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Rill 0.5 – Frictionless data source ingestion and exploration

Β· 2 min read

⚑ Rill Developer is a tool that makes it effortless to transform your datasets with SQL. These are our release notes for the 0.5.0 release, still in Tech Preview.

To try out Rill Developer, check out these instructions and let us know over on Discord if you encounter any problems or have ideas about how to improve Rill Developer!

Drag and drop local data ingestion​

At Rill we want to make every small step in data work feel faster, more tactile, and more intuitive. To this end, we have upgraded the user interface to include smarter ways to ingest files as new data sources.

  • drag-and-drop source files β€” Don’t fumble in your computer’s file system when you can see what you need on the screen. Now you can drag and drop a CSV or parquet file directly to the Rill Developer window to kick off ingesting a new data source.
  • overwriting duplicate sources β€” Data work is iterative by nature. Often the data files we are exporting from other tools share the same name (eg: export.csv) and can create conflicts during data ingestion. We now support choosing how to handle these cases with data source overwrite or rename functionality at the time of ingestion.

Delightful data source interactions​

In addition to making it easier to get data into Rill Developer, we are making it easier to explore and understand each source that has been added.

  • automatically query a source β€” Stop writing SELECT * FROM my_new_source to get started after ingestion. You can use command-click in the left navigation bar under sources to pull the first query anyone writes when they are building data intuition into the SQL editor.
  • rename a source β€” Data source file names are often not descriptive, human readable, or unique. Now you can rename sources from the UI to help keep your projects clean and clear.
  • table aesthetics β€” The output table can be an important source of information when you are building intuition across columns. This release introduces tighter columns and row numbers for output tables that help you quickly skim raw output for row-level patterns.