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@ronb you mentioned that your version of Datascript is not backwards compatible. What are the breaking changes?


@kiemdoder Attributes are stored as Integers (d/datom 0 :attr :val) is not allowed anymore Queries return attributes as Integers, not Keywords You need to define the Attribute order in the schema -> {:attr {:db/order 0}} Transaction Id’s are created from 2^24 -1 downwards New range for Entity ID’s is from 0 to 2^24 New range for valid Transaction ID’s is from 2^24 to (2^24) - 2^20


Every attribute is represented as an ID (similar to Datomic) All attributes need a db/order key in the schema


{:attr {:db/order 0} :attr2 {:db/order 1}}


Will do some benchmarking and better Docs. @tonsky Thanks for the reply on the pull request. I will reply later


I’d say, semantically, biggest setback for existing users would be: — lack of datom call with keyword attribute — unexpected integers in query results (although I believe impl can be changed to return keywords) — the need to specify all attributes in schema (:db/order could be probably calculated, but it requires all attributes to be specified explicitly)


@tonsky I completely agree. Right now the backwards incompatibilities are too big. If I address the issues you mentioned, would you be willing to merge the pull request or do you prefer a seperate project?


most incompatibilities could be addressed with code in db/-search and (transact-add), but changes in how (datom) constructor works would remain and probably be confusing to users


I don’t see how we can work around requiring that every attribute must be specified in schema. So far it’s not required and I believe most users rely on that


And then there’s JS story, which lacks 64-bit numbers so that schema wouldn’t work as well there :(


it feels like jvm-only, separate project with no backwards compatibility guarantees would be best


Yeah it would require additional logic in transaction handling to add new attributes on demand and is a bit messy 😄


i use 64 bit floats to guarantee compatibility with JS environments. All tests run successfully on JVM and JS as far as I can see


No problem. I will close the PR later. Thanks for the feedback


You can cheat if you do the following: (/ num (js/Math.pow 2 32)) -> gives access to the upper part of float numbers in the lower 32 bit region


for changing the upper part you can do (+ (* upper (js/Math.pow 2 32)) lower-bits)


isn’t it like SUPER slow?


as far as I can see this is in conformance with IEEE Floating point spec


Will test the performance in the evening, but i compared this with bit-shift operators and they have similar performance. Looks like JS engine optimize (/ num some-binary-exponent) into (bit-shift-right )


^^ maybe helpful?


btw maybe instead of trying to fit everything into one 64-bit value, it might be easier to fit everything in two 32-bit values? memory consumption will be the same


that's what goog.math.Long and therefore ^^ does


No, I mean, there’s no reason to pretend it should look like single 64-bit at any point


depends what you want to do


what @ronb is doing


@thedavidmeister Looks interesting, thanks for the link. I looked into using goog.math.Long based solution. but if i understand correctly how js engines work, it would use twice the memory of a single double number


although maybe i am mistaken and engines actually detect that you only use 32bits of the number and optimize the rest away


this benchmark compares a bitshift operation with division. and shows a 30% performance advantage for shift based operation. which is not significant enough in my use case to be detectable, as performance is largely memory bound


just tested memory usage of 32bit numbers and values that go beyond 32bits. they both use the same amount of memory