Starburst Vertica connector#
The Starburst Vertica connector allows querying a Vertica database as an external data source.
Requirements#
To connect to Vertica, you need:
Vertica 9.1.x or higher.
Network access from the coordinator and workers to the Vertica server. Port 5433 is the default port.
A valid Starburst Enterprise license.
Configuration#
Create a catalog properties file in etc/catalog
named example.properties
to access the configured Vertica database in the example
catalog (replace
example with your database name or some other descriptive name of the catalog).
Configure the usage of the connector by specifying the name vertica
and
replace the connection properties as appropriate for your setup.
connector.name=vertica
connection-url=jdbc:vertica://example.net:5433/test_db
connection-user=root
connection-password=secret
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.
General configuration properties#
The following table describes general catalog configuration properties for the connector:
Property name |
Description |
Default value |
---|---|---|
|
Support case insensitive schema and table names. |
|
|
This value should be a duration. |
|
|
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. |
|
|
Frequency with which Trino checks the name matching configuration file for changes. This value should be a duration. |
(refresh disabled) |
|
The duration for which metadata, including table and column statistics, is cached. |
|
|
Cache the fact that metadata, including table and column statistics, is not available |
|
|
Maximum number of objects stored in the metadata cache |
|
|
Maximum number of statements in a batched execution. Do not change this setting from the default. Non-default values may negatively impact performance. |
|
|
Push down dynamic filters into JDBC queries |
|
|
Maximum duration for which Trino will wait 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. |
|
Type mapping#
Because Trino and Vertica 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.
Vertica to Trino type mapping#
The connector maps Vertica types to the corresponding Trino types according to the following table:
Vertica type |
Trino type |
Notes |
---|---|---|
BOOLEAN |
BOOLEAN |
|
BIGINT |
BIGINT |
Vertica treats TINYINT, SMALLINT, INTEGER, and BIGINT as synonyms for the same 64-bit BIGINT data type |
DOUBLE PRECISION (FLOAT) |
DOUBLE |
Vertica treats FLOAT and REAL as the same 64-bit IEEE FLOAT |
DECIMAL(p, s) |
DECIMAL(p, s) |
|
CHAR, CHAR(n) |
CHAR, CHAR(n) |
|
VARCHAR, LONG VARCHAR, VARCHAR(n), LONG VARCHAR(n) |
VARCHAR(n) |
|
VARBINARY,LONG VARBINARY, VARBINARY(n), LONG VARBINARY(n) |
VARBINARY(n) |
|
DATE |
DATE |
No other types are supported.
Unsupported Vertica types can be converted to VARCHAR
with the
vertica.unsupported_type_handling
session property. The default value for
this property is IGNORE
.
SET SESSION vertica.unsupported_type_handling = 'CONVERT_TO_VARCHAR'
Trino to Vertica type mapping#
The connector maps Trino types to the corresponding Vertica types according to the following table:
Trino type |
Vertica type |
---|---|
BOOLEAN |
BOOLEAN |
TINYINT |
BIGINT |
SMALLINT |
BIGINT |
INTEGER |
BIGINT |
BIGINT |
BIGINT |
REAL |
DOUBLE PRECISION |
DOUBLE |
DOUBLE PRECISION |
DECIMAL(p, s) |
DECIMAL(p, s) |
CHAR |
CHAR |
VARCHAR |
VARCHAR |
VARBINARY |
VARBINARY |
DATE |
DATE |
No other types are supported.
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 read and write access to data and metadata in Vertica. In addition to the globally available and read operation statements, the connector supports the following features:
ALTER TABLE excluding
DROP COLUMN
ALTER TABLE#
The connector does not support renaming tables across multiple schemas. For example, the following statement is supported:
ALTER TABLE example.schema_one.table_one RENAME TO example.schema_one.table_two
The following statement attempts to rename a table across schemas, and therefore is not supported:
ALTER TABLE example.schema_one.table_one RENAME TO example.schema_two.table_two
Table functions#
The connector provides specific table functions to access Vertica.
query(varchar) -> table
#
The query
function allows you to query the underlying database directly. It
requires syntax native to the data source, because the full query is pushed down
and processed in the data source. This can be useful for accessing native
features or for improving query performance in situations where running a query
natively may be faster.
The query
table function is available in the system
schema of any
catalog that uses the Vertica connector, such as example
. The
following example passes myQuery
to the data source. myQuery
has to be a
valid query for the data source, and is required to return a table as a result:
SELECT
*
FROM
TABLE(
example.system.query(
query => 'myQuery'
)
);
Performance#
The connector includes a number of performance improvements, detailed in the following sections.
Pushdown#
The connector supports pushdown for a number of operations:
Join pushdown#
The join-pushdown.enabled
catalog configuration property or
join_pushdown_enabled
catalog session property control whether the connector pushes
down join operations. The property defaults to false
, and enabling join
pushdowns may negatively impact performance for some queries.
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.
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 |
---|---|---|
|
Enable connection pooling for the catalog. |
|
|
The maximum number of idle and active connections in the pool. |
|
|
The maximum lifetime of a connection. When a connection reaches this lifetime it is removed, regardless of how recently it has been active. |
|
|
The maximum size of the JDBC data source cache. |
|
|
The expiration time of a cached data source when it is no longer accessed. |
|
Caching table projections#
The connector supports table scan redirection to improve performance and reduce load on the data source.
Table statistics#
You can use ANALYZE statements in SEP to populate the table statistics in Vertica. The cost-based optimizer then uses these statistics to improve query performance.
Support for table statistics is disabled by default. You can enable it with the
catalog property statistics.enabled
set to true
. In addition, the
connection-user
configured in the catalog must have superuser permissions in
Vertica to gather and populate statistics.
You can view statistics in SEP using SHOW STATS.
Security#
The connector includes a number of security-related features, detailed in the following sections.
User impersonation#
The connector supports user impersonation.
Enable user impersonation by setting the vertica.impersonation.enabled
property in the catalog properties file to true
:
vertica.impersonation.enabled=true
User impersonation in the connector is based on the SET ROLE command
supported in Vertica.
Prior to setting the impersonated role, SET ROLE NONE
is executed to clear
any roles that have been already set, so only the impersonated role is used.
Password credential pass-through#
The connector supports password credential pass-through. To enable it, edit the catalog properties file to include the authentication type:
vertica.authentication.type=PASSWORD_PASS_THROUGH
For more information about configurations and limitations, see Password credential pass-through.