charred VS ham-fisted

After building tech.ml.dataset and charred I wanted to take the lessons learned there and apply them back into the base Clojure substrate of persistent maps, persistent vectors, and algorithmic primitives like group-by and frequencies.

...and in some circumstances, the most correct Clojure program has a little Java in it because it's faster or whatever. (Chris Nuernberger's charred is a recent example.) This is unusual Clojuring; most Clojurians never do this.

Introducing Charred - fast json/csv encode and decode. This library finalizes my research into csv and json parsing and is a complete drop-in replacement for clojure.data.csv and clojure.data.json. Same API, much better (5-10x) performance. This library gets as good performance for those tasks as anything on the JVM and avoids the jackson hairball entirely.

3 - Similar to 2, the savings of mutably building the collection have to outweigh the cost of persisting it. Or if you are using the transient as a mutable container (e.g. held by an item) for limited random access and writes (as opposed to say a mutable arraylist or hashmap or hashset), performance should still be substantially better for writes over the persistent counterparts. The most gains come from building up large collections, using transients to mutably collect values and then persist at the end. Similar idea (but more general) in ham-fisted.

I have taken the time in between caring for my young son to write a new library that provides higher performance datastructures and algorithms for Clojure.