We would like to avoid confusion like we have in webpack-contrib/webpack-bundle-analyzer#185

We could document statsFilename and reportFilename options allowing the use of an absolute file path like /path/to/folder so that people would know it's supported.

Let us know in this issue if you would like to contribute to this!

Most items coming from questions on the community forum

• a proper multicategory bar example based on https://community.plotly.com/t/multicategory-axis-type-example/26392
• example of shape or annotation covering several subplots thanks to xref='paper'. Also the shapes and annotations tutorial should link to each other.
• orthographic projection example in 3d axes tutorial (or

potential api example

bit fix undo-commit
bit fix untrack-file
bit fix rename-commit
bit fix catch-up-to-branch

Given a stream s1 that contains a NULL value:

CREATE STREAM s1 (x INTEGER) ...
INSERT INTO s1 (x) VALUES (null);

If that NULL expression is used in an arithmetic operation, the result of the operation will be NULL:

SELECT x + 1 FROM s1 EMIT CHANGES;

However, if a NULL literal is used in the same way, an NPE will be thrown:

ksql> SELECT NULL + 1 FROM

To improve the quality of our end-to-end testing code, we want to create lint checks for common bad practices. If you would like to help with this issue, please leave a comment on this issue with the task you want to work on.

How to Write E2E Lint Checks

1. First think about how you can identify the bad practice based solely on the text of the code. Imagine you get a code file as a string

So that you can run the tests over and over, without filling your computer's memory.

Take a look at https://github.com/fonsp/Pluto.jl/tree/main/test/frontend and run the tests to learn more about our frontend tests

Hey everyone!

mapd-core-cpu is already available on conda-forge (https://anaconda.org/conda-forge/omniscidb-cpu)

now we should add some instructions on the documentation.

at this moment it is available for linux and osx.

some additional information about the configuration:

1. for now, always install omniscidb-cpu inside a conda environment (also it is a good practice), eg: