MySQL connector#
The MySQL connector lets you query and create tables in an external MySQL instance. This can be used to join data between different systems like MySQL and Hive, or between two different MySQL instances.
SEP includes additional enterprise features that are built on top of the existing Trino connector functionality. For more information on connector key feature differences between Trino and SEP, see the connectors feature matrix.
Requirements#
To connect to MySQL, you need:
MySQL 5.7, 8.0 or higher.
Network access from the SEP coordinator and workers to MySQL. Port 3306 is the default port.
A valid Starburst Enterprise license.
Configuration#
To configure the MySQL connector, create a catalog properties file that
specifies the MySQL connector by setting the connector.name
to mysql
.
For example, to access a database as the example
catalog, create the file
etc/catalog/example.properties
. Replace the connection properties as
appropriate for your setup:
connector.name=mysql
connection-url=jdbc:mysql://example.net:3306
connection-user=root
connection-password=secret
The connection-url
defines the connection information and parameters to pass
to the MySQL JDBC driver. The supported parameters for the URL are available in
the MySQL Developer
Guide.
For example, the following connection-url
gives you the ability to require
encrypted connections to the MySQL server:
connection-url=jdbc:mysql://example.net:3306?sslMode=REQUIRED
The connection-user
and connection-password
are typically required and
determine the user credentials for the connection, often a service user. You can
use secrets to avoid exposing actual values in the
catalog properties files.
Connection security#
If you have TLS configured with a globally-trusted certificate installed on your
data source, you can enable TLS between your cluster and the data source by
appending a parameter to the JDBC connection string set in the connection-url
catalog configuration property.
For example, with version 8.0 of MySQL Connector/J, use the sslMode
parameter
to secure the connection with TLS. By default the parameter is set to
PREFERRED
which secures the connection if enabled by the server. You can also
set this parameter to REQUIRED
which causes the connection to fail if TLS is
not established.
You can set the sslMode
parameter in the catalog configuration file by
appending it to the connection-url
configuration property:
connection-url=jdbc:mysql://example.net:3306/?sslMode=REQUIRED
For more information on TLS configuration options, see the MySQL JDBC security documentation.
Data source authentication#
The connector can provide credentials for the data source connection in multiple ways:
inline, in the connector configuration file
in a separate properties file
in a key store file
as extra credentials set when connecting to Trino
You can use secrets to avoid storing sensitive values in the catalog properties files.
The following table describes configuration properties for connection credentials:
Property name |
Description |
---|---|
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Type of the credential provider. Must be one of |
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Connection user name. |
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Connection password. |
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Name of the extra credentials property, whose value to use as the user
name. See |
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Name of the extra credentials property, whose value to use as the password. |
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Location of the properties file where credentials are present. It must
contain the |
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The location of the Java Keystore file, from which to read credentials. |
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File format of the keystore file, for example |
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Password for the key store. |
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Name of the key store entity to use as the user name. |
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Password for the user name key store entity. |
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Name of the key store entity to use as the password. |
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Password for the password key store entity. |
Multiple MySQL servers#
You can have as many catalogs as you need. If you have additional MySQL servers,
add another properties file to etc/catalog
with a different name, making sure
it ends in .properties
. For example, if you name the property file
sales.properties
, SEP creates a catalog named sales
using the configured
connector.
General configuration properties#
The following table describes general catalog configuration properties for the connector:
Property name |
Description |
---|---|
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Support case insensitive schema and table names. Defaults to |
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Duration for which case insensitive schema and table
names are cached. Defaults to |
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Path to a name mapping configuration file in JSON format that allows
Trino to disambiguate between schemas and tables with similar names in
different cases. Defaults to |
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Frequency with which Trino checks the name matching configuration file
for changes. The duration value defaults to |
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Duration for which metadata, including table and
column statistics, is cached. Defaults to |
|
Cache the fact that metadata, including table and column statistics, is
not available. Defaults to |
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Duration for which schema metadata is cached.
Defaults to the value of |
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Duration for which table metadata is cached.
Defaults to the value of |
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Duration for which tables statistics are cached.
Defaults to the value of |
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Maximum number of objects stored in the metadata cache. Defaults to |
|
Maximum number of statements in a batched execution. Do not change
this setting from the default. Non-default values may negatively
impact performance. Defaults to |
|
Push down dynamic filters into JDBC queries. Defaults to |
|
Maximum duration for which Trino waits for dynamic
filters to be collected from the build side of joins before starting a
JDBC query. Using a large timeout can potentially result in more detailed
dynamic filters. However, it can also increase latency for some queries.
Defaults to |
Appending query metadata#
The optional parameter query.comment-format
allows you to configure a SQL
comment that is sent to the datasource with each query. The format of this
comment can contain any characters and the following metadata:
$QUERY_ID
: The identifier of the query.$USER
: The name of the user who submits the query to Trino.$SOURCE
: The identifier of the client tool used to submit the query, for exampletrino-cli
.$TRACE_TOKEN
: The trace token configured with the client tool.
The comment can provide more context about the query. This additional
information is available in the logs of the datasource. To include environment
variables from the Trino cluster with the comment , use the
${ENV:VARIABLE-NAME}
syntax.
The following example sets a simple comment that identifies each query sent by Trino:
query.comment-format=Query sent by Trino.
With this configuration, a query such as SELECT * FROM example_table;
is
sent to the datasource with the comment appended:
SELECT * FROM example_table; /*Query sent by Trino.*/
The following example improves on the preceding example by using metadata:
query.comment-format=Query $QUERY_ID sent by user $USER from Trino.
If Jane
sent the query with the query identifier
20230622_180528_00000_bkizg
, the following comment string is sent to the
datasource:
SELECT * FROM example_table; /*Query 20230622_180528_00000_bkizg sent by user Jane from Trino.*/
Note
Certain JDBC driver settings and logging configurations might cause the comment to be removed.
Domain compaction threshold#
Pushing down a large list of predicates to the data source can compromise
performance. Trino compacts large predicates into a simpler range predicate
by default to ensure a balance between performance and predicate pushdown.
If necessary, the threshold for this compaction can be increased to improve
performance when the data source is capable of taking advantage of large
predicates. Increasing this threshold may improve pushdown of large
dynamic filters.
The domain-compaction-threshold
catalog configuration property or the
domain_compaction_threshold
catalog session property can be used to adjust the default value of
32
for this threshold.
Case insensitive matching#
When case-insensitive-name-matching
is set to true
, Trino
is able to query non-lowercase schemas and tables by maintaining a mapping of
the lowercase name to the actual name in the remote system. However, if two
schemas and/or tables have names that differ only in case (such as “customers”
and “Customers”) then Trino fails to query them due to ambiguity.
In these cases, use the case-insensitive-name-matching.config-file
catalog
configuration property to specify a configuration file that maps these remote
schemas/tables to their respective Trino schemas/tables:
{
"schemas": [
{
"remoteSchema": "CaseSensitiveName",
"mapping": "case_insensitive_1"
},
{
"remoteSchema": "cASEsENSITIVEnAME",
"mapping": "case_insensitive_2"
}],
"tables": [
{
"remoteSchema": "CaseSensitiveName",
"remoteTable": "tablex",
"mapping": "table_1"
},
{
"remoteSchema": "CaseSensitiveName",
"remoteTable": "TABLEX",
"mapping": "table_2"
}]
}
Queries against one of the tables or schemes defined in the mapping
attributes are run against the corresponding remote entity. For example, a query
against tables in the case_insensitive_1
schema is forwarded to the
CaseSensitiveName schema and a query against case_insensitive_2
is forwarded
to the cASEsENSITIVEnAME
schema.
At the table mapping level, a query on case_insensitive_1.table_1
as
configured above is forwarded to CaseSensitiveName.tablex
, and a query on
case_insensitive_1.table_2
is forwarded to CaseSensitiveName.TABLEX
.
By default, when a change is made to the mapping configuration file, Trino must
be restarted to load the changes. Optionally, you can set the
case-insensitive-name-mapping.refresh-period
to have Trino refresh the
properties without requiring a restart:
case-insensitive-name-mapping.refresh-period=30s
Non-transactional INSERT#
The connector supports adding rows using INSERT statements.
By default, data insertion is performed by writing data to a temporary table.
You can skip this step to improve performance and write directly to the target
table. Set the insert.non-transactional-insert.enabled
catalog property
or the corresponding non_transactional_insert
catalog session property to
true
.
Note that with this property enabled, data can be corrupted in rare cases where exceptions occur during the insert operation. With transactions disabled, no rollback can be performed.
Fault-tolerant execution support#
The connector supports Fault-tolerant execution of query processing. Read and write operations are both supported with any retry policy.
Type mapping#
Because Trino and MySQL each support types that the other does not, this connector modifies some types when reading or writing data. Data types may not map the same way in both directions between Trino and the data source. Refer to the following sections for type mapping in each direction.
MySQL to Trino type mapping#
The connector maps MySQL types to the corresponding Trino types following this table:
MySQL database type |
Trino type |
Notes |
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No other types are supported.
Trino to MySQL type mapping#
The connector maps Trino types to the corresponding MySQL types following this table:
Trino type |
MySQL type |
Notes |
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No other types are supported.
Timestamp type handling#
MySQL TIMESTAMP
types are mapped to Trino TIMESTAMP WITH TIME ZONE
. To
preserve time instants, Trino sets the session time zone of the MySQL
connection to match the JVM time zone. As a result, error messages similar to
the following example occur when a timezone from the JVM does not exist on the
MySQL server:
com.mysql.cj.exceptions.CJException: Unknown or incorrect time zone: 'UTC'
To avoid errors, you must use a time zone that is known on both systems or install the missing time zone on the MySQL server.
Decimal type handling#
DECIMAL
types with unspecified precision or scale are ignored unless the
decimal-mapping
configuration property or the decimal_mapping
session
property is set to allow_overflow
. Then such types are mapped to a Trino
DECIMAL
with a default precision of 38 and default scale of 0. To change the
scale of the resulting type, use the decimal-default-scale
configuration
property or the decimal_default_scale
session property. The precision is
always 38.
By default, values that require rounding or truncation to fit will cause a
failure at runtime. This behavior is controlled via the
decimal-rounding-mode
configuration property or the
decimal_rounding_mode
session property, which can be set to UNNECESSARY
(the default), UP
, DOWN
, CEILING
, FLOOR
, HALF_UP
,
HALF_DOWN
, or HALF_EVEN
(see RoundingMode).
Type mapping configuration properties#
The following properties can be used to configure how data types from the connected data source are mapped to Trino data types and how the metadata is cached in Trino.
Property name |
Description |
Default value |
---|---|---|
|
Configure how unsupported column data types are handled:
The respective catalog session property is |
|
|
Allow forced mapping of comma separated lists of data types to convert to
unbounded |
Querying MySQL#
The MySQL connector provides a schema for every MySQL database. You can see
the available MySQL databases by running SHOW SCHEMAS
:
SHOW SCHEMAS FROM example;
If you have a MySQL database named web
, you can view the tables in this
database by running SHOW TABLES
:
SHOW TABLES FROM example.web;
You can see a list of the columns in the clicks
table in the web
database
using either of the following:
DESCRIBE example.web.clicks;
SHOW COLUMNS FROM example.web.clicks;
Finally, you can access the clicks
table in the web
database:
SELECT * FROM example.web.clicks;
If you used a different name for your catalog properties file, use
that catalog name instead of example
in the above examples.
SQL support#
The connector provides read and write access to data and metadata in the MySQL database. In addition to the globally available and read operation statements, the connector supports the following statements:
UPDATE#
Only UPDATE
statements with constant assignments and predicates are
supported. For example, the following statement is supported because the values
assigned are constants:
UPDATE table SET col1 = 1 WHERE col3 = 1
Arithmetic expressions, function calls, and other non-constant UPDATE
statements are not supported. For example, the following statement is not
supported because arithmetic expressions cannot be used with the SET
command:
UPDATE table SET col1 = col2 + 2 WHERE col3 = 1
All column values of a table row cannot be updated simultaneously. For a three column table, the following statement is not supported:
UPDATE table SET col1 = 1, col2 = 2, col3 = 3 WHERE col3 = 1
SQL DELETE#
If a WHERE
clause is specified, the DELETE
operation only works if the
predicate in the clause can be fully pushed down to the data source.
ALTER TABLE EXECUTE#
This connector supports the following commands for use with ALTER TABLE EXECUTE:
collect_statistics#
The collect_statistics
command is used with
Managed statistics to collect statistics for a table
and its columns.
The following statement collects statistics for the example_table
table
and all of its columns:
ALTER TABLE example_table EXECUTE collect_statistics;
Collecting statistics for all columns in a table may be unnecessarily
performance-intensive, especially for wide tables. To only collect statistics
for a subset of columns, you can include the columns
parameter with an
array of column names. For example:
ALTER TABLE example_table
EXECUTE collect_statistics(columns => ARRAY['customer','line_item']);
Procedures#
system.flush_metadata_cache()
#
Flush JDBC metadata caches. For example, the following system call
flushes the metadata caches for all schemas in the example
catalog
USE example.example_schema;
CALL system.flush_metadata_cache();
system.execute('query')
#
The execute
procedure allows you to execute a query in the underlying data
source directly. The query must use supported syntax of the connected data
source. Use the procedure to access features which are not available in Trino
or to execute queries that return no result set and therefore can not be used
with the query
or raw_query
pass-through table function. Typical use cases
are statements that create or alter objects, and require native feature such
as constraints, default values, automatic identifier creation, or indexes.
Queries can also invoke statements that insert, update, or delete data, and do
not return any data as a result.
The query text is not parsed by Trino, only passed through, and therefore only subject to any security or access control of the underlying data source.
The following example sets the current database to the example_schema
of the
example
catalog. Then it calls the procedure in that schema to drop the
default value from your_column
on your_table
table using the standard SQL
syntax in the parameter value assigned for query
:
USE example.example_schema;
CALL system.execute(query => 'ALTER TABLE your_table ALTER COLUMN your_column DROP DEFAULT');
Verify that the specific database supports this syntax, and adapt as necessary based on the documentation for the specific connected database and database version.
Table functions#
The connector provides specific table functions to access MySQL.
query(varchar) -> table
#
The query
function lets you query the underlying database directly. It
requires syntax native to MySQL because the full query is pushed down and
processed in MySQL. This can be useful for accessing native features which are
not available in SEP or for improving query performance in situations where
running a query natively may be faster.
The native query passed to the underlying data source is required to return a table as a result set. Only the data source performs validation or security checks for these queries using its own configuration. Trino does not perform these tasks. Only use passthrough queries to read data.
For example, query the example
catalog and group and concatenate all
employee IDs by manager ID:
SELECT
*
FROM
TABLE(
example.system.query(
query => 'SELECT
manager_id, GROUP_CONCAT(employee_id)
FROM
company.employees
GROUP BY
manager_id'
)
);
Note
The query engine does not preserve the order of the results of this
function. If the passed query contains an ORDER BY
clause, the
function result may not be ordered as expected.
Performance#
The connector includes a number of performance features, detailed in the following sections.
Table statistics#
The MySQL connector can use table and column statistics for cost based optimizations to improve query processing performance based on the actual data in the data source.
The statistics are collected by MySQL and retrieved by the connector.
The table-level statistics are based on MySQL’s INFORMATION_SCHEMA.TABLES
table. The column-level statistics are based on MySQL’s index statistics
INFORMATION_SCHEMA.STATISTICS
table. The connector can return column-level
statistics only when the column is the first column in an index.
MySQL database can automatically update its table and index statistics. In some cases, you may want to force statistics update, for example after creating new index, or after changing data in the table. You can do that by executing the following statement in MySQL Database:
ANALYZE TABLE table_name;
Note
MySQL and SEP may use statistics information in different ways. For this reason, the accuracy of table and column statistics returned by the MySQL connector might be lower than that of other connectors.
Improving statistics accuracy
You can improve statistics accuracy with histogram statistics (available since MySQL 8.0). To create histogram statistics execute the following statement in MySQL Database.
ANALYZE TABLE table_name UPDATE HISTOGRAM ON column_name1, column_name2, ...;
Refer to MySQL documentation for information about options, limitations, and additional considerations.
Managed statistics#
The connector supports Managed statistics which lets SEP collect and store its own table and column statistics that can then be used for performance optimizations in query planning.
Statistics must be collected manually using the built-in collect_statistics
command, see collect_statistics for details
and examples.
Pushdown#
The connector supports pushdown for the following operations:
Aggregate pushdown for the following functions:
Note
The connector performs pushdown where performance may be improved, but in order to preserve correctness an operation may not be pushed down. When pushdown of an operation may result in better performance but risks correctness, the connector prioritizes correctness.
Cost-based join pushdown#
The connector supports cost-based Join pushdown to make intelligent decisions about whether to push down a join operation to the data source.
When cost-based join pushdown is enabled, the connector only pushes down join operations if the available Table statistics suggest that doing so improves performance. Note that if no table statistics are available, join operation pushdown does not occur to avoid a potential decrease in query performance.
The following table describes catalog configuration properties for join pushdown:
Property name |
Description |
Default value |
---|---|---|
|
Enable join pushdown. Equivalent catalog
session property is
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Strategy used to evaluate whether join operations are pushed down. Set to
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Predicate pushdown support#
The connector does not support pushdown of any predicates on columns with
textual types like CHAR
or VARCHAR
.
This ensures correctness of results since the data source may compare strings
case-insensitively.
In the following example, the predicate is not pushed down for either query
since name
is a column of type VARCHAR
:
SELECT * FROM nation WHERE name > 'CANADA';
SELECT * FROM nation WHERE name = 'CANADA';
Dynamic filtering#
Dynamic filtering is enabled by default. It causes the connector to wait for dynamic filtering to complete before starting a JDBC query.
You can disable dynamic filtering by setting the dynamic-filtering.enabled
property in your catalog configuration file to false
.
Wait timeout#
By default, table scans on the connector are delayed up to 20 seconds until dynamic filters are collected from the build side of joins. Using a large timeout can potentially result in more detailed dynamic filters. However, it can also increase latency for some queries.
You can configure the dynamic-filtering.wait-timeout
property in your
catalog properties file:
dynamic-filtering.wait-timeout=1m
You can use the dynamic_filtering_wait_timeout
catalog session property in a specific session:
SET SESSION example.dynamic_filtering_wait_timeout = 1s;
Compaction#
The maximum size of dynamic filter predicate, that is pushed down to the
connector during table scan for a column, is configured using the
domain-compaction-threshold
property in the catalog
properties file:
domain-compaction-threshold=100
You can use the domain_compaction_threshold
catalog
session property:
SET SESSION domain_compaction_threshold = 10;
By default, domain-compaction-threshold
is set to 32
.
When the dynamic predicate for a column exceeds this threshold, it is compacted
into a single range predicate.
For example, if the dynamic filter collected for a date column dt
on the
fact table selects more than 32 days, the filtering condition is simplified from
dt IN ('2020-01-10', '2020-01-12',..., '2020-05-30')
to dt BETWEEN '2020-01-10' AND '2020-05-30'
. Using a large threshold can result in increased
table scan overhead due to a large IN
list getting pushed down to the data
source.
Metrics#
Metrics about dynamic filtering are reported in a JMX table for each catalog:
jmx.current."io.trino.plugin.jdbc:name=example,type=dynamicfilteringstats"
Metrics include information about the total number of dynamic filters, the number of completed dynamic filters, the number of available dynamic filters and the time spent waiting for dynamic filters.
Starburst Cached Views#
The connector supports table scan redirection, which improves performance and reduces load on the data source.
JDBC connection pooling#
When JDBC connection pooling is enabled, each node creates and maintains a connection pool instead of opening and closing separate connections to the data source. Each connection is available to connect to the data source and retrieve data. After completion of an operation, the connection is returned to the pool and can be reused. This improves performance by a small amount, reduces the load on any required authentication system used for establishing the connection, and helps avoid running into connection limits on data sources.
JDBC connection pooling is disabled by default. You can enable JDBC connection
pooling by setting the connection-pool.enabled
property to true
in your
catalog configuration file:
connection-pool.enabled=true
The following catalog configuration properties can be used to tune connection pooling:
Property name |
Description |
Default value |
---|---|---|
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Enable connection pooling for the catalog. |
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The maximum number of idle and active connections in the pool. |
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The maximum lifetime of a connection. When a connection reaches this lifetime it is removed, regardless of how recently it has been active. |
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The maximum size of the JDBC data source cache. |
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The expiration time of a cached data source when it is no longer accessed. |
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Security#
The connector includes a number of security-related features, detailed in the following sections.
AWS IAM authentication#
When the MySQL database is deployed as an AWS RDS instance, the connector can use IAM authentication. This feature lets you manage access control from SEP with IAM policies.
Configuration#
To enable IAM authentication, add the following configuration properties to the catalog configuration file:
mysql.authentication.type=AWS
connection-user=<RDS username>
aws.region-name=<AWS region>
aws.token-expiration-timeout=10m
You can also configure the connector to assume a specific IAM role for authentication before creating the access token, in order to apply policies specific to SEP. Alongside this role, you must include an (informal) external identifier of a user to assume this role.
To apply an IAM role to the connector, add the following configuration properties:
aws.iam-role=<role_arn>
aws.external-id=<external_id>
This table describes the configuration properties for IAM authentication:
Property name |
Description |
---|---|
|
The database account used to access the RDS database instance. |
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The name of the AWS region in which the RDS instance is deployed. |
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(Optional) Set an IAM role to assume for authentication before creating
the access token. If set, |
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(Optional) The informal identifier of the user who assumes
the IAM role set in |
|
The amount of time to keep the generated RDS access tokens for each user
before they are regenerated. The maximum value is 15 minutes. Defaults to
|
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The access key of the principal to authenticate with for the token generator service. Used for fixed authentication, setting this property disables automatic authentication. |
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The secret key of the principal to authenticate with for the token generator service. Used for fixed authentication, setting this property disables automatic authentication. |
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(Optional) A session token for temporary credentials, such as credentials obtained from SSO. Used for fixed authentication, setting this property disables automatic authentication. |
Authentication#
By default the connector attempts to automatically obtain its authentication credentials from the environment. The default credential provider chain attempts to obtain credentials from the following sources, in order:
Environment variables:
AWS_ACCESS_KEY_ID
andAWS_SECRET_ACCESS_KEY
, orAWS_ACCESS_KEY
andAWS_SECRET_KEY
.Java system properties:
aws.accessKeyId
andaws.secretKey
.Web identity token: credentials from the environment or container.
Credential profiles file: a profiles file at the default location (
~/.aws/credentials
) shared by all AWS SDKs and the AWS CLI.EC2 service credentials: credentials delivered through the Amazon EC2 container service, assuming the security manager has permission to access the value of the
AWS_CONTAINER_CREDENTIALS_RELATIVE_URI
environment variable.Instance profile credentials: credentials delievered through the Amazon EC2 metadata service.
If the SEP cluster is running on an EC2 instance, these credentials most likely come from the metadata service.
Alternatively, you can set fixed credentials for authentication. This option disables the container’s automatic attempt to locate credentials. To use fixed credentials for authentication, set the following configuration properties:
aws.access-key=<access_key>
aws.secret-key=<secret_key>
# (Optional) You can use temporary credentials. For example, you can use temporary credentials from SSO
aws.session-token=<session_token>