Starburst Netezza connector

The Starburst Netezza connector allows querying and creating tables in an external IBM Netezza Database.

Requirements

To connect to Netezza, you need:

• Netezza version 11.2.0.0 or higher.

• Network access from the coordinator and workers to the Netezza Server. Port 5480 is the default port.

• Netezza JDBC driver, downloaded from IBM Fix Central.

• A valid Starburst Enterprise license.

Configuration

You need to add the JDBC driver, before creating catalogs:

1. Obtain the Netezza JDBC driver.

2. Add the JDBC JAR file to the SEP plugin/netezza directory on the coordinator and all workers.

3. Restart SEP on every node.

Create a catalog properties file in etc/catalog named example.properties to access the configured Netezza 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 netezza and replace the connection properties as appropriate for your setup.

connector.name=netezza
connection-url=jdbc:netezza://example.net:5480/database
connection-user=admin
connection-password=secret

More information about the supported JDBC URL format and parameters of the Netezza JDBC driver is available in the Netezza documentation.

General configuration properties

The following table describes general catalog configuration properties for the connector:

Property name	Description	Default value
case-insensitive-name-matching	Support case insensitive schema and table names.	false
case-insensitive-name-matching.cache-ttl	This value should be a duration.	1m
case-insensitive-name-matching.config-file	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.	null
case-insensitive-name-matching.config-file.refresh-period	Frequency with which Trino checks the name matching configuration file for changes. This value should be a duration.	(refresh disabled)
metadata.cache-ttl	The duration for which metadata, including table and column statistics, is cached.	0s (caching disabled)
metadata.cache-missing	Cache the fact that metadata, including table and column statistics, is not available	false
metadata.cache-maximum-size	Maximum number of objects stored in the metadata cache	10000
write.batch-size	Maximum number of statements in a batched execution. Do not change this setting from the default. Non-default values may negatively impact performance.	1000
dynamic-filtering.enabled	Push down dynamic filters into JDBC queries	true
dynamic-filtering.wait-timeout	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.	20s

Type mapping

Because Trino and Netezza each support types that the other does not, this connector modifies some types when reading data.

Netezza to Trino type mapping

The connector maps Netezza types to the corresponding Trino types according to the following table:

Netezza to Trino read type mapping

Netezza type	Trino type	Notes
BOOLEAN, BOOL	BOOLEAN
BYTEINT, INT1	TINYINT
SMALLINT, INT2	SMALLINT
INTEGER, INT, INT4	INTEGER
BIGINT, INT8	BIGINT
DOUBLE PRECISION	DOUBLE
REAL, FLOAT(p)	REAL	Special values Infinity, -Infinity, and NaN are supported.
NUMERIC,(p, s), NUMERIC(p), NUMERIC, DECIMAL(p, s)	DECIMAL(p, s)
CHARACTER(n), CHAR(n), NCHAR(n)	CHAR(n)
CHARACTER VARYING(n), VARCHAR(n), NVARCHAR(n)	VARCHAR(n)
VARBINARY(n)	VARBINARY	ST_GEOMETRY(n) is not supported.
DATE	DATE
TIME	TIME(6)
TIME WITH TIME ZONE	TIME(6) WITH TIME ZONE
TIMESTAMP	TIMESTAMP(6)
JSON, JSONB	JSON

No other types are supported.

SQL support

The connector provides read and write access to data and metadata in the Netezza database. In addition to the globally available and read operation statements, the connector supports the following features:

• INSERT

• DELETE

• CREATE TABLE

• CREATE TABLE AS

• DROP TABLE

• ALTER TABLE

• CREATE SCHEMA

• DROP SCHEMA

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

The 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']);

SEP to Netezza write type mapping

The following write type mapping applies when tables are created in Netezza from SEP.

SEP to Netezza write type mapping

SEP type	Netezza type	Notes
BOOLEAN	BOOLEAN
TINYINT	BYTEINT
SMALLINT	SMALLINT
INTEGER	INTEGER
BIGINT	BIGINT
REAL	REAL
DOUBLE	DOUBLE PRECISION
DECIMAL(p, s)	DECIMAL(p, s)
CHAR(n)	NCHAR(n)	max n is 16,000
VARCHAR	NVARCHAR(n)	max n is 16,000
VARBINARY	VARBINARY(64000)
DATE	DATE
TIME, TIME(p)	TIME	max supported precision is 6
TIME WITH TIME ZONE, TIME(p) WITH TIME ZONE	TIME WITH TIME ZONE	max supported precision is 6
TIMESTAMP, TIMESTAMP(p)	TIMESTAMP	max supported precision is 6, TIMESTAMP WITH TIME ZONE is not supported
JSON	JSONB

No other type is 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
unsupported-type-handling	Configure how unsupported column data types are handled: IGNORE, column is not accessible. CONVERT_TO_VARCHAR, column is converted to unbounded VARCHAR. The respective catalog session property is unsupported_type_handling.	IGNORE
jdbc-types-mapped-to-varchar	Allow forced mapping of comma separated lists of data types to convert to unbounded VARCHAR

Table functions

The connector provides specific table functions to access Netezza.

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 Netezza 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.

Table statistics

The Netezza 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 Netezza and retrieved by the connector. Read more in Netezza documentation.

Managed statistics

The connector supports Managed statistics allowing SEP to 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 a number of operations:

• Join pushdown

• Limit pushdown

• Top-N pushdown

Aggregate pushdown for the following functions:

• avg()

• count(), also count(distinct x)

• max()

• min()

• sum()

• stddev() and stddev_samp()

• stddev_pop()

• variance() and var_samp()

• var_pop()

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
join-pushdown.enabled	Enable join pushdown. Equivalent catalog session property is join_pushdown_enabled.	true
join-pushdown.strategy	Strategy used to evaluate whether join operations are pushed down. Set to AUTOMATIC to enable cost-based join pushdown, or EAGER to push down joins whenever possible. Note that EAGER can push down joins even when table statistics are unavailable, which may result in degraded query performance. Because of this, EAGER is only recommended for testing and troubleshooting purposes.	AUTOMATIC

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:

JDBC connection pooling catalog configuration properties

Property name	Description	Default value
connection-pool.enabled	Enable connection pooling for the catalog.	false
connection-pool.max-size	The maximum number of idle and active connections in the pool.	10
connection-pool.max-connection-lifetime	The maximum lifetime of a connection. When a connection reaches this lifetime it is removed, regardless of how recently it has been active.	30m
connection-pool.pool-cache-max-size	The maximum size of the JDBC data source cache.	1000
connection-pool.pool-cache-ttl	The expiration time of a cached data source when it is no longer accessed.	30m

Starburst Cached Views

The connector supports table scan redirection to improve performance and reduce load on the data source.

Security

The connector includes a number of security-related features, detailed in the following sections.

Kerberos authentication

The connector supports Kerberos authentication. Use the following properties in the catalog properties file to configure it.

netezza.authentication.type=KERBEROS
kerberos.client.principal=example@example.com
kerberos.client.keytab=etc/kerberos/example.keytab
kerberos.config=etc/kerberos/krb5.conf

In this example the user example@example.com, as defined in the kerberos.client.principal property, is used to connect to the database. The related Kerberos service ticket is located in the file defined in the kerberos.client.keytab property.

Kerberos credential pass-through

The connector can be configured to pass through Kerberos credentials, received by SEP, to the Netezza database. This allows you to apply Kerberos-defined permissions to Netezza connections through SEP.

To configure credential pass-through in Kerberos and SEP, see Kerberos credential pass-through.

After you configure Kerberos and SEP, edit the catalog properties file to enable the connector to pass the credentials to the Netezza database. Configure the following Kerberos client configuration properties in the catalog properties file:

netezza.authentication.type=KERBEROS_PASS_THROUGH
http.authentication.krb5.config=/etc/krb5.conf
http-server.authentication.krb5.service-name=exampleServiceName
http-server.authentication.krb5.keytab=/path/to/Keytab/File

Any Netezza database accessed using SEP is now subject to the Kerberos-defined data access restrictions and permissions.

Password credential pass-through

The connector supports password credential pass-through. To enable it, edit the catalog properties file to include the authentication type:

netezza.authentication.type=PASSWORD_PASS_THROUGH

For more information about configurations and limitations, see Password credential pass-through.

User impersonation

The Netezza connector supports user impersonation.

User impersonation can be enabled in the catalog properties file:

netezza.impersonation.enabled=true

User impersonation in the connector is based on Netezza’s masquerading feature, which uses the EXECUTE AS command. For more information, see Netezza masquerading.