- 1267 Views
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Databricks Optimization Tips – What’s Your Secret?
When I first started working with Databricks, I was genuinely impressed by its potential. The seamless integration with Delta Lake, the power of PySpark, and the ability to process massive datasets at incredible speeds—it was truly impactful.Over tim...
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1. Try to remove cache() and persist() in the dataframe operations in the code base.2. Fully avoid driver operations like collect() and take() - the information from the executors are brought back to driver, which is highly network i/o overhead.3. Av...
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- 669 Views
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Request for a guest post
Hi, I hope you're doing well. My name is Prasanna. C, Digital Marketing Strategist at Express Analytics, a company that understands consumer behavior and provides analytics solutions and services to businesses. Express Analytics primarily offers...
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- 1336 Views
- 2 replies
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Automatic Liquid Clustering and PO
I spent some time to understand how to use automatic liquid clustering with dlt pipelines. Hope this can help you as well.Enable Predictive Optimization Use this code:# Enabling Automatic Liquid Clustering on a new table @dlt.table(cluster_by_auto=Tr...
- 1336 Views
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Hi @Addy0_, thanks for sharing how to set it for existing table. Unfortunately, I think ALTER cannot be used with materialized view and streaming tables defined in dlt pipelines.I was looking for something similar to @dlt.table(cluster_by_auto=True, ...
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- 685 Views
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Databricks Data Classification
I encourage you to try out a new beta feature in Databricks called : Data Classification. It automatically classifies your catalog data and tag it with tags. Docs: https://docs.databricks.com/aws/en/lakehouse-monitoring/data-classification
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- 767 Views
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Strong Databricks Fundamental - Gen Z
Why Databricks is the Future of Data Analytics for Gen ZIn the fast-paced world of data analytics, staying ahead of the curve is crucial. For Gen Z, who are digital natives and always on the lookout for the latest tech trends, understanding the diffe...
- 767 Views
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- 3380 Views
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Financial Crime detection with the help of Apache Spark, Data Mesh and Data Lake
For those interested in Data Mesh and Data Lakes for FinCrime detection:Data mesh is a relatively new architectural concept for data management that emphasizes domain-driven data ownership and self-service data availability. It promotes the decentral...
- 3380 Views
- 3 replies
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It's great that you're focusing on financial crime detection with advanced technologies like Apache Spark, Data Mesh, and Data Lake. For those looking to dive deeper into criminal records and related data, tools like KY criminal lookup can provide es...
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- 3522 Views
- 1 replies
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Post: Lakehouse Federation - Databricks
Lakehouse Federation - Databricks In the world of data, innovation is constant. And the most recent revolution comes with Lakehouse Federation, a fusion between data lakes and data warehouses, taking data manipulation to a new level. This advancement...
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Hey Quick Question, Can we use it for the production version ? We have application server as SQL server, we are planning to use lakehouse federation so we can bypass creating and maintaining 100 of workflows. as we a small dataset I am not too sure o...
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- 777 Views
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Hub Star Modeling 2.0 for Medalion Architecture
Excited to share my latest publication on arXiv!“Hub Star Modeling 2.0 for Medallion Architecture” https://arxiv.org/abs/2504.08788This new version builds on the original Hub Star Modeling approach, published last year, and now tailored for the Meda...
- 777 Views
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- 2285 Views
- 1 replies
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Handling Complex Nested JSON in Databricks Using schemaHints
When I first got into managing schemas in Databricks, it took me a while to realize that putting in a little planning up front could save me a ton of headaches later on.I was working with these deeply nested, constantly changing JSON files. At first,...
- 2285 Views
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Great tip @genevive_mdonça! schemaHints help avoid issues with evolving JSON data, making data processing more reliable and easier to maintain. Thanks for sharing.
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- 1593 Views
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Understanding Coalesce, Skewed Joins, and Why AQE Doesn't Always Intervene
In Spark, data skew can be the silent killer of performance. One wide partition pulling in 90% of the data?But even with AQE (Adaptive Query Execution) turned on in Databricks, skewness isn't always automatically identified— and here’s why.What Is co...
- 1593 Views
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@mark_ott , this question seems right up your alley. Care to comment?
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- 1834 Views
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One of the solution of [FAILED_READ_FILE.NO_HINT] Error while reading file, when display() or SELECT
One of the solution of [FAILED_READ_FILE.NO_HINT] Error while reading file, when display() or SELECTI got stuck with the above error when using `spark.read.table().display()` or directly query the table using %sql.While the display method is just one...
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- 1741 Views
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Power BI to Databricks Semantic Layer Generator (DAX → SQL/PySpark)
Hi everyone!I’ve just released an open-source tool that generates a semantic layer in Databricks notebooks from a Power BI dataset using the Power BI REST API. Im not an expert yet, but it gets job done and instead of using AtScale/dbt/or the PBI Sem...
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- 775 Views
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How to train a Convolutional Neural Network on Databricks with Tensorflow and Keras
Here is how to trained a lightweight Convolutional Neuronal Network (CNN) to detect pneumonia from chest X-rays pictures on Azure Databricks. I promise no LLMs, no hype, just real-world deep learning:1. Built it with TensorFlow & Keras on Databricks2...
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- 1568 Views
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When Did the Data Go Wrong? Using Delta Lake Time Travel for Investigation in Databricks
I. IntroductionData pipelines are the lifeblood of modern data-driven organizations. However, even the most robust pipelines can experience unexpected issues: data corruption, erroneous updates, or sudden data drops. When these problems occur, quickl...
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- 2129 Views
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Real Lessons in Databricks Schema, Streaming, and Unity Catalog
Hey Databricks community,I wanted to take a moment to share some things I’ve learned while working with Databricks in real projects—especially around schema management, Unity Catalog, Autoloader, and streaming jobs. These are the kinds of small detai...
- 2129 Views
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