class Sequel::Model::Associations::EagerGraphLoader

# File lib/sequel/model/associations.rb, line 2285
def initialize(dataset)
  opts = dataset.opts
  eager_graph = opts[:eager_graph]
  @master =  eager_graph[:master]
  requirements = eager_graph[:requirements]
  reflection_map = @reflection_map = eager_graph[:reflections]
  reciprocal_map = @reciprocal_map = eager_graph[:reciprocals]
  @unique = eager_graph[:cartesian_product_number] > 1
      
  alias_map = @alias_map = {}
  type_map = @type_map = {}
  after_load_map = @after_load_map = {}
  limit_map = @limit_map = {}
  reflection_map.each do |k, v|
    alias_map[k] = v[:name]
    type_map[k] = v.returns_array?
    after_load_map[k] = v[:after_load] unless v[:after_load].empty?
    limit_map[k] = v.limit_and_offset if v[:limit]
  end

  # Make dependency map hash out of requirements array for each association.
  # This builds a tree of dependencies that will be used for recursion
  # to ensure that all parts of the object graph are loaded into the
  # appropriate subordinate association.
  @dependency_map = {}
  # Sort the associations by requirements length, so that
  # requirements are added to the dependency hash before their
  # dependencies.
  requirements.sort_by{|a| a[1].length}.each do |ta, deps|
    if deps.empty?
      dependency_map[ta] = {}
    else
      deps = deps.dup
      hash = dependency_map[deps.shift]
      deps.each do |dep|
        hash = hash[dep]
      end
      hash[ta] = {}
    end
  end
      
  # This mapping is used to make sure that duplicate entries in the
  # result set are mapped to a single record.  For example, using a
  # single one_to_many association with 10 associated records,
  # the main object column values appear in the object graph 10 times.
  # We map by primary key, if available, or by the object's entire values,
  # if not. The mapping must be per table, so create sub maps for each table
  # alias.
  records_map = {@master=>{}}
  alias_map.keys.each{|ta| records_map[ta] = {}}
  @records_map = records_map

  datasets = opts[:graph][:table_aliases].to_a.reject{|ta,ds| ds.nil?}
  column_aliases = opts[:graph_aliases] || opts[:graph][:column_aliases]
  primary_keys = {}
  column_maps = {}
  models = {}
  row_procs = {}
  datasets.each do |ta, ds|
    models[ta] = ds.model
    primary_keys[ta] = []
    column_maps[ta] = {}
    row_procs[ta] = ds.row_proc
  end
  column_aliases.each do |col_alias, tc|
    ta, column = tc
    column_maps[ta][col_alias] = column
  end
  column_maps.each do |ta, h|
    pk = models[ta].primary_key
    if pk.is_a?(Array)
      primary_keys[ta] = []
      h.select{|ca, c| primary_keys[ta] << ca if pk.include?(c)}
    else
      h.select{|ca, c| primary_keys[ta] = ca if pk == c}
    end
  end
  @column_maps = column_maps
  @primary_keys = primary_keys
  @row_procs = row_procs

  # For performance, create two special maps for the master table,
  # so you can skip a hash lookup.
  @master_column_map = column_maps[master]
  @master_primary_keys = primary_keys[master]

  # Add a special hash mapping table alias symbols to 5 element arrays that just
  # contain the data in other data structures for that table alias.  This is
  # used for performance, to get all values in one hash lookup instead of
  # separate hash lookups for each data structure.
  ta_map = {}
  alias_map.keys.each do |ta|
    ta_map[ta] = [records_map[ta], row_procs[ta], alias_map[ta], type_map[ta], reciprocal_map[ta]]
  end
  @ta_map = ta_map
end