marcle

This is a very interesting addition to the embedded analytics database landscape. MonetDB/e may hit a sweet spot.

I always enjoyed using MonetDBLite (with R), but it is no longer being developed. I understand that CWI has contributed to the development of MonetDBLite, DuckDB and MonetDB/e. It would be useful to know how DuckDB and MonetDB/e differ. The latter may have the advantage of building on a well established server.

For some other embedded databases, see http://embedded-database.com/open-source-embedded-database-s....

This is an interesting benchmark comparing parallel functional programming languages, including Rust, Parallel OCaml and MPL. MPL is "a parallelism-oriented fork of MLton for Standard ML" which is described as being "definitely the star" (see also http://www.cs.cmu.edu/~swestric/20/popl-disentangled.pdf). This benchmark was inspired by Jon Harrop's ray tracer benchmark (https://www.ffconsultancy.com/languages/ray_tracer/index.htm...).

I have co-authored several academic articles in Org mode with exporting to LaTeX. The main reasons for choosing Org were that (i) we wanted to include the analysis code, table generation and figures in the same file as the manuscript, and (ii) the workflow was Emacs-centric. The Org markup was simple, readily allowed for inserting most LaTeX, had nice tables, but was fiddly for some more complex tasks. I recently needed to convert one of the manuscripts from Org to Word - pandoc was very helpful.

We could possibly have used TeXmacs, R markdown (especially with RStudio), some variant of noweb, or even Jupyter with conversion to LaTeX using pandoc.

As a reminder, there is also a Simula compiler provided by GNU (https://www.gnu.org/software/cim/). A gist for installing and running the compiler is available from https://gist.github.com/mclements/706fcb68047f7f8c07014c70f9....

For what it's worth, if we define Rsql as the following script:

  #!/usr/bin/env Rscript
  library(sqldf, quietly=TRUE)
  statement <- commandArgs(TRUE)
  a <- read.table(file("stdin"), header=TRUE)
  print(sqldf(statement))

then we can call

  ps -Ao user | Rsql 'select USER, count(*) as nprocesses from a group by USER limit 5'

to get the output

          USER nprocesses
  1      avahi          2
  2     colord          1
  3     daemon          1
  4     marcle        136
  5 messagebus          1