Databend is a modern cloud data warehouse, serving your massive-scale analytics needs at low cost and complexity. Open source alternative to Snowflake. Also available in the cloud: https://app.databend.com .
What's On In Databend
Stay connected with the latest news about Databend.
Masking Policy
A masking policy refers to rules and settings that control the display or access to sensitive data in a way that safeguards confidentiality while allowing authorized users to interact with the data. Databend enables you to define masking policies for displaying sensitive columns in a table, thus protecting confidential data while still permitting authorized roles to access specific parts of the data.
-- Create a masking policy
CREATE MASKING POLICY email_mask
AS
(val string)
RETURNS string ->
CASE
WHEN current_role() IN ('MANAGERS') THEN
val
ELSE
'*********'
END
COMMENT = 'hide_email';
-- Associate the masking policy with the 'email' column
ALTER TABLE user_info MODIFY COLUMN email SET MASKING POLICY email_mask;
Masking Policy
If you are interested in learning more, please check out the resources listed below.
Code Corner
Discover some fascinating code snippets or projects that showcase our work or learning journey.
Adding show()
Method to Python Binding
show()
In Python packages such as PySpark, DuckDB, and DataFusion, the
show()
n
Recently, Databend has also implemented corresponding support for Python binding through PyO3. The code snippet is as follows:
#[pyo3(signature = (num=20))]
fn show(&self, py: Python, num: usize) -> PyResult<()> {
let blocks = self.collect(py)?;
let bs = self.get_box();
let result = blocks.box_render(num, bs.bs_max_width, bs.bs_max_width);
// Note that println! does not print to the Python debug console and is not visible in notebooks for instance
let print = py.import("builtins")?.getattr("print")?;
print.call1((result,))?;
Ok(())
}
If you are interested in learning more, please check out the resources listed below:
Highlights
We have also made these improvements to Databend that we hope you will find helpful:
- Added support for distributed .
REPLACE INTO
- Added support for the operator to calculate the L2 norm (Euclidean norm) of a vector.
<->
- Added Geo functions: ,
h3_to_center_child
,h3_exact_edge_length_m
,h3_exact_edge_length_km
,h3_exact_edge_length_rads
,h3_num_hexagons
,h3_line
,h3_distance
andh3_hex_ring
.h3_get_unidirectional_edge
- Read document Docs | ALTER TABLE COLUMN to learn how to modify a table by adding, converting, renaming, changing, or removing a column.
What's Up Next
We're always open to cutting-edge technologies and innovative ideas. You're more than welcome to join the community and bring them to Databend.
Adding Storage Backend Support for Hive Catalog
Previously, Databend's implementation of the Hive Catalog lacked support for configuring its own storage backend and could only fall back to the storage backend corresponding to the Default Catalog. This caused issues when the storage service pointed to by Hive MetaStore was inconsistent with the configuration of Default Catalog, resulting in an inability to read data.
Now there are plans to introduce
CONNECTION
CREATE CATALOG hive_ctl
TYPE=HIVE
HMS_ADDRESS='127.0.0.1:9083'
CONNECTION=(
URL='s3://warehouse/'
AWS_KEY_ID='admin'
AWS_SECRET_KEY='password'
ENDPOINT_URL='http://localhost:9000'
);
Issue #12407 | Feature: Add storage support for Hive catalog
Please let us know if you're interested in contributing to this feature, or pick up a good first issue at https://link.databend.com/i-m-feeling-lucky to get started.
New Contributors
We always open arms to everyone and can't wait to see how you'll help our community grow and thrive.
Changelog
You can check the changelog of Databend Nightly for details about our latest developments.
Full Changelog: https://github.com/databendlabs/databend/compare/v1.2.51-nightly...v1.2.62-nightly
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