Cloudera Docs

Known issues and limitations in Data Visualization 7.1.0

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
When downloading CSV and Excel files using legacy Arcengine, Impala, or Hive connections only headers are visible
Workaround:
To resolve this issue, switch to non-legacy connections.
Versions affected:
CDV 7.0.3 - 7.1.0
Fixed in version:
Cloudera Data Visualization 7.1.1
Cloudera issue:
VIZ-1555
Filters breaking on spaces and special characters
Filters with column names that contain spaces or special characters return a syntax error when added to the dashboard or to a visual’s shelves.
Workaround:
To resolve this issue, bracket the column names affected in the filter’s expression editor.
Versions affected:
Cloudera Data Visualization 7.0.5 - 7.1.1
Fixed in version:
Cloudera Data Visualization 7.1.0-b3
Cloudera issue:
VIZ-1876, VIZ-1896
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
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