Avro schemas

To store JSON data as tuples, we will apply a savvy practice which reduces data footprint and ensures all stored documents are valid. We will use Tarantool module avro-schema which checks the schema of a JSON document and converts it to a Tarantool tuple. The tuple will contain only field values, and thus take a lot less space than the original document. In avro-schema terms, converting JSON documents to tuples is “flattening”, and restoring the original documents is “unflattening”.

First you need to install the module with tt rocks install avro-schema.

Further usage is quite straightforward:

1. For each entity, we need to define a schema in Apache Avro schema syntax, where we list the entity’s fields with their names and Avro data types.
2. At initialization, we call avro-schema.create() that creates objects in memory for all schema entities, and compile() that generates flatten/unflatten methods for each entity.
3. Further on, we just call flatten/unflatten methods for a respective entity on receiving/sending the entity’s data.

Here’s what our schema definitions for the player and pokémon entities look like:

local schema = {
    player = {
        type="record",
        name="player_schema",
        fields={
            {name="id", type="long"},
            {name="name", type="string"},
            {
                name="location",
                type= {
                    type="record",
                    name="player_location",
                    fields={
                        {name="x", type="double"},
                        {name="y", type="double"}
                    }
                }
            }
        }
    },
    pokemon = {
        type="record",
        name="pokemon_schema",
        fields={
            {name="id", type="long"},
            {name="status", type="string"},
            {name="name", type="string"},
            {name="chance", type="double"},
            {
                name="location",
                type= {
                    type="record",
                    name="pokemon_location",
                    fields={
                        {name="x", type="double"},
                        {name="y", type="double"}
                    }
                }
            }
        }
    }
}

And here’s how we create and compile our entities at initialization:

-- load avro-schema module with require()
local avro = require('avro_schema')

-- create models
local ok_m, pokemon = avro.create(schema.pokemon)
local ok_p, player = avro.create(schema.player)
if ok_m and ok_p then
    -- compile models
    local ok_cm, compiled_pokemon = avro.compile(pokemon)
    local ok_cp, compiled_player = avro.compile(player)
    if ok_cm and ok_cp then
        -- start the game
        <...>
    else
        log.error('Schema compilation failed')
    end
else
    log.info('Schema creation failed')
end
return false

As for the map entity, it would be an overkill to introduce a schema for it, because we have only one map in the game, it has very few fields, and – which is most important – we use the map only inside our logic, never exposing it to external users.

Next, we need methods to implement the game logic. To simulate object-oriented programming in our Lua code, let’s store all Lua functions and shared variables in a single local variable (let’s name it as game). This will allow us to address functions or variables from within our module as self.func_name or self.var_name. Like this:

local game = {
    -- a local variable
    num_players = 0,

    -- a method that prints a local variable
    hello = function(self)
      print('Hello! Your player number is ' .. self.num_players .. '.')
    end,

    -- a method that calls another method and returns a local variable
    sign_in = function(self)
      self.num_players = self.num_players + 1
      self:hello()
      return self.num_players
    end
}

In OOP terms, we can now regard local variables inside game as object fields, and local functions as object methods.

So, our game module will have the following methods:

• catch() to calculate whether the pokémon was caught (besides the coordinates of both the player and pokémon, this method will apply a probability factor, so not every pokémon within the player’s reach will be caught);
• respawn() to add missing pokémons to the map, say, every 60 seconds (we assume that a frightened pokémon runs away, so we remove a pokémon from the map on any catch attempt and add it back to the map in a while);
• notify() to log information about caught pokémons (like “Player 1 caught pokémon A”);
• start() to initialize the game (it will create database spaces, create and compile avro schemas, and launch respawn()).

Besides, it would be convenient to have methods for working with Tarantool storage. For example:

• add_pokemon() to add a pokémon to the database, and
• map() to populate the map with all pokémons stored in Tarantool.

We’ll need these two methods primarily when initializing our game, but we can also call them later, for example to test our code.