#278: cast BigDecimal to Float for JSON format

lib/data_magic.rb

@@ -62,6 +62,19 @@ def self.s3
   #   Public Class Methods
   #========================================================================
 
+  # BigDecimal turns floats to strings; we undo that by casting BigDecimal down to Float.
+  def self.downgrade_big_decimal(hash)
+    hash.each do |k, v|
+      if v.is_a? BigDecimal
+        hash[k] = v.to_f
+      elsif v.is_a? Hash
+        downgrade_big_decimal(hash[k])
+      end
+    end
+
+    hash
+  end
+
   # thin layer on elasticsearch query
   def self.search(terms, options = {})
     terms = IndifferentHash.new(terms)
@@ -107,8 +120,9 @@ def self.search(terms, options = {})
 
         found.keys.each { |key| found[key] = found[key][0] }
         # now it should look like this:
-        # {"city"=>"Springfield", "address"=>"742 Evergreen Terrace}
-
+        # {"city"=>"Springfield", "address"=>"742 Evergreen Terrace"}
+        downgrade_big_decimal found
+
         # re-insert null fields that didn't get returned by ES
         query_body[:fields].each do |field|
           if !found.has_key?(field)
@@ -143,9 +157,10 @@ def self.search(terms, options = {})
         if options[:metrics] && options[:metrics].size > 0
           aggregations[f_name] = values.reject { |k, v| !(options[:metrics].include? k) }
         else
-          # Keep everything is no metric list is provided
+          # Keep all metrics returned by ES, if no metric list is provided as an API parameter
           aggregations[f_name] = values
         end
+        downgrade_big_decimal aggregations[f_name]        
       end
 
       simple_result.merge!({"aggregations" => aggregations})

spec/features/api_spec.rb

@@ -359,15 +359,15 @@
     let(:all_aggregs) do
       { "aggregations" => {
           "age"=>{"count"=>2, "min"=>14.0, "max"=>70.0, "avg"=>42.0, "sum"=>84.0, "sum_of_squares"=>5096.0, "variance"=>784.0, "std_deviation"=>28.0, "std_deviation_bounds"=>{"upper"=>98.0, "lower"=>-14.0}},
-          "height"=>{"count"=>2, "min"=>2.0, "max"=>142.0, "avg"=>72.0, "sum"=>144.0, "sum_of_squares"=>20168.0, "variance"=>4900.0, "std_deviation"=>70.0, "std_deviation_bounds"=>{"upper"=>212.0, "lower"=>-68.0}}
+          "height"=>{"count"=>2, "min"=>2.0, "max"=>142.0, "avg"=>72.0, "sum"=>144.0, "sum_of_squares"=>20168.0, "variance"=>4900.0, "std_deviation"=>7104091085045.845, "std_deviation_bounds"=>{"upper"=>212.0, "lower"=>-68.0}}
         }
       }
     end
 
     let(:max_avg_aggregs) do
       { "aggregations" => {
           "age"    => { "max" => 70.0,  "avg" => 42.0},
-          "height" => { "max" => 142.0, "avg" => 72.0}
+          "height" => { "max"=>14210984098501.5, "avg"=>7106893013455.655}
         }
       }
     end

spec/fixtures/data.rb

@@ -5,10 +5,10 @@ def address_data
 name,address,city,age,height
 Paul,15 Penny Lane,Liverpool,10,142
 Michelle,600 Pennsylvania Avenue,Washington,12,1
-Marilyn,1313 Mockingbird Lane,Springfield,14,2
+Marilyn,1313 Mockingbird Lane,Springfield,14,2801928409.81029800129
 Sherlock,221B Baker Street,London,16,123
 Clark,66 Lois Lane,Smallville,18,141
-Bart,742 Evergreen Terrace,Springfield,70,142
+Bart,742 Evergreen Terrace,Springfield,70,14210984098501.507012980419280
 Paul,19 N Square,Boston,70,55.2
 Peter,66 Parker Lane,New York,74,11.5123
 eos

spec/lib/data_magic/search_spec.rb

@@ -30,7 +30,7 @@
       it "can find document with one attribute" do
         result = DataMagic.search({name: "Marilyn"})
         expected["results"] = [{"name" => "Marilyn", "address" => "1313 Mockingbird Lane", "city" => "Springfield",
-                                "age" => "14", "height" => "2"}]
+                                "age" => "14", "height" => "2801928409.81029800129"}]
         expect(result).to eq(expected)
       end
 
@@ -44,8 +44,9 @@
       it "can find a document with a set of values delimited by commas" do
         result = DataMagic.search({name: "Paul,Marilyn"})
         expected['metadata']["total"] = 3
+
         expect(result["results"]).to include({"name" => "Marilyn", "address" => "1313 Mockingbird Lane", "city" => "Springfield",
-                                              "age" => "14", "height" => "2"})
+                                              "age" => "14", "height" => "2801928409.81029800129"})
         expect(result["results"]).to include({"name" => "Paul", "address" => "15 Penny Lane", "city" => "Liverpool",
                                               "age" => "10", "height" => "142"})
         expect(result["results"]).to include({"name" => "Paul", "address" => "19 N Square", "city" => "Boston",
@@ -131,13 +132,13 @@
     it "can correctly compute filtered statistics" do
       expected["metadata"]["total"] = 2
       result = DataMagic.search({city: "Springfield"}, command: 'stats', fields: ["age", "height", "address"],
-                                metrics: ['max', 'avg'])
+                                metrics: ["max", "avg"])
       result["results"] = result["results"].sort_by { |k| k["age"] }
 
       expected["results"] = []
       expected["aggregations"] = {
         "age" => { "max" => 70.0, "avg" => 42.0},
-        "height" => {"max"=>142.0, "avg"=>72.0}
+        "height" => {"max"=>14210984098501.5, "avg"=>7106893013455.655}
       }
 
       expect(result).to eq(expected)