Druid connector#
The Druid connector allows querying an Apache Druid database from Trino.
Requirements#
To connect to Druid, you need:
Druid version 0.18.0 or higher.
Network access from the Trino coordinator and workers to your Druid broker. Port 8082 is the default port.
Configuration#
Create a catalog properties file that specifies the Druid connector by setting
the connector.name to druid and configuring the connection-url with
the JDBC string to connect to Druid.
For example, to access a database as example, create the file
etc/catalog/example.properties. Replace BROKER:8082 with the correct
host and port of your Druid broker.
connector.name=druid
connection-url=jdbc:avatica:remote:url=http://BROKER:8082/druid/v2/sql/avatica/
You can add authentication details to connect to a Druid deployment that is secured by basic authentication by updating the URL and adding credentials:
connection-url=jdbc:avatica:remote:url=http://BROKER:port/druid/v2/sql/avatica/;authentication=BASIC
connection-user=root
connection-password=secret
Now you can access your Druid database in Trino with the example catalog
name from the properties file.
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 actual values in the catalog
properties files.
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 |
|---|---|
|
Type of the credential provider. Must be one of |
|
Connection user name. |
|
Connection password. |
|
Name of the extra credentials property, whose value to use as the user
name. See |
|
Name of the extra credentials property, whose value to use as the password. |
|
Location of the properties file where credentials are present. It must
contain the |
|
The location of the Java Keystore file, from which to read credentials. |
|
File format of the keystore file, for example |
|
Password for the key store. |
|
Name of the key store entity to use as the user name. |
|
Password for the user name key store entity. |
|
Name of the key store entity to use as the password. |
|
Password for the password key store entity. |
General configuration properties#
The following table describes general catalog configuration properties for the connector:
Property name |
Description |
|---|---|
|
Support case insensitive schema and table names. Defaults to |
|
Duration for which case insensitive schema and table
names are cached. Defaults to |
|
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 |
|
Frequency with which Trino checks the name matching configuration file
for changes. The duration value defaults to |
|
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 |
|
Duration for which schema metadata is cached.
Defaults to the value of |
|
Duration for which table metadata is cached.
Defaults to the value of |
|
Duration for which tables statistics are cached.
Defaults to the value of |
|
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
256 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
Type mapping#
Because Trino and Druid each support types that the other does not, this connector modifies some types when reading data.
Druid type to Trino type mapping#
The connector maps Druid types to the corresponding Trino types according to the following table:
Druid type |
Trino type |
Notes |
|---|---|---|
|
|
|
|
|
|
|
|
|
|
|
Except for the special |
|
|
Only applicable to the special |
No other data types are supported.
Druid does not have a real NULL value for any data type. By
default, Druid treats NULL as the default value for a data type. For
example, LONG would be 0, DOUBLE would be 0.0, STRING would
be an empty string '', and so forth.
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 |
SQL support#
The connector provides globally available and read operation statements to access data and metadata in the Druid database.
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 Druid.
query(varchar) -> table#
The query function allows you to query the underlying database directly. It
requires syntax native to Druid, because the full query is pushed down and
processed in Druid. This can be useful for accessing native features which are
not available in Trino 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.
As an example, query the example catalog and use STRING_TO_MV and
MV_LENGTH from Druid SQL’s multi-value string functions
to split and then count the number of comma-separated values in a column:
SELECT
num_reports
FROM
TABLE(
example.system.query(
query => 'SELECT
MV_LENGTH(
STRING_TO_MV(direct_reports, ",")
) AS num_reports
FROM company.managers'
)
);
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.