Databricks goes native on Excel. You can now ingest + query .xls/.xlsx directly in Databricks (SQL + PySpark, batch and streaming), with auto schema/type inference, sheet + cell-range targeting, and evaluated formulas, no extra libraries anymore.
Our final webinar of December is here and we are closing the year with a powerhouse session!SpeakersAs many organisations still get stuck in the PoC phase, we’re bringing clarity, structure, and real delivery practices to help teams move from promi...
Appreciate you sharing this with the community, @bianca_unifeye!
I have a Databricks App I need to integrate with volumes using local python os functions. I've setup a simple test: def __init__(self, config: ObjectStoreConfig): self.config = config # Ensure our required paths are created ...
I also cannot read from a Volume from a databricks app and would be interested in a solution
I’m exploring how to handle real-time data for an application and I keep seeing Databricks recommended as a strong option — especially with its support for streaming pipelines, Delta Live Tables, and integrations with various event sources. That said...
Databricks is very effective for real-time app data because it supports streaming data processing using Apache Spark and Delta Lake. It helps handle large data volumes, provides low-latency analytics, and makes it easier to build scalable event-drive...
Hello - I am following some online code to create a function as follows:-----------------------------------------CREATE OR REPLACE FUNCTION my_catalog.my_schema.insert_data_function(col1_value STRING,col2_value INT)RETURNS BOOLEANCOMMENT 'Inserts dat...
Hi @greengil ,You can't use functions to modify data. They're intended to return scalar value or table. If you need to modify content of a table use stored procedure instead.
I was wondering if there's a way to alter table and add/update comments for multiple columns at once using SQL or API calls. For instance - ALTER TABLE <table_name> CHANGE COLUMN <col1> COMMENT '<comment1>',CHANGE COLUMN <col2> COMMENT 'comment2' ; ...
The correct SQL syntax for this is:ALTER TABLE your_table_name ALTER COLUMN col1 COMMENT 'comment1', col2 COMMENT 'comment2', col3 COMMENT 'comment3';
Tags, whether manually assigned or automatically assigned by the “data classification” service, can be protected using policies. Column masking can automatically mask columns with a given tag for all except some with elevated access.
Hi everyone,I’m exploring ways to leverage Databricks for building data-driven web and mobile applications and wanted to get some insights from this community. Databricks is great for processing large datasets, running analytics, and building machine...
Check Databricks Apps - you pass databricks resources and then use databricks-sdk to interact with them.
Data classification automatically tags Unity Catalog tables and is now available in system tables as well.
Getting into the data space can feel overwhelming, with so many tools, terms, and technologies. But after years inExpect failure. Design for it.Jobs will fail. The data will be late. Build systems that can recover gracefully, and continually monitor ...
Hi @boitumelodikoko A few more principles I always share with people entering the data space:Observability is non-negotiable.If you can’t see what your pipelines are doing, you can’t fix what breaks.Good logging, metrics, and alerts save countless ho...
Databricks is positioning the platform as a full stack for LLM development — from data ingestion → feature/embedding pipelines → fine-tuning (Mosaic AI) → evaluation → deployment (Model Serving) → monitoring (Lakehouse Monitoring).I’m curious about r...
Hi @Poorva21 In several projects I’ve seen and worked on, Databricks gets you very close to a full end-to-end LLMOps platform, but not completely. It realistically covers most of the lifecycle, but in real production setups you still complement it wi...
Imagine all a data engineer or analyst needs to do to read from a REST API is use spark.read(), no direct request calls, no manual JSON parsing - just spark .read. That’s the power of a custom Spark Data Source. Soon, we will see a surge of open-sour...
DBX is one of the most crucial projects of dblabs this year, and we can expect that more and more great checks from it will be supported natively in databricks. More about dbx on https://databrickslabs.github.io/dqx/
I'm using Job cluster and created compute policies for library management and now I'm trying to use pools in databricks. I'm getting error like this : Cluster validation error: Validation failed for azure_attributes.spot_bid_max_price from pool, the ...
This error occurs because instance pools require a concrete spot bid max price value, even if the cluster policy marks it as unlimited. Set an explicit value (e.g., 100) directly in the instance pool configuration, or switch the pool to on-demand nod...
I'm running a DBR/Spark job using a container. I've set docker_image.url to `docker.io/databricksruntime/standard:13.3-LTS`, as well as the Spark env var `DATABRICKS_RUNTIME_VERSION=13.3`. At runtime, however, I'm encountering this error: ImportError...
Go to Compute → Your Cluster / Job ComputeChange Databricks Runtime to:Databricks Runtime 13.3 LTSRe-run your job with the same container.
