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#spark

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I know this is a long shot but does anybody know how to set a "secondary role" (or activate all secondary roles) in #Snowflake via the #Spark connector? I'm going to note that a lot of things that seem like they should work don't, so I'd be grateful for ideas from folks who are in a position to actually test this.

📢 New call for proposals: #Spark enables researchers from all disciplines to test or develop novel and unconventional scientific approaches, methods, theories or ideas within a short time.
🗓️ Submission deadline: 4 March 2025.
➡️snf.ch/en/CVNR0Q5f3P32Cg9f/new

Swiss National Science Foundation (SNSF)Spark: call for proposalsThe Swiss National Science Foundation (SNSF) funds excellent research at universities and other institutions.

If you’re an Apache #Spark user, you benefit from its speed and scalability for #BigData processing.

However, you might still want to leverage #RStats’s extensive ecosystem of packages and intuitive syntax. One effective way to do this is by writing user-defined functions (UDFs) with sparklyr.

UDFs enable you to execute R functions within Spark, harnessing Spark’s processing power and combining the strengths of both tools.

🔍 Learn more in a recent blog post → posit.co/blog/databricks-udfs/

The sparklyr package and friends have been getting some important updates in the past few months!

sparklyr is a package that allows you to interact with Spark using familiar R interfaces, such as dplyr, broom, and DBI. You can also gain access to Spark's distributed Machine Learning libraries, Structure Streaming, and ML Pipelines from R.

Read more in the blog post: blogs.rstudio.com/ai/posts/202

Posit AI BlogPosit AI Blog: News from the sparkly-verseHighlights to the most recent updates to `sparklyr` and friends