"; */ ?>


Oct 13

Datomic: Your Call Will Be Answered In The Order It Was Received

The Star Family

Mother Sun likes to have its planets close by at all times. Some closer than others, but that’s how life goes: someone grows up and becomes a star, others take their places next to that someone.

This narrative is about such a family, a Solar System family, where planets live at a certain distance from the Sun. The schema is simple, “solar/planet” with a “solar/distance”:

(def schema
  [{:db/id #db/id[:db.part/db]
    :db/ident :solar/planet
    :db/valueType :db.type/string
    :db/cardinality :db.cardinality/one
    :db.install/_attribute :db.part/db}
   {:db/id #db/id[:db.part/db]
    :db/ident :solar/distance
    :db/valueType :db.type/long
    :db/cardinality :db.cardinality/one
    :db.install/_attribute :db.part/db}])

Here is the data from almighty wikipedia:

(def data
  [{:db/id #db/id[:db.part/user]
    :solar/planet "Mercury"
    :solar/distance 57909175}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Venus"
    :solar/distance 108208930}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Earth"
    :solar/distance 149597890}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Mars"
    :solar/distance 227936640}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Jupiter"
    :solar/distance 778412010}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Saturn"
    :solar/distance 1426725400}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Uranus"
    :solar/distance 2870972200}
   {:db/id #db/id[:db.part/user]
    :solar/planet "Neptune"
    :solar/distance 4498252900}])

Creating a schema and importing the data:

(d/transact *conn* schema)
(d/transact *conn* data)


Great, so now we have all that knowledge in Datomic. Let’s check it out:

(d/q '[:find ?p ?d :in $ 
       :where [?e :solar/planet ?p]
              [?e :solar/distance ?d]] (db *conn*))
#{["Venus" 108208930] ["Earth" 149597890] ["Saturn" 1426725400] ["Uranus" 2870972200] 
  ["Jupiter" 778412010] ["Mercury" 57909175] ["Neptune" 4498252900] ["Mars" 227936640]}

Looks right, but.. out of order? Yea, that is strange, since we “imported” the data in a vector, e.g. with an order in mind. Let’s focus on the planets themselves:

(d/q '[:find ?p :in $ 
       :where [?e :solar/planet ?p]] (db *conn*))
#{["Saturn"] ["Venus"] ["Jupiter"] ["Mercury"] ["Earth"] ["Mars"] ["Neptune"] ["Uranus"]}

Again out of order, this time in a “different” out of order.

Popping The Hood

One thing to notice above is that the result, that gets returned from a query, is a set, and a set has no (specific) order. So given the result and its type, Datomic did not do anything wrong, it just returned a set of planets: exactly what we asked for.

However, since all the facts were asserted in order, Datomic must have remembered them in order, right? Well let’s check. Every fact that gets asserted, gets assigned an entity id. Hence instead of looking at planet names, let’s look at corresponding entity ids:

(d/q '[:find ?e :in $
       :where [?e :solar/planet ?p]] (db *conn*))
#{[17592186045418] [17592186045420] [17592186045419] [17592186045422] [17592186045421] 
  [17592186045424] [17592186045423] [17592186045425]}

Better. Now we see that Datomic in fact has entity ids that we can easily sort:

(d/q '[:find (sort ?e) :in $ 
       :where [?e :solar/planet ?p]] (db *conn*))
[[(17592186045418 17592186045419 17592186045420 17592186045421 17592186045422 17592186045423 
   17592186045424 17592186045425)]]

And even convert these ids back to planet names, it’s all data after all:

(->> (d/q '[:find (sort ?e) :in $ 
            :where [?e :solar/planet ?p]] (db *conn*))
     (map (comp :solar/planet #(d/entity (db *conn*) %))))
("Mercury" "Venus" "Earth" "Mars" "Jupiter" "Saturn" "Uranus" "Neptune")

Very nice. But can we do better? Yes we can.

Now I Know The Trick

The problem with the solution above, it does two lookups: first to get the entity id, second to lookup data for this entity id. But we can do better. The query to get an entity id already “works with” a planet name, and “knows” about it. So why not use both of them right away:

(d/q '[:find ?p ?e :in $ 
       :where [?e :solar/planet ?p]] (db *conn*))
#{["Mars" 17592186045421] ["Saturn" 17592186045423] ["Neptune" 17592186045425] 
  ["Uranus" 17592186045424] ["Earth" 17592186045420] ["Mercury" 17592186045418] 
  ["Venus" 17592186045419] ["Jupiter" 17592186045422]}

Same query, just a little more data back. And Clojure loves data, now its trivial to get them in order with just Clojure:

(->> (d/q '[:find ?p ?e :in $ 
           :where [?e :solar/planet ?p]] (db *conn*))
     (sort-by second)
     (map first))
("Mercury" "Venus" "Earth" "Mars" "Jupiter" "Saturn" "Uranus" "Neptune")

That’s more like it. Of course we can use our knowledge about the data, and sort planets by the distance:

(->> (d/q '[:find ?p ?d :in $ 
            :where [?e :solar/planet ?p]
                   [?e :solar/distance ?d]] (db *conn*))
     (sort-by second)
     (map first))
("Mercury" "Venus" "Earth" "Mars" "Jupiter" "Saturn" "Uranus" "Neptune")

Not all data comes with such a direct ranking (as distance) of course, but whatever comes in Datomic’s way is definitely processed in the order it was received.

Sent from Earth

May 13

Datomic: Can Simple be also Fast?

“An ounce of performance is worth pounds of promises”
© Mae West

Speed for the sake of Speed

Benchmarks, performance, speed comparisons, metrics, apples to apples, apples to nuclear weapons.. We, software developers “for real”, know that all that is irrelevant. What relevant is a clear problem definition, flexible data model, simple tool/way to solve it, a feeling of accomplishment, approved billing papers, moving along closer to the stars..

All is true, premature optimization is the root of all evil, readability over pointer arithmetic, performance does not really matter,… until it does. Until a problem definition itself is numbers over time i.e. ..ions per second.

It is not only HFT that defines capabilities of trading companies in their ability to cope with speed of light and picoseconds. Having big data and real time online processing coming out of basements and garages and finally hitting the brains of suits who suddenly “get it” and have money ready for it, makes a new wave of “performance problems” that are “just that”: little bit of business behind the problem, and mostly raw things per second.

Never Trust Sheep

© Ryan Stiles

Interesting thing about choosing the right database for a problem today is the fact that there are just so many available, and many scream that they can do everything for you, from storing data to taking your shirts to dry cleaning on Wednesdays if you buy a dozen of their enterprise licensees. One thing I learned is “to be quick and efficient we have to mute screamers and assholes”, so some fruit and fragile NoSQL boys and Oracle are out.

Datomic is kind of a new kid on a block. Although the development started about 3 years ago, and it was done by Relevance and Rich Hickey, so it is definitely ready for an enterprise ride. To put in into perspective: if MongoDB was ready for Foursquare as soon as MongoDb learned to “async fsync”, then given the creds, Datomic is ready for NASA.

Speed and Time

While usually all Datomic discussions involve “time” and rely on Cojure’s core principles of “Epochal Time Model”, this novel introduces another main character: “Speed”.

Datomic processes write transactions by sending them to a transactor via queue, which is currently HornetQ. Hornet claims to be able to do millions a second with SpecJms2007.

Before transaction is off to a tx queue it needs to be created though. It usually consist out of one or more queries. The documented, and recommended, way to create a query is a Datomic’s implementation of Datalog. It is a nice composable way to talk to the data.

While writes are great, and HornetQ looks quite promising, the fact that Datomic is ACID, and all the writes are coordinated by a transactor, Datomic is not (at least not yet) a system that would be a good fit for things like clickstream data. It does not mean writes are slow, it just means that it is not for 1% of problems that need “clickstream” like writes.

Reads are another story, one of the kickers in Datomic is having access to the database as a value. While “as a value” part sounds like a foreign term for a database, it provides crazy benefits: immutability, time, …, and among all others it provides a database value inside the application server that runs queries on it. A closest analogy is a git repository where you talk to the git repo locally, hence “locality of references”, hence caching, hence fast reads.

Peeking into The Universe

It is always good to start from the beginning, so why not start directly from the source: The Universe. Humans naively separated The Universe into galaxies, where a single galaxy has many planets. So here is our data model, many galaxies and many planets:

(def schema [
  {:db/id #db/id[:db.part/db]
   :db/ident :universe/planet
   :db/valueType :db.type/string
   :db/cardinality :db.cardinality/many
   :db/index true
   :db.install/_attribute :db.part/db}
  {:db/id #db/id[:db.part/db]
   :db/ident :universe/galaxy
   :db/valueType :db.type/string
   :db/cardinality :db.cardinality/many
   :db/index true
   :db.install/_attribute :db.part/db} ])

Here is the data we are going to be looking for:

(def data [
  {:db/id #db/id[:db.part/user]
   :universe/galaxy "Pegasus"
   :universe/planet "M7G_677"} ])

And here is a Datalogy way to look for planets in Pegasus galaxy:

(d/q '[:find ?planet :in $ ?galaxy 
       :where [?e :universe/planet ?planet]
              [?e :universe/galaxy ?galaxy]] (db *conn*) "Pegasus")

Which returns an expected planet: #{[“M7G_677”]}

Secret of a Clause

Now let’s bench it. I am going to use criterium:

  (d/q '[:find ?planet :in $ ?galaxy 
         :where [?e :universe/planet ?planet]
                [?e :universe/galaxy ?galaxy]] (db *conn*) "Pegasus"))
   Evaluation count : 384000 in 60 samples of 6400 calls.
Execution time mean : 169.482941 µs

170µs for a lookup.. not too shabby, but not blazing either.. Can we do better? Yes.

The way Datalog is implemented in Datomic, it takes less time, and needs to do less, if most specific query clauses are specified first. In the example above “[?e :universe/galaxy ?galaxy]” is the most specific, since the “?galaxy” is provided as “Pegasus”. Let’s use this knowledge and bench it again:

  (d/q '[:find ?planet :in $ ?galaxy 
         :where [?e :universe/galaxy ?galaxy]
                [?e :universe/planet ?planet]] (db *conn*) "Pegasus"))
   Evaluation count : 384000 in 60 samples of 6400 calls.
Execution time mean : 158.893114 µs

The “clause trick” shaved off 10µs, which is pretty good. But can we do better? We can.

The Art of Low Level

Since I was a kid, I knew that Basic is great, but it is for kids, and Assembly is the real deal. While Datalog is not Basic, and it is really powerful and good for 95% of cases, there are limitations with how fast you can go. Again, most of the time, a 200µs lookup is more than enough, but sometimes it is not. At times like these we turn to Datomic Assembly: we turn directly to indices.

While in the universe of other DB engines and languages doing something low level requires reading 3 books and then paying a consultant to do it, in Clojuretomic land it is a simple function that is called datoms:

Usage: (datoms db index & components)
Raw access to the index data, by index. The index must be supplied,
and, optionally, one or more leading components of the index can be
supplied to narrow the result.
    :eavt and :aevt indexes will contain all datoms
    :avet contains datoms for attributes where :db/index = true.
    :vaet contains datoms for attributes of :db.type/ref
    :vaet is the reverse index

And it is not just simple, it also works. Let’s cook a generic lookup function that would lookup an attribute of an entity by another attribute of that same entity:

(defn lookup [?a _ a v] 
  (let [d (db *conn*)] 
    (map #(map :v (d/datoms d :eavt (:e %) ?a)) 
         (d/datoms d :avet a v))))

A couple of things:

First we look for an entity with an attribute “a” that has a value “v”. For that we’re peeking into the AVET index. In other words, we know “A” and “V” from “AVET”, we are looking for an “E”.

Then we map over all matches and get the values of an attribute in question: “?a”. This time we’d do that by peeking into “EAVT” index. In other words, we are looking for a value “V”, by “E” and “A” in “EAVT”.

Note that idiomatically, or should I say datomically, we should pass a database value into this “lookup” function, since it would enable lookups across time, and not just “the latest”.

Let’s bench it already:

    (lookup :universe/planet :by :universe/galaxy "Pegasus")))
   Evaluation count : 11366580 in 60 samples of 189443 calls.
Execution time mean : 5.848209 µs

Yep, from 170µs to 6µs, not bad of a jump.

Theory of Relativity

All performance numbers are of course relative. Relative to the data, to the hardware, to the problem and other sequence of events. The above is done on “Mac Book Pro 2.8 GHz, 8GB, i7 2 cores” with a 64 bit build of JDK 1.7.0_21 and “datomic-free 0.8.3862”. Having Clojure love for concurrency I would expect Datomic performance (i.e. those 6µs) to improve even further on the real multicore server.

Another thing to note, above results are from a single Datomic instance. Since Datomic is easily horizontally scalable, by partitioning reads and having them go out against “many Datomics” (I am not using a “cluster” term here, since the database is a value and it is/can be collocated with readers) the performance will improve even further.

While most of the time I buy arguments on how useless benchmarks are, sometimes they really do help. And believe it or not, my journey from Datalog to Datomic indicies, with a strictly performance agenda, made it possible to apply Datomic to the real big money problem, beyond hello worlds, git gists and prototypes that die after the “initial commit”.

Apr 13

Software as Space-Time Continuum

Is Software for Real?

Here is a question and an answer. They both propose a sequence of logical conclusions, but the answer is of course a “stronger” form of communicating this sequence:

Q: Do you create computer programs? Do you design them based on a business/problem domain? Do you understand this domain? Does this domain apply to the real world? Do you understand the real world? Do you create computer programs based on your understanding of the real world? Do you need to?

A: If you create computer programs they should be based on a business/problem domain. Hence you should understand this domain. Most of the problems/businesses are directly applicable/modeled after the real world. Hence you should understand the real world. Therefore you should create computer programs that apply/modeled after the real world (as much as possible, hence then you can “implement” the domain more closely / find a solution to a problem that can be directly applied to the real world).

While Q and A both follow the same logical sequence, I’d like to explore the Q of things. I’d like to question whether it is really true that we need to design/model our software/languages/libraries after the real world. And if it is true how close we need to “get the real world right” in our software design.

Intuition vs. Intellect

The first instinct, or my “natural intuitive power”, suggests that it is really the case. If we do model after the real world then we are building systems, evolving our metal and software friends who can potentially just coexist with us in our world following the laws of nature. Another supportive argument is a “business problem” that needs to be solved with software. For example “empowering businesses to predict nature”. Of course in order to predict something, we have to understand it and its environment. Currently we do that by taking petabytes of data and slapping it with something like Random Forest, and looking at probabilities… But what if our software just “knew” how things work, not based on historical data, but based on metaphysics, i.e. based on “what the world is and how it really works”.

While I am still not convinced we have to model our software after the real world “all the time”, I do lean towards this idea for the “most problems” I get to work with. In the least number of cases, for example when I get to write a stress test that sends billions of option quotes over the wire, I really don’t care whether it is an “ugly” imperative for loop or a “beautiful” pure function ‘send’ that is mapped over an immutable lazy sequence of quotes. This of course is an over simplification: firstly I should care, and it should be an imperative for loop, since it is faster, and secondly mapping functions over a sequence of things is not really a true modeling of a real world. Or is it?

“A Mad Tea-Party”

Mad Hatter
If modeling after the real world is important, it is obvious we can’t omit “time” dimension when designing and creating software. But most of the time (no pun intended) we do just that. Most widely known/deployed software design approaches/patterns and instruments (e.g. programming languages) are stuck in “Wonderland“:

“Time has punished the Hatter by eternally standing still at 6 pm, and therefore there is always tea time”

Think about a C++/Ruby/Python/Java.. “object”. Does it have a notion of time? No. It may seem it has a notion of “now”, but when it is (its state) teared apart by multiple threads at the same time there is no notion of “now” anymore, and the poor object suffers terribly.

There is a classical talk by Rich Hickey “Are We There Yet?”, where he presents an “Epochal Time Model”:

Epochal Time Model

Where he introduces time as succession of states, and advocates immutability, i.e. the value of state “V1” is forever “V1” at that particular point in time. And we only get to state with a value “V2” after applying a function “F” to the state “V1”. Theoretically if we did support this notion of time, we could just talk to this “timeline”, which Rich calls an identity, and ask “what was its state at that point in time?” or more precisely “when/at which point in time was the state’s ‘value’ equal to “V1″?”. Practically we can do it with Datomic.

Does Time Stutter?

It’s more of a metaphysical thought, but if we are after true representation of the real world, does the “Epochal Time Model” really reflect how the world “changes”? If you wave your hand, does it just hyperjump from a state A to a state B? How granular is the path from A to B? Or is it absolutely “continuous” in which case there is no granularity, i.e. no smallest time interval? If you observe someone waving her hand, it is a different story: “the human eye and its brain interface, the human visual system, can process 10 to 12 separate images per second”, so here is a “state succession” interval. But what does really happen? Is the hand itself moving one planck at a time? Is it moving “de Broglie wavelength” at a time? Is it even important when modeling software?

Do You “Function” Me?

Rich, and many other functional programming advocates, “sell” the idea of functional programming by stressing two things:

1. “This is how things work in the real world…”
2. “It is much easier to reason about…”

While the latter is mostly human based (how “we think”), it is connected to the #1. Since we think one way or another because our thinking is limited by what we know (+ imagination [this is controversial :]). And quite possibly our thinking is based on what we know “about the real world”, which we are part of.

It does seem to be important to model after the real world [ maybe :]. But why now? Why not 20 or 50 years ago? Did any of the programming languages actually aim to even connect to the real world before?

1957 Fortran: concepts included easier entry of equations into a computer

1958 Lisp: created as a practical mathematical notation for computer programs, influenced by the notation of Alonzo Church’s lambda calculus.

1958 ALGOL: was the standard method for algorithm description used by the ACM in textbooks and academic works

1962 Simula: created as a special purpose programming language for simulating discrete event systems

Ok, looks like the closest match is Simula that at least was created to simulate “something”. It is an ironic coincidence that it also is the source of Object Orientation (and actor model), but that is besides the point.

1971 Smalltalk-71 was created by Ingalls in a few mornings on a bet that a programming language based on the idea of message passing inspired by Simula could be implemented in “a page of code.”

1972 Prolog was motivated in part by the desire to reconcile the use of logic as a declarative knowledge representation language with the procedural representation of knowledge

1972 C was designed to be compiled using a relatively straightforward compiler, to provide low-level access to memory, to provide language constructs that map efficiently to machine instructions, and to require minimal run-time support.

1973 ML was conceived to develop proof tactics in the LCF theorem prover (whose language, pplambda, a combination of the first-order predicate calculus and the simply typed polymorphic lambda calculus, had ML as its metalanguage).

1975 Scheme started as an attempt to understand Carl Hewitt’s Actor model, for which purpose Steele and Sussman wrote a “tiny Lisp interpreter” using Maclisp and then “added mechanisms for creating actors and sending messages.”

1979 C++ remembering his Ph.D. experience, Stroustrup set out to enhance the C language with Simula-like features

1986 Erlang was designed with the aim of improving the development of telephony applications

1991 Java was originally designed (as “Oak”) for interactive television, but it was too advanced for the digital cable television industry at the time.

1995 JavaScript was originally implemented as part of web browsers so that client-side scripts could interact with the user, control the browser, communicate asynchronously, and alter the document content that was displayed

Looking at major languages created before “10/20 years ago”, their creational purpose does not seem to be “real world” related. For example the first two are clearly strictly math related.

Emotional Mathematics

So is it about Math? After all, we are “Computer Scientists” and although most of “Computer Programmers” are (unfortunately) very far from math, the science behind computers is very much based on it. Is the goal of mathematics, as a science, to model the real world? Let’s look how we “know to define” math:

math·e·mat·ics  [math-uh-mat-iks]
1. The systematic treatment of magnitude, relationships between figures and forms, 
   and relations between quantities expressed symbolically.
2. A group of related sciences, including algebra, geometry, and calculus, 
   concerned with the study of number, quantity, shape, and space 
   and their interrelationships by using a specialized notation
3. Mathematical operations and processes involved in the solution of a problem 
   or study of some scientific field

Complimenting with “the current world intellect” (wikipedia):

Mathematics "has no generally accepted definition". 
Aristotle defined mathematics as "the science of quantity", 
Benjamin Peirce's "the science that draws necessary conclusions", 
                  "Mathematics is the mental activity which consists 
                  in carrying out constructs one after the other.",
Haskell Curry defined mathematics simply as "the science of formal systems", 
where a formal system is a set of symbols, or tokens, 
and some rules telling how the tokens may be combined into formulas.

From the above definitions it is hard to say whether the “real world modeling” is what Math is after, although we definitely know that Math is there to “explain” things in the world, oh.. wait, that’s Physics :]

If we are after modeling the real world (if it is indeed important), should we try to be as close as possible to the “reality”? Or should we just take the real world in by pieces and convenient definitions that suit a certain process, a problem at hand, programming style, hype, tech movement, etc.? It feels right to be close to the real world, since we are a part of it. It feels right to be close to ourselves. Are we just selfish? :]