What's new in Cloudera Data Warehouse on premises 1.5.5 SP4

Cloudera Data Warehouse on premises

OpenTelemetry export support

Cloudera Data Warehouse introduces the Enable OpenTelemetry export feature to streamline workload monitoring across your Virtual Warehouses. Administrators can now easily configure Hive and Impala Virtual Warehouses to route telemetry metrics and traces directly to the Cloudera Control Plane's OpenTelemetry gateway from a single setting. By unifying telemetry collection into a centralized pipeline, this feature eliminates the need to manually set up each Virtual Warehouse individually, simplifying observability management, speeding up issue diagnosis, and delivering seamless operational insights across your environment. For more information, see Enabling OpenTelemetry export.

Configuration change notifications integrated with Cloudera Management Console

Cloudera Data Warehouse now integrates with the Cloudera Management Console notification service to send real time alerts when Virtual Warehouse configuration changes occur. When configuration change detection is active, notification events, such as updates to Kerberos configurations or security certificates, are automatically pushed to the Cloudera Control Plane. Users and administrators can view and track these notification events directly within the Cloudera Management Console Notifications page or from the top right notification bell menu. This provides central visibility and enhanced tracking for critical system and security configuration updates across your environments. For more information, see Receiving notifications.

Add specific stable labels to Cloudera Data Warehouse workload namespaces

Cloudera Data Warehouse now automatically applies stable and static labels to the enclosing namespaces of all Cloudera Data Warehouse workload pods. Previously, labeling was limited to individual pods, which could cause increased load when third-party applications or webhooks filtered on pod attributes. With this update, namespaces for Impala, Hive, and Trino Virtual Warehouses, Database Catalogs, and Hue instances are automatically tagged using the [cdw.cloudera.com/application](https://cdw.cloudera.com/application):<application_name> format, enabling seamless third-party integration and more precise resource filtering across your clusters. For more information, see List of labels for third-party integration.

Integrate with Velero-based Disaster Recovery Service (DRS)

Cloudera Data Warehouse introduces enhanced DRS capabilities that support Velero-based backup and restore operations for Cloudera Data Warehouse workloads. The Cloudera Data Warehouse server now supports backing up all Virtual Warehouses, Cloudera Data Visualization, and shared Cloudera Data Explorer (Hue) instances so that they are automatically included in backup snapshots. You can now restore Cloudera Data Explorer (Hue) workloads onto a secondary ECS cluster, provided the target cluster is connected to the same base cluster as the source.

Cloudera Data Visualization updated to version 8.1.4

The Cloudera Data Visualization component included in Cloudera Data Warehouse is updated to version 8.1.4.1000-4. This update brings the latest improvements, bug fixes, and enhancements from the Cloudera Data Visualization 8.1.4 release to Cloudera Data Warehouse, including a refreshed look across the product with updated colors, fonts, borders, and spacing. Additionally, this update addresses security vulnerabilities to ensure the component is completely CVE 2026 85046 KEV free.

Enrolling Cloudera Data Warehouse Virtual Warehouse namespaces into Istio service mesh

Cloudera Data Warehouse now supports enrolling Virtual Warehouse namespaces into an Istio service mesh to enforce mutual TLS (mTLS) security across workload pods. You can configure service mesh enrollment by updating the istio-mesh-mode property in the Cloudera Data Warehouse ConfigMap to enable ambient mode for transparent layer 4 and layer 7 policy enforcement. When enabled, STRICT mTLS is automatically applied across all Virtual Warehouse services while maintaining Prometheus metrics accessibility. For more information, see Istio service mesh integration.

What's new in Cloudera Data Explorer (Hue) on Cloudera Data Warehouse on premises

Enhanced session security for Cloudera Data Explorer (Hue)

Data Explorer now includes security for the session ID (sessionid) cookie. This enhancement helps prevent unauthorized access results in data exposure, unauthorized query execution, and job submission across connected Data Explorer services.

For more information, see Securing sessions .

Data Explorer Query Processor JDK 17 upgrade

Data Explorer Query Processor supports JDK 17. Upgrading to JDK 17 ensures your application stays competitive and maintainable by providing improved performance, increased security, modern language features, and long-term support.

What's new in Hive on Cloudera Data Warehouse on premises

There are no new features in this release.

What's new in Iceberg on Cloudera Data Warehouse on premises

Trino Iceberg deletion vector support

Trino supports deletion vectors on Iceberg V3 tables. In Iceberg format version 3, deletion vectors in Puffin files replace the positional delete files used for row-level deletes in Iceberg format version 2. For a row-level DELETE, Trino records deletions in a Roaring Bitmap Deletion Vector paired with the data file instead of creating many small position delete files corresponding a single data file, which reduces small-file overhead and speeds up reads. During query execution, Trino loads the deletion vector and skips rows marked deleted in the bitmap. You can upgrade a format version 2 table with ALTER TABLE … SET PROPERTIES format_version = 3. After this upgrade, delete files written in format version 2 remain until you compact the table. ALTER TABLE … EXECUTE compacts the table and optimizes small data files and removes deleted rows and refreshes statistics such as row counts and min/max values. Run ALTER TABLE … EXECUTE optimize and ANALYZE to update row counts, min/max, and NDV as needed.

Create an Iceberg V3 table with format_version = 3 in the WITH clause or upgrade by using ALTER TABLE … SET PROPERTIES with format_version = 3. For more information, see the “Add support for creating, writing to or deleting from Iceberg v3 tables” bullet point in Trino 480 release notes: Iceberg connector.

Trino Iceberg row lineage support

Trino supports row lineage on Iceberg V3 tables. Row lineage tracks row history using two metadata fields: $row_id, a unique identifier assigned when a row is inserted and $last_updated_sequence_number, the sequence number of the snapshot that appended or last changed the row. Query these columns in SELECT statements like other Iceberg metadata columns. UPDATE is implemented as delete and insert and keeps the original $row_id; $last_updated_sequence_number is set to the sequence number of the update operation. ALTER TABLE … EXECUTE optimize compacts files and carries forward $row_id and $last_updated_sequence_number.

Create an Iceberg V3 table with format_version = 3 in the WITH clause or upgrade by using ALTER TABLE … SET PROPERTIES with format_version = 3. For more information, see the “Add support for Iceberg v3 row lineage” bullet point in Trino 480 release notes: Iceberg connector.

What's new in Impala on Cloudera Data Warehouse on premises

Java 17 support for Impala in Cloudera Data Warehouse runtime containers

Java 17 is now the default Java runtime environment inside Docker images used for Impala in Cloudera Data Warehouse runtime containers. This update upgrades the Java runtime from Java 8 to Java 17 for Cloudera Data Warehouse on premises 1.5.5 SP4.

What's new in Trino on Cloudera Data Warehouse on premises

Trino runtime upgraded

The Trino runtime is upgraded from version 479 to 481.

This upgrade introduces stability improvements and performance optimizations.

Apache Kudu connector available in federation connectors

Trino supports the Apache Kudu connector as part of the federation connectors. You can query, insert, and delete data directly in Apache Kudu using Trino. See Apache Kudu connector support for Trino

Trino Lakehouse connector support

Cloudera Data Warehouse now supports the Trino Lakehouse connector starting with version 479. This update allows you to easily configure and manage Lakehouse connectors directly within the Trino UI, complete with integrated Apache Ranger properties for simplified security management and seamless cluster integration. For more information, see Trino Lakehouse connector.

Kerberos authentication for the Trino Oracle connector

The Trino Oracle connector now supports Kerberos authentication, so you can connect Trino to Kerberos-secured Oracle databases. For more information, see Configuring Kerberos authentication for the Oracle connector

Connection pooling for Hive and Impala federation connectors

Cloudera Data Warehouse now supports JDBC connection pooling for the Hive-jdbc and Impala federation connectors, extending the pooling already available for the MySQL, PostgreSQL, MariaDB, Teradata, and Oracle connectors. When pooling is enabled, a connector reuses physical JDBC connections instead of opening and closing one for every query, which reduces connection handshake latency and load on the target data source. Connection pooling is disabled by default; to enable it, set connection-pool.enabled to true in the connector configuration.

Configuring query-level fault tolerance and coordinator high availability for Trino

Cloudera Data Warehouse supports fault tolerance with query-level retry and Active-Passive coordinator high availability (HA) for Trino Virtual Warehouses. Query-level retry automatically reruns failed queries up to four times using in-memory buffer spooling, while Active-Passive HA deploys a standby coordinator to quickly take over if the active coordinator crashes or shuts down, ensuring continuous cluster availability. You can enable and configure both settings when creating or editing a Trino Virtual Warehouse in the Cloudera Data Warehouse web UI. For more information, see Configuring query-level fault tolerance for Trino.