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deborshi_nag
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Joined 8 months ago
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Re: Onelake security with large tables
Hello FabricJacob There's a small nuance to this if you're using a semantic model to access data - Microsoft documentation says that to access data with RLS from a semantic model, the semantic model needs to use Direct Lake on OneLake. Row-level security - Microsoft Fabric | Microsoft Learn This is probably the reason why you see odd bevaviour with the visuals.344Views1like1CommentRe: Gap in Actual Fabric Item/Sub-items and Fabric Scan results in Microsoft Purview
Hello pranavsabnis It is quite possible - Purview scan is relies on fully qualified name, so your ADLS Gen2 may have been referenced multiple times, one as an OneLake shortcut, and other as a fully qualified name. What you're looking at is probably Asset Normalisation in Purview, where metadata from duplicate entires are tagged to the same asset. Asset normalization in Microsoft Purview Data Map | Microsoft Learn263Views1like0CommentsRe: What’s the best for Metadata driven Pipeline?
Hello Kuladeep I would recommend using an Azure SQL database for your use case, as this will allow you to avoid being limited by the same Fabric capacity. Your pipelines and notebooks can access data from an Azure SQL database without needing significant changes.1.3KViews1like4CommentsRe: Copy Data Activity - Issues and saying not found target file path
Hello hsa297 I noticed that in the File extension setting you have .txt - if your file is .csv as the name suggests, "SourceDataControl.csv", shouldn't this be set to .csv instead? Could you change this setting and try again please? Also, check if you can use Preview data to inspect the contents of the source file.497Views0likes1CommentRe: Microsoft Fabric: [TooManyRequestsForCapacity] HTTP Response code 430: This Spark job can’t be run b
Hello TAnalytics Fabric trial capacity is shared, so when there are no free cores, pipeline jobs are queued and interactive jobs may fail. That’s why you’re seeing the error message. You can check the Monitoring Hub and try loading the CSV file when activity is lower. Alternatively, you could use Dataflow Gen2 for CSV ingestion in a pipeline.918Views2likes0CommentsRe: How can I read a different content from one same lakehouse table ?
Hello MathieuSGA The underlying format of the files in /Tables would be delta, so you should use the appropriate format when reading the table. Since you're using parquet format, your Spark code is reading all parquet files that includes historical or deleted rows. Please use: spark.read.format("delta").load(f"abfss://{ws_id}@onelake.dfs.fabric.microsoft.com/{lh_id}/Tables/{table_name}")290Views2likes1Comment
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