- 261 Views
- 1 replies
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Creating links in embedded dashboards
I am curious what Databricks AI/BI's capabilities are in terms of linking out other dashboards in your dashboards. Can I create a text box that links out another dashboard? I noticed you can also create links in a pivot table. What will happen if I e...
- 261 Views
- 1 replies
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You can add a text widget to the canvas to insert hyperlinks to any URL, including other dashboards.In pivot tables, you can define URL paths for cell values from the Actions tab to make them clickable.For navigation within a dashboard, use “drill th...
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- 34 Views
- 1 replies
- 0 kudos
Attempting to Use VSCode Extension: Error: No sync destination found
Hello,I have the Databricks Extension + Databricks Connect Python module installed.I am connected to the target environment with a running cluster and I have all green checkmarks under the "Configuration" section.However, when testing a python file a...
- 34 Views
- 1 replies
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The error message "No sync destination found" when running your Python file in Databricks with the Extension and Databricks Connect module, even with all green configuration checkmarks, typically indicates a configuration issue with the sync destinat...
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- 8 Views
- 0 replies
- 0 kudos
Missing warehouse id/metadata for the system compute warehouse table
I ran the following queries for a specific warehouse_id = '54a93d2138433216' SELECT * FROM system.billing.usage WHERE usage_metadata.warehouse_id = '54a93d2138433216';SELECT * FROM system.compute.warehouse_events WHERE warehouse_id = '54a93d213843321...
- 8 Views
- 0 replies
- 0 kudos
- 30 Views
- 2 replies
- 0 kudos
What’s the easiest way to clean and transform data using PySpark in Databricks?
You have some raw data (like messy Excel files, CSVs, or logs) and you want to prepare it for analysis — by removing errors, fixing missing values, changing formats, or combining columns — using PySpark (Python for Apache Spark) inside Databricks.
- 30 Views
- 2 replies
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The easiest way to clean and transform data using PySpark in Databricks is by leveraging the DataFrame API. Start by loading data into a Spark DataFrame with spark.read. Use built-in functions like dropna, fillna, and withColumn to handle missing val...
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- 25 Views
- 0 replies
- 0 kudos
Python Async db connection to databricks
How to connect to azure databricks using sqlalchemy asynchronously
- 25 Views
- 0 replies
- 0 kudos
- 30 Views
- 0 replies
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Migration from Oracle DB in Linux server to Azure Databricks
Can anyone provide steps for the migration steps
- 30 Views
- 0 replies
- 0 kudos
- 43 Views
- 1 replies
- 0 kudos
How to Leverage Databricks for End-to-End AI Model Development
Hi everyone,I’m exploring how to use Databricks as a platform for end-to-end AI and machine learning model development, and I’d love to get insights from professionals and practitioners who have hands-on experience.Specifically, I’m curious about:Set...
- 43 Views
- 1 replies
- 0 kudos
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You can leverage Databricks for end-to-end AI model development by using its Lakehouse Platform, which unifies data engineering, analytics, and machine learning in one workspace. Start by ingesting and transforming data using Apache Spark and Delta L...
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- 2340 Views
- 4 replies
- 2 kudos
Resolved! Try Databricks sign up failed
Hi, I am trying to use Databricks with the community edition. However, when I tried to create an account, the sign-up failed after I completed the puzzle.
- 2340 Views
- 4 replies
- 2 kudos
- 73 Views
- 1 replies
- 1 kudos
- 73 Views
- 1 replies
- 1 kudos
- 1 kudos
We are going to need a little more information to better help you. What is the scenario? Louis
- 1 kudos
- 101 Views
- 1 replies
- 1 kudos
Why keep both Azure OpenAI and Databricks?
Hi everyone,I’m curious to hear your thoughts on the benefits of having both Azure OpenAI and Azure Databricks within the same ecosystem.From what I can see, Databricks provides a strong foundation for data engineering, governance, and model lifecycl...
- 101 Views
- 1 replies
- 1 kudos
- 1 kudos
Two use case I can think of is RAG:Use Databricks for vector indexing (e.g., via Delta Lake or FAISS) and Azure OpenAI for inference.Example: A chatbot that queries Databricks-hosted documents and uses GPT-4 for response generation.Agentic Workflows:...
- 1 kudos
- 107 Views
- 2 replies
- 1 kudos
Resolved! Ingesting data from APIs Like Shopify (for orders), Meta Ads, Google Ads etc
Hi,I am and trying to create some table by calling APIs of Shopify/Meta Ads/Google Ads and so on. Where will I make the API call ? Is making API calls in Notebooks considered standard way to ingest in these cases. I intend to make a daily call to ge...
- 107 Views
- 2 replies
- 1 kudos
- 59 Views
- 0 replies
- 2 kudos
Databricks One
Databricks One is a user interface designed for business users, giving them a single, intuitive entry point to interact with data and AI in Azure Databricks, without needing to navigate technical concepts such as clusters, queries, models, or noteboo...
- 59 Views
- 0 replies
- 2 kudos
- 74 Views
- 0 replies
- 0 kudos
SQL warehouse: A materialized view is the simplest and cost-efficient way to transform your data
Materialized views running on SQL warehouse are super cost-efficient, and additionally, it is a really simple and powerful data engineering tool - just be sure that Enzyme updates it incrementally. Read more: - https://databrickster.medium.com/sql-wa...
- 74 Views
- 0 replies
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- 80 Views
- 0 replies
- 1 kudos
The purpose of your All-Purpose Cluster
Small, hidden but useful cluster setting.You can set that no jobs are allowed on the all-purpose cluster.Or vice versa, you can set an all-purpose cluster that can be used only by jobs. read more: - https://databrickster.medium.com/purpose-for-your-...
- 80 Views
- 0 replies
- 1 kudos
- 106 Views
- 1 replies
- 1 kudos
How to Integrate Machine Learning Model Development with Databricks Workflows?
Hey everyone I’m currently exploring machine learning model development and I’m interested in understanding how to effectively integrate ML workflows within Databricks.Specifically, I’d like to hear from the community about:How do you structure ML pi...
- 106 Views
- 1 replies
- 1 kudos
- 1 kudos
You can integrate machine learning model development into Databricks Workflows pretty smoothly using the platform’s native tools. The main idea is to treat your ML lifecycle (data prep → training → evaluation → deployment) as a series of tasks within...
- 1 kudos
