Release 0.69

The following config properties must be removed from the file on both the coordinator and workers:

• presto-metastore.db.type

• presto-metastore.db.filename

Additionally, the datasources property is now deprecated and should also be removed (see Datasource Configuration).

We have a new config property, node-scheduler.include-coordinator, that allows or disallows scheduling work on the coordinator. Previously, tasks like final aggregations could be scheduled on the coordinator. For larger clusters, processing work on the coordinator can impact query performance because the machine’s resources are not available for the critical task of scheduling, managing and monitoring query execution.

Datasource Configuration

The datasources config property has been deprecated. Please remove it from your etc/config.properties file. The datasources configuration is now automatically generated based on the node-scheduler.include-coordinator property (see Prevent Scheduling Work on Coordinator).

Presto has an extremely experimental connector that was previously called the native connector and was intertwined with the main Presto code (it was written before Presto had connectors). This connector is now named and lives in a separate plugin.

As part of this refactoring, the presto-metastore.db.type and presto-metastore.db.filename config properties no longer exist and must be removed from etc/config.properties.

The Raptor connector stores data on the Presto machines in a columnar format using the same layout that Presto uses for in-memory data. Currently, it has major limitations: lack of replication, dropping a table does not reclaim the storage, etc. It is only suitable for experimentation, temporary tables, caching of data from slower connectors, etc. The metadata and data formats are subject to change in incompatible ways between releases.

If you would like to experiment with the connector, create a catalog properties file such as etc/catalog/raptor.properties on both the coordinator and workers that contains the following:

Machine Learning Functions

SELECT evaluate_classifier_predictions(label, classify(features, model))
FROM (
    SELECT learn_classifier(label, features) AS model
)

In the above example, the column label is a bigint and the column features is a map of feature identifiers to feature values. The feature identifiers must be integers (encoded as strings because JSON only supports strings for map keys) and the feature values are numbers (floating point).

Presto now supports the varbinary type for variable length binary data. Currently, the only supported function is length(). The Hive connector now maps the Hive BINARY type to varbinary.

General Changes

• Add missing operator: timestamp with time zone - interval year to month

• Support explaining sampled queries

• Add JMX stats for abandoned and canceled queries

• Improve error categorization in event logging