { "entries": { "additionalItems": false, "id": "/properties/entries", "items": { "additionalProperties": false, "id": "/properties/entries/items", "properties": { "mandatory": { "default": "false", "id": "/properties/entries/items/properties/mandatory", "type": "boolean" }, "url": { "id": "/properties/entries/items/properties/url", "maxLength": 1024, "minLength": 1, "type": "string" } }, "required": [ "url" ], "type": "object" }, "type": "array", "uniqueItems": true } }, "required": [ "entries" ], "type": "object" }
Each url
in the manifest must specify a URL with the bucket name
and full object path for the file, not just a prefix. You can use a manifest to
load files from different buckets, different regions, or files that do not share
the same prefix. If a region is not specified in the URL, the region of the
target Aurora DB cluster is used. The following example shows a manifest file
that loads four files from different buckets.
{ "entries": [ { "url":"s3://aurora-bucket/2013-10-04-customerdata", "mandatory":true }, { "url":"s3-us-west-2://aurora-bucket-usw2/2013-10-05-customerdata", "mandatory":true }, { "url":"s3://aurora-bucket/2013-10-04-customerdata", "mandatory":false }, { "url":"s3://aurora-bucket/2013-10-05-customerdata" } ] }
The optional mandatory
flag specifies whether LOAD DATA FROM S3
should return an error if
the file is not found. The mandatory
flag defaults to false
. Regardless of how
mandatory
is set, LOAD DATA FROM S3
terminates if no files are found.
Manifest files can have any extension. The following example runs the LOAD DATA FROM S3
statement with
the manifest in the previous example, which is named customer.manifest
.
LOAD DATA FROM S3 MANIFEST 's3-us-west-2://aurora-bucket/customer.manifest' INTO TABLE CUSTOMER FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' (ID, FIRSTNAME, LASTNAME, EMAIL);
After the statement completes, an entry for each successfully loaded file is
written to the aurora_s3_load_history
table.
Verifying loaded files using the aurora_s3_load_history table
Every successful LOAD DATA FROM S3
statement updates the aurora_s3_load_history
table in
the mysql
schema with an entry for each file that was loaded.
After you run the LOAD DATA FROM S3
statement, you can verify which files were loaded by querying the
aurora_s3_load_history
table. To see the files that were loaded from one iteration of the statement,
use the WHERE
clause to filter the records on the Amazon S3 URI for the manifest file used in the statement. If
you have used the same manifest file before, filter the results using the timestamp
field.
select * from mysql.aurora_s3_load_history where load_prefix = '
S3_URI
';
The following table describes the fields in the
aurora_s3_load_history
table.
Field | Description |
---|---|
|
The URI that was specified in the load statement. This URI can map to any of the following:
|
|
The name of a file that was loaded into Aurora from
Amazon S3 using the URI identified in the
|
|
The version number of the file identified by the
|
|
The size of the file loaded, in bytes. |
|
The timestamp when the |
Examples
The following statement loads data from an Amazon S3 bucket that is in the same
region as the Aurora DB cluster. The statement reads the comma-delimited data in
the file customerdata.txt
that is in the amzn-s3-demo-bucket
Amazon S3
bucket, and then loads the data into the table
store-schema.customer-table
.
LOAD DATA FROM S3 's3://
amzn-s3-demo-bucket
/customerdata.csv' INTO TABLE store-schema.customer-table FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' (ID, FIRSTNAME, LASTNAME, ADDRESS, EMAIL, PHONE);
The following statement loads data from an Amazon S3 bucket that is in a different
region from the Aurora DB cluster. The statement reads the comma-delimited data
from all files that match the employee-data
object prefix in the
amzn-s3-demo-bucket
Amazon S3 bucket in the us-west-2
region, and
then loads the data into the employees
table.
LOAD DATA FROM S3 PREFIX 's3-us-west-2://
amzn-s3-demo-bucket
/employee_data' INTO TABLE employees FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' (ID, FIRSTNAME, LASTNAME, EMAIL, SALARY);
The following statement loads data from the files specified in a JSON manifest
file named q1_sales.json into the sales
table.
LOAD DATA FROM S3 MANIFEST 's3-us-west-2://
amzn-s3-demo-bucket1
/q1_sales.json' INTO TABLE sales FIELDS TERMINATED BY ',' LINES TERMINATED BY '\n' (MONTH, STORE, GROSS, NET);
LOAD XML FROM S3
You can use the LOAD XML FROM S3
statement to load data from XML
files stored on an Amazon S3 bucket in one of three different XML formats:
-
Column names as attributes of a
<row>
element. The attribute value identifies the contents of the table field.<row column1="value1" column2="value2" .../>
-
Column names as child elements of a
<row>
element. The value of the child element identifies the contents of the table field.<row> <column1>value1</column1> <column2>value2</column2> </row>
-
Column names in the
name
attribute of<field>
elements in a<row>
element. The value of the<field>
element identifies the contents of the table field.<row> <field name='column1'>value1</field> <field name='column2'>value2</field> </row>
Syntax
LOAD XML FROM S3 '
S3-URI
' [REPLACE | IGNORE] INTO TABLEtbl_name
[PARTITION (partition_name,...)] [CHARACTER SET charset_name] [ROWS IDENTIFIED BY '<element-name>
'] [IGNOREnumber
{LINES | ROWS}] [(field_name_or_user_var,...)] [SET col_name = expr,...]
Parameters
The LOAD XML FROM S3
statement uses the following required and optional parameters. You can find more
details about some of these parameters in LOAD XML
Statement
- FILE | PREFIX
-
Identifies whether to load the data from a single file, or from all files that match a given prefix.
FILE
is the default. - REPLACE | IGNORE
-
Determines what action to take if an input row has the same unique key values as an existing row in the database table.
-
Specify
REPLACE
if you want the input row to replace the existing row in the table. -
Specify
IGNORE
if you want to discard the input row.IGNORE
is the default.
-
- INTO TABLE
-
Identifies the name of the database table to load the input rows into.
- PARTITION
-
Requires that all input rows be inserted into the partitions identified by the specified list of comma-separated partition names. If an input row cannot be inserted into one of the specified partitions, then the statement fails and an error is returned.
- CHARACTER SET
-
Identifies the character set of the data in the input file.
- ROWS IDENTIFIED BY
-
Identifies the element name that identifies a row in the input file. The default is
<row>
. - IGNORE
number
LINES | ROWS -
Specifies to ignore a certain number of lines or rows at the start of the input file. For example, you can use
IGNORE 1 LINES
to skip over the first line in the text file, orIGNORE 2 ROWS
to skip over the first two rows of data in the input XML. - field_name_or_user_var, ...
-
Specifies a comma-separated list of one or more XML element names or user variables that identify which elements to load by name. The name of a user variable used for this purpose must match the name of an element from the XML file, prefixed with @. You can employ user variables to store the corresponding field values for subsequent reuse.
For example, the following statement loads the first column from the input file into the first column of
table1
, and sets the value of thetable_column2
column intable1
to the input value of the second column divided by 100.LOAD XML FROM S3 's3://
amzn-s3-demo-bucket
/data.xml' INTO TABLE table1 (column1, @var1) SET table_column2 = @var1/100; - SET
-
Specifies a comma-separated list of assignment operations that set the values of columns in the table to values not included in the input file.
For example, the following statement sets the first two columns of
table1
to the values in the first two columns from the input file, and then sets the value of thecolumn3
intable1
to the current time stamp.LOAD XML FROM S3 's3://
amzn-s3-demo-bucket
/data.xml' INTO TABLE table1 (column1, column2) SET column3 = CURRENT_TIMESTAMP;You can use subqueries in the right side of
SET
assignments. For a subquery that returns a value to be assigned to a column, you can use only a scalar subquery. Also, you can't use a subquery to select from the table that's being loaded.