Known Issues and Limitations

Following are known issues, limitations, and changes to default behavior in HEAVY.AI.


HeavyDB supports only Web Mercator projection

Because HeavyDB supports Web Mercator projection only, applications that use coordinates other than Web Mercator may not render data accurately on their maps.

Variable length types are not supported when performing columnar conversion

Whenever the result of a query is going to be used for another query (for example, CREATE TABLE AS SELECT, any multi-step query, and so on), HEAVY.AI performs columnar conversion to change the intermediate results into proper columnar format that all HEAVY.AI queries expect as input. Variable length types, including all geometry targets, are not supported when performing columnar conversion.

Do not set BLOSC_* environment variables

HEAVY.AI uses a compression library called BLOSC that reads operating system environment variables and changes behavior according to those variables. Do not set any of the environment variables listed below.


OPTIMIZE TABLE with VACUUM increases metadata

The with (vacuum = 'true') option has the suboptimal effect of increasing the size of your metadata in HEAVY.AI Core version 4.5.0. Do not use the vacuum option.

ALTER TABLE ADD COLUMN does not work with geo column type

ALTER TABLE ADD COLUMN for a geo column type in MapD 4.1 only partially adds the column. Any queries on that column will result in a system failure. If you encounter this issue, contact HEAVY.AI support at

This issue was fixed in MapD version 4.1.1.

MapD 4.0 backward compatibility with MapD 3.x

MapD 4.0 includes several major changes that can affect compatibility with 3.x releases.

MapD recommends you make a backup of your 3.x installations before proceeding with the upgrade to MapD 4.0 so that you can revert if the upgrade is unsuccessful or problematic.

For assistance during the upgrade process, contact HEAVY.AI support at before you upgrade your system.

Migration from releases 3.2.1, 3.2.2, or 3.2.3

There is a known issue with automatic migration if the source database was migrated through any of the following releases: 3.2.1, 3.2.2 or 3.2.3. Contact HEAVY.AI support before you update to v4.0.0 if you think this is the case with your database.

Object permissions and role-based access control on by default in MapD 4.0

If you are using MapD 3.x, setting up MapD 4.0 over an existing 3.x installation data directory migrates existing users and databases to use the new model automatically.

If you encounter issues during upgrade, you must restore your 3.x installation data from backup. Back up your 3.x installations before upgrading to MapD 4.0. You cannot downgrade MapD 4.0 data directories to use them in MapD 3.x installations.

Possible integer overflow on select count(*) for tables with more than 2^32 rows

To prevent return of negative counts, set bigint-count = true in heavyai.conf.

DELETE works only on tables created using MapD 4.0 or later

DELETE functionality does not work on tables created using MapD 3.x. For DELETE to function correctly, create a new table in MapD 4.0 with the same schema, and then copy the data.

NOTE: To remove all rows from a table, use TRUNCATE TABLE instead of DELETE * FROM

UPDATE limitations

  • HEAVY.AI does not currently support UPDATE from a subquery. For example, the following will not work:

    UPDATE tempDataView SET marks = ( SELECT marks FROM tempData b WHERE tempDataView.Name = b.Name )
  • UPDATE is not currently supported on variable-length data types.

CUDA error on NVIDIA DGX systems

On NVIDIA DGX systems, you might get the following error:

2021-05-14T15:56:16.571249 E 40446 0 DBHandler.cpp:403 Unable to instantiate CudaMgr, falling back to CPU-only mode. CUDA Error (999): unknown error

This error occurs if no fabric manager is installed on the system. To resolve the issue, install the fabric manager on the system.

HEAVY.AI Rendering Engine

Potential deadlock when handling table modify statements while a render is in flight

In OmniSci 5.1.2, a deadlock can result if a render_vega request is executed at the same time as a table modification request (DROP/TRUNCATE/RENAME/APPEND TABLE) and the same table is referenced in both requests.

This is scheduled to be fixed in a future release. Until that time, HEAVY.AI recommends that you avoid executing a table modification request at the same time as a render_vega request against the same table.

Sizing points by meters at large zoom levels introduces error

When evaluating the new convert_meters_to_pixel_width and convert_meters_to_pixel_height extension functions for accuracy against circular polygons created with ST_Buffer in other packages, some errors are introduced by the extension functions somewhere at large zoom levels.

The resulting point/symbol sized by meters is just an approximate. It does not represent the exact area on the globe. There is more error in the approximate as you get closer to the poles in a mercator-projected view: a circle defined in meters should become egg-shaped, whereas the current symbol remains elliptical.

Workaround: If your clients are going to use these extension functions, HEAVY.AI recommends you use the legacysymbol vega mark type if the size in meters is large and zooming in close is useful for your analysis.

MapD 3.x shapefiles must be reimported for MapD 4.0

If you imported shapefiles into MapD 3.x, you must reimport this data in MapD 4.0 to use the new storage model for geospatial data types. Identify the tables you need to reimport and do so before using MapD 4.0.

Migrate custom client polygon rendering and hit-testing for MapD 4.0

If you imported polygon data into MapD 3.x for a custom application and are rendering or performing hit-testing on that data, upgrading to OmniSci 4.0+ will break your client-side polygon code because the storage model is different. For guidelines on migrating your code for OmniSci 4.0, see Migrating Polygon Rendering and Hit-testing for Custom Clients Upgrading to OmniSci 4.0+.

Heavy Immerse

Parameters and geo-join failure

In Release 5.6.0, parameters do not work with geo joins.

High-precision timestamp limitation

You can import higher-precision timestamps (3, 6, 9, milli, micro, nano, rather than the default of seconds) via the data manager, but you cannot use them as a part of the actual queries or filters for a chart (as opposed to displaying them as results). For example, you cannot use a high-precision timestamp as the time dimension for a combo chart.

Dashboard sharing limitations

  • In MapD 4.0, dashboards can be shared only as 'read-only'. Users with whom a dashboard has been shared cannot currently make edits to the dashboard.

  • For security reasons, dashboard sharing does not automatically provide permissions on underlying tables/views. For now, this requires a one-time setup by a superuser/administrative to configure a group of users or a role with permissions on the underlying objects.

  • Dashboard sharing does not currently work in HEAVY.AI Cloud because each HEAVY.AI Cloud user currently has a dedicated HEAVY.AI instance. This limitation will be addressed in a future release.

Dashboards loaded by ID instead of name

If your OmniSci instance is set up to autoload specific dashboards on login by specifying the name in servers.json, you need to update the entry to use the dashboard ID instead. If you do not, your dashboards will not autoload. Find the dashboard ID by running `\dash` from omnisql, and then update the servers.json entry accordingly:

     "database": "omnisci",
     "master": "true",
     "username": "user",
     "password": "HyperInteractive",
     "url": "",
     "loadDashboard": "740",
     "GTM": "GTM-MDD8888"

Immerse backward compatibility

MapD Immerse versions 3.4.0 and higher work only with MapD Core versions 3.4.0 and higher.

Unexpected update queries for Line and Histogram charts

Any update on Line or Histogram charts also starts an update query for range chart that is not required.

Unexpected render of complex data fields exported to CSV format

Binned columns and date extracts appear as JSON strings when exported to CSV format.

Adding layers in the Pointmap chart does not work when using Firefox browser

Sorting by non-grouped column in a table chart might not work properly in a distributed configuration

Old share links (for example,\ no longer load and render all charts immediately. You must resize the browser or otherwise cause the page to re-render to see all charts.

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