#ApacheIceberg + #SparkSQL = a solid foundation for building #ML systems that work reliably in production. Time travel, schema evolution & ACID transactions address fundamental data management challenges that have plagued ML infrastructure for years. 🔍 bit.ly/46kCCpQ

💸 Spark SQL costs out of control? Run your dbt transformations for 50% less, with 2–3× better efficiency. No rewrites required. Join Amy Chen (@dbt_labs) & @KyleJWeller (Onehouse) next week to see how. 👉 onehouse.ai/webinar/dbt-on… #dbt #SparkSQL #ETL #DataEngineering

💸 Spark SQL costs out of control? Join @getdbt + @Onehousehq to learn how to cut them in half. 📅 Sep 3 | 10am PT → onehouse.ai/webinar/dbt-on… #DataEngineering #ETL #dbt #DataLakehouse #SparkSQL

📷 Enroll today and take your data career to the next level! zxacademy.com/course/apache-… 📷 Supercharge Your Big Data Skills with Apache Spark & Scala! 📷 #ApacheSpark #Scala #BigData #ZxAcademy #DataEngineering #SparkStreaming #MLlib #SparkSQL

at @yourcreatebase, i was working with large unclaimed music royalty records — to consolidate publisher objects: mapping rights admin relationships to shares, writers, and iswc codes — to make our royalty payout pipeline faster and more accurate #SparkSQL #PySpark #AWS #S3

🧵7/10 Results from TPC-H style workloads: - Joins: 84–95% faster - Filters: 30–50% faster - Aggregations: 20–40% less shuffle All changes are semantically safe. Success rate: 95%+ #SparkSQL #QueryOptimization

#ApacheIceberg + #SparkSQL = a solid foundation for building #ML systems that work reliably in production. Time travel, schema evolution & ACID transactions address fundamental data management challenges that have plagued ML infrastructure for years. 🔍 bit.ly/46kCCpQ

What languages can be used in Fabric Notebooks? 🔹 PySpark 🔹 Spark (Scala) 🔹 SparkSQL 🔹 SparkR (R) 🔹 HTML #MicrosoftFabric #FabricNotebooks #PySpark #SparkSQL #SparkR #Scala #BigData #DataEngineering #DataScience #OneLake #FabricCommunity #DataPlatform #DP700

Want a follow-up post on common mistakes that break Catalyst optimizations? Reply below or drop a 🔥 Follow @yashdantale for more on PySpark, Apache Spark internals, and modern data workflows! #PySpark #SparkSQL #DataEngineering #BigData #CatalystOptimizer

Working with tons of data? Spark SQL makes querying big datasets feel effortless. Whether it's quick analysis or complex pipelines, it's a must-know for today’s data engineers. Read more: bit.ly/45Tik6A #SparkSQL #BigData #DataEngineering #ApacheSpark #DataAnalytics

Discover how Databricks' evolution from Spark SQL to declarative pipelines is reshaping data processing! 🚀 Dive into enhanced efficiency and flexibility for modern data workloads. #Databricks #SparkSQL #DataEngineering #TechInnovation #BigData #DataPipeline

🚀Transforming Data With Apache Spark in Databricks | 360DigiTMG🚀 📅 Date: 4th July 2025 🕓 Time: 4:00 PM IST 📝 Register Now by clicking the link below 👇 360digitmg.zoom.us/webinar/regist… #ApacheSpark #Databricks #DataTransformation #BigData #DataEngineering #SparkSQL

🚀 Working with PySpark SQL? Here's a quick and powerful example! You can query DataFrames using SQL syntax in Spark — great for teams coming from SQL backgrounds. #PySpark #BigData #SparkSQL #DataEngineering #ETL #ApacheSpark #SQL #DataScience #XavierDataTech

📢 We’re Hiring: Data Architect ct with deep expertise in modern data stacks and scalable architecture design. Ready to lead impactful data solutions? Let’s talk. Apply Now:[email protected] #DataArchitect #DataEngineeringJobs #Databricks #AWS #SparkSQL

Analyzed Retail data in Databricks using Spark SQL to uncover insights on sales, customers, and product trends—driving targeted marketing, inventory planning, and strategic pricing decisions. #Databricks #SparkSQL #RetailAnalytics #DataScience #BigData #businessintelligence

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7/ 📚 Spark SQL: Tables & Views 🗂 Managed Table = Spark owns data + metadata 📂 External Table = Spark owns metadata only 🔍 Temporary Views = Session-only 🌐 Global Views = All sessions #SparkSQL

✅ Use DataFrames over RDDs Why? DataFrames are optimized for speed & memory, leveraging Catalyst Optimizer for better execution. Switching from RDDs → DataFrames = 🚀 Faster performance! #DataFrames #SparkSQL

🚀 Exciting news from DogeKing! The SparkSQLHelper v2025.1.1 is here with support for PyCharm, thanks to user feedback. Enhance your SparkSQL experience today! Check it out: ift.tt/FSWlQpd #SparkSQL #PyCharm #DevTools 🚀 ift.tt/BCbzE8j