Known issues and limitations in Data Visualization 7.1.2

Learn about the known issues and limitations that you might experience while using Cloudera Data Visualization. You can find information about the areas of impact, affected product versions, and possible workarounds.

Picklist in complex data types Show Selected unselects previous selections

Show selected in a filter list selection may not show all selections depending on the data type. A fix is expected in a future release.

Workaround

None

Versions affected

Cloudera Data Visualization 7.0.2 - 7.2.9

Fixed in version

N/A

Cloudera issue

VIZ-456

Inconsistent support for non-roman or character-based alphabets across visual types

Non-romanized or character-based alphabets are not consistently supported across various visual types. If not supported, the affected visual is not properly rendered in PDF/PNG downloads. CSV/Excel downloads and general dashboard viewing is available for all languages.

The following languages are not supported when using a table visual.

In CML:	In CDW:
Amharic (Ethiopia) Arabic (multiple countries) Bengali (Bangladesh) Berber (multiple countries) Burmese (Myanmar) Dari Pashto (Afghanistan) Dzongkha (Bhutan) Fijian (Fiji) Georgian Hebrew (Israel) Khmer (Cambodia) Lao Malay (Brunei) Many Indian languages Nepalese (Nepal) Persian (Iran) Tamil (Malaysia, India, Singapore) Thai (Thailand) Urdu (Pakistan)	Amharic (Ethiopia) Bengali (Bangladesh) Burmese (Myanmar) Dzongkha (Bhutan) Fijian (Fiji) Khmer (Cambodia) Many Indian languages Nepalese (Nepal) Tamil (Malaysia, India, Singapore) Thai (Thailand)

Workaround

None

Versions affected

Cloudera Data Visualization 7.0.2 - 7.2.9

Fixed in version

N/A

Cloudera issue

VIZ-984

Saved value does not show properly when arcapi is present

After the fix included for VIZ-1070, a known issue is still present when using arcapi.sendParameters with app-scope filters.

Workaround

None

Versions affected

Cloudera Data Visualization 7.0.2 - 7.2.9

Fixed in version

N/A

Cloudera issue

VIZ-1181

Upgrade snowflake-connector-python when the corresponding issue is fixed

For some characters, snowflake queries return "Failed to convert current row, cause: 'utf-8' codec can't decode byte" error (SNOW-182387: UTF-8 decoding exception when querying table in SNOWFLAKE_SAMPLE_DATA).

Workaround

None

Versions affected

Cloudera Data Visualization 7.0.0 - 7.2.9

Fixed in version

Cloudera Data Visualization 7.2.2

Cloudera issue

VIZ-1455

Importing visual artifacts can fail in some systems, even with the “Disregard artifacts that exist in other workspaces” option selected

Manually edit the UUID of objects in the exported JSON file with a suffix like ‘-import’.

Workaround:

To resolve this issue, manually edit the data connection to use impersonation if trusted impersonation is enabled.

Versions affected:

Cloudera Data Visualization 7.0.5 - 7.1.2

Fixed in version:

Cloudera Data Visualization 7.1.3

Cloudera issue:

VIZ-2050

Histogram visual fails with an execution error “e.map is not a function”

Workaround:

N/A

Versions affected:

Cloudera Data Visualization 6.2.6 - 7.1.4

Fixed in version:

Cloudera Data Visualization 7.1.4-b74

Cloudera issue:

VIZ-2058

Trusted impersonation does not work for Impala in Cloudera Datawarehouse on CDP Private Cloud

Impersonation should be the default setting used for these connections.

Workaround:

To resolve this issue, manually edit the data connection to use impersonation if trusted impersonation is enabled.

Versions affected:

Cloudera Data Visualization 7.1.1 - 7.1.2

Fixed in version:

Cloudera Data Visualization 7.1.3

Cloudera issue:

VIZ-2088

Issue with impersonation in CDW Impala connections

You may see the following error while creating or editing the data connection to a CDW Impala or Hive Virtual Warehouse and using the connection details auto-populated from the CDW Warehouse drop-down:

User <username> is not authorized to delegate to <username>.

This happens because the Impersonation and Trusted Impersonation options are both enabled.

Workaround:

If the message appears when creating a new data connection, try refreshing the page. This will reset the Impersonation and Trusted Impersonation options.

If the message appears on the Edit Data Connection modal, copy the hostname, username, HTTP path, and other values present on the Advanced tab, and manually edit the existing CDW Hive connections. A manual edit will typically not trigger this bug.

Versions affected:

Cloudera Data Visualization 7.1.1-7.1.5, CDV 7.1.6-b8

Fixed in version:

Cloudera Data Visualization 7.1.6.2-3

Cloudera issue:

VIZ-2269

Partitioned Cloudera Impala on premise extract tables cannot be updated

Tables in Cloudera Impala that are both partitioned and set as extract targets cannot be updated directly. This prevents operations such as dropping or adding new partitions.

Workaround:

Move the data to a new table that supports altering commands. Then replace the original extract table by renaming the newly created table. Optionally, you can create a backup of the original table before replacing it.

A sample SQL workflow is provided below. Customize the components marked in blue, while the remaining parts of the query are standard.

1. Create a temporary table (database_name.new_table_name) that supports altering.

   create table database_name.cdv_table_name_new (table_definition) partitioned by (partition_field string) tblproperties('transactional'='false');

2. Copy existing data from the original extract target.

   insert into database_name.cdv_table_name_new partition(partition_field) select * from database_name.cdv_table_name;

3. [Optional] Save the original extract target as a backup.

   alter table database_name.cdv_table_name rename to database_name.cdv_table_name_bak;

4. Make the temporary table the current extract target.

   alter table database_name.cdv_table_name_new rename to database_name.cdv_table_name;

Versions affected:

Cloudera Data Visualization 7.2.8 and all earlier versions

Fixed in version:

Cloudera Data Visualization 7.2.9

Cloudera issue:

VIZ-3042