Hi, I think that it could be very useful to see the component columns when a KQL materialized view is created, in the KQL databases explorer. I can see the columns of a table and not of a materialized view. Also it could be very useful seeing the related data types. Thanks ... View more

When sharing a dashboard, the link that is being shared must include the current page and current parameters values for it to be effective. ... View more

We want to get data from Kafka Topics as streaming data. Custom App option is of no use as it expects the source to push to this individual broker, which is not liked and opted by most customers for obvious reasons. Hence, we want to access the kafka topic using notebook which we can access but this Kafka topic has restrictions with respect to IP. Hence if we call from notebook, it restricts us. So, we tried to put it behind VPN. Even in that case, the notebooks are not getting considered as behind the VPN. Probably, Fabric Notebooks in real-time intelligence item lack IP address and hence make it. Same goes for making restricted API calls, which dont offer authentication mechanism but expect whitelisting instead. ... View more

I would like to request a feature in Kusto that allows column renaming using the .rename command to automatically propagate throughout all tables that reference this column, whether they are upstream or downstream in the data pipeline. This would cover scenarios where tables are linked through update policies, functions, or other forms of dependencies, making it easier to maintain schema consistency across multiple tables. For example, if a column in a central table is renamed, any other table that relies on that column (via update policies or joins) should automatically reflect this change. This feature could use graph analytics to detect the relationships between tables and their shared columns, simplifying the task of schema maintenance and reducing the risk of errors from manual updates across interconnected tables. Such a feature would be especially useful in environments with complex data dependencies, where table schemas evolve over time, as it would ensure consistency across the entire data ecosystem with minimal manual intervention. ... View more

The following are examples of scenarios that benefit from clustering: Tables often filtered by high cardinality columns. Tables with significant skew in data distribution. Tables that grow quickly and require maintenance and tuning effort. Tables with access patterns that change over time. Tables where a typical partition column could leave the table with too many or too few partitions. ... View more

Finger- Loan- app-custOmer-care-HELPLINE--number +91)09120509022_/091-205-0-9-022-:caI. ; How ... View more

Please allow to derive a value out of a complex JSON which is stored in a single field in your stream ... View more

Provide continuous ingestion from OneLake. ... View more

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Currently, materialised views cannot reference external tables. For data curation, it is important to combine Lakehouse table dimensions (cold data) with KQL tables (hot data). Support for this feature improves data manageability. ... View more

Currently data can be ingested into KQL table but if for some reasons data needs to be modified or removed it is not generally possible. Mirroring policy is enabled if OneLake availability is activated Disabling mirroring policy to modify the table makes OneLake synchonization non-functional. It would be very helpful to make KQL table fully synchronized with OneLake for all operations ... View more

We are still "playing" with Fabric here, but while I was testing the Eventhouse I realized that for every Database/Table we create we would need to configure a shortcut on a lakehouse.   For my use case I believe that RTA will be the main entrance for the data, but I want all of it to be available in lakehouse (delta) and be queried from there as well. On our current ADX cluster we have more than 200 tables, and having to copy the shortcut from each table to a lakehouse for all of them (or even having to do it for every new table we create - we are still ingesting different sources) would be, in my vision, time consuming,error prone and "weird" 🙂 So, in my humble view, it'd be interesting to create a Lakehouse when ever we create a new Eventhouse, with shortcuts for all tables synced by default, more of less like a semantic model and a SQL endpoint are created when creating a new Lakehouse.    Of course the possibility to copy the link and create new shortcuts in other lakehouses should still be available.  My suggestion is more on the lines of "visibility and consistency", considering that all data should be available as delta this should be a "natural" step. Please feel free to reach me if the idea was not clear enough. Thanks!   ... View more

Drag and drop a function/table in the left nav tree into a folder to make reorganizing the tree easier ... View more

I’d love to be able to specify textual tool tip on a series from a different column. For example, you can see that the number looks less readable than I would prefer: This is a numeric value, 331015043222593745 but I want to present it as 294 PB. I can do so using a KQL function, I just need to be able to specify a different source for the tooltip ... View more

It's not very widely known or shared that Kql queries can be run in Fabric notebooks. Could you please install the Kqlmagic extension in the default Fabric environment so it can be used without installation. Thanks. Tutorial- Use a notebook with Kqlmagic to query a KQL database - Microsoft Fabric | Microsoft Learn ... View more

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LZ4 and ZSTD are compression codecs that are natively support on spark (lz4 since 0.8.0 and zstd since 3.0.0 -https://spark.apache.org/docs/latest/configuration.html). These formats provides better compression ratios and faster decompression speeds (https://facebook.github.io/zstd/, https://github.com/lz4/lz4 and self experience 😉 ). Currently Kusto only supports Snappy and GZIP, and GZIP doesn't provide Splittablity  ("parallel decompression" , but couln't find a good reference for this). So adding support for zstd and lz4 would provide potentially better query performance (faster decompression), lower storage cost (better compression) and more widespread compatibility (people saving data on these formats since spark natively support them). Please feel free to reach me if in need of clarification. ... View more

When we copy and share a query, we get support for executing the query in Web or Desktop. Would like to see another option to run this directly in Fabric (As shown in the example below ). This draw more users to Fabric also will allow users to hit and run without any additional steps Execute in [Web] [Fabric] [Desktop] [cluster('xxxxxxx.eastus.kusto.windows.net') database('yyyyy')]  ... View more

Facilitate analysis on Fabric using Log Analytics. Through mirroring or shortcuts to the KQL database, we can make it possible for data to be used in near real-time and with zero copy for BI analysis via Direct Lake or with AI Skills. This feature will also simplify the configuration of export jobs for long-term storage. ... View more