CQEngine VS amber-docs

Wrote the code to convert CQEngineCQEngine queries into Solr search queries.

It seems that you're looking for something like https://github.com/npgall/cqengine but unfortunately I'm not aware of any equivalent in Go. LINQ is similar. I'd probably try searching for "LINQ in go" or something like that.

I wonder if there's a huge difference in efficiency between RoaringBitmap and CQEngine. I used CQEngine a few years back and it turned out really great. Never tried RoaringBitmap, though.

Record patterns are one step on the path to general pattern matching utility. The bigger building block is general deconstructors. I recommend reading Functional Transformation of Immutable Objects by Brian Goetz. The idea of "withers" shown there requires deconstructors:

https://github.com/openjdk/amber-docs/blob/master/eg-drafts/...

This is the vague plan.

You may be joking but...

Here is the much more detailed version: https://github.com/openjdk/amber-docs/blob/master/eg-drafts/reconstruction-records-and-classes.md

This kind of pattern matching is discussed in the design notes: https://github.com/openjdk/amber-docs/blob/master/site/design-notes/patterns/pattern-match-object-model.md

True, but that only pushes the question of value down the line.

I'm curious about lenses because Java did have a serious problem that required a solution: working with "simple" data correctly was difficult. The chosen solution was ADTs, so we did buy into that. But the approach being explored for transforming records (https://github.com/openjdk/amber-docs/blob/master/eg-drafts/...) only works one level at a time rather than for an entire path. So I wonder how valuable it would be to have a solution for paths. If the answer is that it's mostly valuable for an approach we haven't bought into yet, then we might not need to consider it just yet.

Just a heads up, something like that spread operator is actually coming sooner or later to java: https://github.com/openjdk/amber-docs/blob/master/eg-drafts/...

Pattern matching (for records) is already a preview feature.