Really cool, thanks for sharing. You all might want to look at Apache Calcite ( http://calcite.apache.org/ ) as well for inspiration, which has similar functionality as a subset of its features!
Apache Drill vs Calcite? Seem very similar.
Drill depends on Calcite for SQL parsing and cost-based query optimization!
Generally, I make use of file_fdw module of Postgres to achieve this. https://www.postgresql.org/docs/11/file-fdw.html
I wonder if you or the other Postgres users here could give me some tips. What would be the best way to use the data from a huge Excel file into my web apps? Currently I'm converting it to CSV and use `BULK INSERT` with MSSQL. I know that with MSSQL I can also use Excel files as "external database" but AFAIK, Excel files are not indexed and are super slow when used as an "external database". I wouldn't mind switching…
As an MSSQL guy who rarely connects it to excel, if your workflow allows it consider pulling the entirety of the excel sheet into a table in the db and working on it just from there. What's huge for excel isn't for MSSQL.
As a decades-long user of MSSQL guy who is getting sick of being rpeatedly done over by MS, could you explain why you prefer postgres? That would be incredibly interesting, TIA
Hey, one of the authors here. The motivation behind this project is that I always wanted a simple commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This started as an university project,…
Generally, I make use of file_fdw module of Postgres to achieve this. https://www.postgresql.org/docs/11/file-fdw.html
My god. I didn't know postgres can do this. Thank you!
Hey, one of the authors here. The motivation behind this project is that I always wanted a simple commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This started as an university project,…
> commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This exactly describes Drill ( https://drill.apache.org/ ) which can query any data source under the sun (RDBMS, NoSQL, files, cluster…
i have a reoccurring use case where i have huge csv files that i need to aggregate / summarize using a pretty old netbook. the only way i can get this done is through spark/scala. would drill be a better option?
> commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This exactly describes Drill ( https://drill.apache.org/ ) which can query any data source under the sun (RDBMS, NoSQL, files, cluster…
i have a reoccurring use case where i have huge csv files that i need to aggregate / summarize using a pretty old netbook. the only way i can get this done is through spark/scala. would drill be a better option?
Sure. Create a filesystem data source in the Drill config (https://drill.apache.org/docs/file-system-storage-plugin/) with the directories where your CSVs are in. Then query them however you'd like. Use the CLI if you want to produce another CSV or REST/JDBC if you need the data somewhere else. If the query is complex and long-running you can monitor it's state in the Drill web UI.
Hey, one of the authors here. The motivation behind this project is that I always wanted a simple commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This started as an university project,…
Hey, at work we have been forced to use Denodo. How does this compare to Denodo? Seems a lot better and doesn’t try to do any “data virtualization”. I am a bit scared by the query optimizer because the Denodo one is super buggy. Overall I think the concept is great and this might be a great companion to etl tools.
Hey, at work we have been forced to use Denodo. How does this compare to Denodo? Seems a lot better and doesn’t try to do any “data virtualization”. I am a bit scared by the query optimizer because the Denodo one is super buggy. Overall I think the concept is great and this might be a great companion to etl tools.
If vis is the focus, I'd recommend Postgres FDW over anything else here, just because PG is supported by almost every vis software (metabase, redash, many Apache projects, Tableau, Google Data Studio (free) etc.)
Hey, one of the authors here. The motivation behind this project is that I always wanted a simple commandline tool allowing me to join data from different places, without needing to set up stuff like presto or spark. On another hand, I never encountered any tool which allows me to easily query csv and json data using SQL (which at least in my opinion is fairly ergonomic to use). This started as an university project,…
Pretty cool stuff.
Does it support writing to (single) data sources too or only reading queries?