DailyDatabricks

Supercharge Your Databricks Catalog Management using Python. Our latest post walks through using Spark Catalog APIs in PySpark to: ✅ Recursively list databases & tables ✅ Capture catalog structure in a dictionary ✅ Diff catalogs across envs https://lnkd.in/eCW5jEc2

❌ Ever experienced the INVALID_STATE.RESTORATION_PERIOD_EXPIRED error when you've just dropped a table? Are you struggling with table restoration issues in Databricks, even within the 7-day recovery window? 😤 "That makes no sense!" you exclaim. You know the table was dropped yesterday, yet Databricks insists the restoration period has expired. 🔍 Here's the twist: sometimes this error isn't about timing at all. Often comes down to naming conflicts and table identification challenges that aren't immediately obvious. 💡 If you're working with Databricks and want to sleep better, check out the full tip https://lnkd.in/e6xWGW7u #Databricks #DataEngineering #CloudComputing #TechnicalTroubleshooting #DataOps #UnityCatalog

🔴 Attention Azure Databricks users! Did you know you can utilise the built-in Managed Identity in your workspace? The latest post walks through how to connect to Azure services like Key Vault, Storage, and more using the dbmanagedidentity - no more juggling credentials! Check out the details and code snippets here: https://lnkd.in/e4h48W8G

🎄📈 Elevate Your PySpark Testing Game 🐍💡 Discover the power of dynamically loading unit tests in your PySpark notebooks. This allows you to activate them on demand, so you can run them during development or deployment but disable them daily. Our latest tip breaks down the process step by step, complete with code samples and practical tips. Level up your testing skills and streamline your Databricks workflow today! 💪 🔗 https://lnkd.in/eKj7pu4r #PySpark #Databricks #SoftwareTesting #CodeQuality

Day3: Level Up Your Window Functions with Named Windows in Databricks   Do you find yourself repeating the same complex window definitions across multiple functions in your Databricks SQL or PySpark code? 🤔 Named window specifications are here to help! 🎉 By allowing you to declare a window spec once and reference it by name, named windows make your queries more concise, readable, and less error-prone. Check out my #Decembricks post to learn how to leverage this feature in both SQL and Python. 💡   #Databricks #Spark #SqlTips #PySpark #DataEngineering #SparkSQL

📝 New Post: Enhancing Delta Lake Tables with Custom Metadata Logging Ever wondered how to maintain better data lineage and governance in your Databricks environment? Our latest guide shows you how to leverage Delta Lake's custom metadata feature to: 🔹 Track pipeline versions and processing details 🔹 Monitor data quality metrics 🔹 Maintain compliance audit trails 🔹 Document data transformations We cover implementation in Python, SQL, and R, with real-world examples for: - Session-level configuration - Operation-specific metadata - Querying historical metadata - Best practices and optimization tips Read the full post here: https://lnkd.in/e6BnsWyk #Databricks #DataEngineering #DeltaLake #BigData #DataGovernance #ApacheSpark #Delta

🎄 Day 1 of #Decembricks: Unlocking Advanced Notebook Powers! Ever wished your Databricks notebooks could automatically track DataFrame changes, log executions, and monitor performance across Python, SQL, and Scala - all without changing your code? Today's tip: IPython Events in Databricks 🚀 Perfect for both beginners (easy to implement) and advanced users (limitless possibilities). This powerful but overlooked feature lets you: - Execute code everytime a cell is run - Add helpers such as automatic DataFrame validation - Implement cross-language logging - Monitor performance metrics and more Check out the full guide: https://lnkd.in/emRf6sU6 #Databricks #DataEngineering #Python #BigData #Analytics