In Big Query there is a function array_concat_agg that aggregates array fields by concatenating the arrays. In Snowflake there is a flatten function that can unnest nested arrays into single array. I am looking for similar functionality in duckdb.

select flatten([[1, 2], [2, 3], [4, 5]] would return [1, 2, 2, 3, 4, 5]
I would also need a distinct option:
`select flatten(DISTINCT [[1, 2],

add stop instructions

Proposed changes

Issue Number: close #xxx

Problem Summary:

Describe the overview of changes.

Checklist(Required)

1. Does it affect the original behavior: (Yes/No/I Don't know)
2. Has unit tests been added: (Yes/No/No Need)
3. Has document been added or modified: (Yes/No/No Need)
4. Does it need to update dependencies: (Yes/No)
5. Are there any ch

Use case:
Add the ability to search for an element in an array and retrieve back the array index.
As per the PostgreSQL documentation:

array_position ( anycompatiblearray, anycompatible [, integer ] ) → integer

Returns the subscript of the first occurrence of the second argument in the array, or NULL if it's not present

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:

we should delete following files:

be/src/util/perf_counters.h
be/src/util/perf_counters.cpp

Welcome newcomers to solve this issue

Describe the bug
If the column names in a CSV file are uppercase, then typing lowercase column names in SQL queries will result in an Error: Invalid identifier for schema.

To Reproduce
Here is a simple example program that runs a query on 2 tables.

#[tokio::main]
async fn main() -> datafusion::error::Result<()> {
    let mut ctx = ExecutionContext::new();
    ctx.regis

In risinglightdb/risinglight@38482e0, we added insert / create column name by simply setting the data chunk header. In the future, the column name should always be derived in planner (optimizer).

AOE v0.1.0 limitations:

1. AOE has a global hard limit of ? table count.
2. AOE has a hard limit of ? columns per table.