SQL Server Big Data Clusters cumulative updates history

Applies to: yesSQL Server 2019 (15.x)

The following release notes apply to SQL Server 2019 Big Data Clusters. The article lists cumulative update information for all the releases of SQL Server Big Data Clusters.

For the latest release notes, see SQL Server Big Data Clusters platform release notes.

CU13 (September 2021)

Cumulative Update 13 (CU13) release for SQL Server Big Data Clusters.

Package version Image tag Contents
15.0.4178.15 [2019-CU13-ubuntu-20.04] SQL Server Big Data Clusters Cumulative Update 13

SQL Server Big Data Clusters CU13 includes important changes and capabilities:

CU12 (August 2021)

Cumulative Update 12 (CU12) release for SQL Server Big Data Clusters.

Package version Image tag Contents
15.0.4153.1 [2019-CU12-ubuntu-20.04] SQL Server Big Data Clusters Cumulative Update 12

SQL Server Big Data Clusters CU12 changes the operating system default python version from 3.5 to 3.6 on all its images. This has no impact on Spark and SQL Server Machine Learning Services, as those components use dedicated Python installations and don't rely on OS python.

CU11 (June 2021)

Cumulative Update 11 (CU11) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4138.2 [2019-CU11-ubuntu-20.04]

SQL Server Big Data Clusters CU11 includes important capabilities:

CU10 (April 2021)

Cumulative Update 10 (CU10) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4123.1 [2019-CU10-ubuntu-20.04]

SQL Server Big Data Clusters CU10 includes important capabilities:

CU9 (February 2021)

Cumulative Update 9 (CU9) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4102.2 [2019-CU9-ubuntu-16.04]

SQL Server Big Data Clusters CU9 includes important capabilities:

  • Support to configure BDC post deployment and provide increased visibility of system settings.

    Clusters using mssql-conf for SQL Server master instance configurations require additional steps after upgrading to CU9. Follow the instructions here.

  • Improved Azure Data CLI (azdata) experience for encryption at rest.

  • Ability to dynamically install Python Spark packages using virtual environments.

  • Upgraded software versions for most of our OSS components (Grafana, Kibana, FluentBit, etc.) to ensure BDC images are up to date with the latest enhancements and fixes. See Open-source software reference.

  • Other miscellaneous improvements and bug fixes.

OSS component versions

Project Version
collectd 5.12
InfluxDB 1.8.3
Elasticsearch 7.9.1
Fluent Bit 1.6.3
Grafana 7.3.1
Hadoop
HDFS DataNode
HDFS NameNode
3.1.4
Hive (Metastore) 2.3.7
3.0.0 (standalone)
3.1.2 (hive)
Kibana 7.9.1
Knox 1.4.0
Livy 0.7.0
opendistro-elasticsearch-security 1.10.1.0
Openresty (Nginx) 1.17.8.2
Spark 2.4.10
Telegraf 1.16.1
ZooKeeper 3.6.2

CU8-GDR(January 2021)

Cumulative Update 8 GDR (CU8-GDR) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4083.2 [2019-CU8-GDR2-ubuntu-16.04]

OSS component versions

The table below shows the open-source projects in use as of SQL Server 2019 (15.x) CU8 and prior.

Project Version
collectd 5.8.1
InfluxDB 1.7.6
Elasticsearch 7.0.1
Fluent Bit 1.1.1
Grafana 6.3.6
Hadoop
HDFS DataNode
HDFS NameNode
3.1.3+
Hive (Metastore) 2.3.7
Kibana 7.0.1
Knox 1.2.0
Livy 0.6.0
opendistro-elasticsearch-security 1.0.0.1
Openresty (Nginx) 1.15.8
Spark 2.4.6+
Telegraf 1.10.3
ZooKeeper 3.5.8

CU8 (September 2020)

Cumulative Update 8 (CU8) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4073.23 [2019-CU8-ubuntu-16.04]

This release includes several fixes and a couple of enhancements.

Added capabilities

CU6 (July 2020)

Cumulative Update 6 (CU6) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4053.23 [2019-CU6-ubuntu-16.04]

This release includes minor fixes and enhancements. The following articles include information related to these updates:

CU5 (June 2020)

Cumulative Update 5 (CU5) release for SQL Server Big Data Clusters.

Package version Image tag
15.0.4043.16 [2019-CU5-ubuntu-16.04]

Added capabilities

  • Support for Big Data Clusters deployment on Red Hat OpenShift. Support includes OpenShift container platform deployed on premises version 4.3 and up and Azure Red Hat OpenShift. See Deploy SQL Server Big Data Clusters on OpenShift
  • Updated the BDC deployment security model so privileged containers deployed as part of BDC are no longer required. In addition to non-privileged, containers are running as non-root user by default for all new deployments using SQL Server Big Data Clusters CU5.
  • Added support for deploying multiple big data clusters against an Active Directory domain.
  • Azure Data CLI (azdata) has its own semantic version, independent from the server. Any dependency between the client and the server version of azdata is removed. We recommend using the latest version for both client and server to ensure you are benefiting from latest enhancements and fixes.
  • Introduced two new stored procedures, sp_data_source_objects and sp_data_source_table_columns, to support introspection of certain External Data Sources. They can be used by customers directly via T-SQL for schema discovery and to see what tables are available to be virtualized. We leverage these changes in the External Table Wizard of the Data Virtualization Extension for Azure Data Studio, which allows you to create external tables from SQL Server, Oracle, MongoDB, and Teradata.
  • Added support to persist customizations performed in Grafana. Before CU5, customers would notice that any edits in Grafana configurations would be lost upon metricsui pod (that hosts Grafana dashboard) restart. This issue is fixed and all configurations are now persisted.
  • Fixed security issue related to the API used to collect pod and node metrics using Telegraf (hosted in the metricsdc pods). As a result of this change, Telegraf now requires a service account, cluster role, and cluster bindings to have the necessary permissions to collect the pod and node metrics. See Custer role required for pods and nodes metrics collection for more details.
  • Added two feature switches to control the collection of pod and node metrics. In case you are using different solutions for monitoring your Kubernetes infrastructure, you can turn off the built-in metrics collection for pods and host nodes by setting allowNodeMetricsCollection and allowPodMetricsCollection to false in control.json deployment configuration file. For OpenShift environments, these settings are set to false by default in the built-in deployment profiles, since collecting pod and node metrics required privileged capabilities.

CU4 (April 2020)

Cumulative Update 4 (CU4) release for SQL Server Big Data Clusters. The SQL Server Database Engine version for this release is 15.0.4033.1.

Package version Image tag
15.0.4033.1 [2019-CU4-ubuntu-16.04]

CU3 (March 2020)

Cumulative Update 3 (CU3) release for SQL Server Big Data Clusters. The SQL Server Database Engine version for this release is 15.0.4023.6.

Package version Image tag
15.0.4023.6 [2019-CU3-ubuntu-16.04]

Resolved issues

SQL Server Big Data Clusters CU3 resolves the following issues from previous releases.

CU2 (February 2020)

Cumulative Update 2 (CU2) release for SQL Server Big Data Clusters. The SQL Server Database Engine version for this release is 15.0.4013.40.

Package version Image tag
15.0.4013.40 [2019-CU2-ubuntu-16.04]

CU1 (January 2020)

Cumulative Update 1 (CU1) release for SQL Server Big Data Clusters. The SQL Server Database Engine version for this release is 15.0.4003.23.

Package version Image tag
15.0.4003.23 [2019-CU1-ubuntu-16.04]

GDR1 (November 2019)

SQL Server Big Data Clusters General Distribution Release 1 (GDR1) - introduces general availability for Big Data Clusters. The SQL Server Database Engine version for this release is 15.0.2070.34.

Package version Image tag
15.0.2070.34 [2019-GDR1-ubuntu-16.04]

SQL Server 2019 servicing updates

For current information about SQL Server servicing updates, see https://support.microsoft.com/help/4518398.

Next steps

For more information about SQL Server Big Data Clusters, see Introducing SQL Server 2019 Big Data Clusters