Perform customer clustering using R and SQL Server ML Services

USE [tpcxbb_1gb]
DROP PROC IF EXISTS generate_customer_return_clusters;
GO
CREATE procedure [dbo].[generate_customer_return_clusters]
AS
/* 
  This procedure uses R to classify customers into different groups based on their
  purchase & return history.
*/
BEGIN
	DECLARE @duration FLOAT
	, @instance_name NVARCHAR(100) = @@SERVERNAME
	, @database_name NVARCHAR(128) = db_name()
-- Input query to generate the purchase history & return metrics
	, @input_query NVARCHAR(MAX) = N'
SELECT
  ss_customer_sk AS customer,
  round(CASE WHEN ((orders_count = 0) OR (returns_count IS NULL) OR (orders_count IS NULL) OR ((returns_count / orders_count) IS NULL) ) THEN 0.0 ELSE (cast(returns_count as nchar(10)) / orders_count) END, 7) AS orderRatio,
  round(CASE WHEN ((orders_items = 0) OR(returns_items IS NULL) OR (orders_items IS NULL) OR ((returns_items / orders_items) IS NULL) ) THEN 0.0 ELSE (cast(returns_items as nchar(10)) / orders_items) END, 7) AS itemsRatio,
  round(CASE WHEN ((orders_money = 0) OR (returns_money IS NULL) OR (orders_money IS NULL) OR ((returns_money / orders_money) IS NULL) ) THEN 0.0 ELSE (cast(returns_money as nchar(10)) / orders_money) END, 7) AS monetaryRatio,
  round(CASE WHEN ( returns_count IS NULL                                                                        ) THEN 0.0 ELSE  returns_count                 END, 0) AS frequency
  
FROM
  (
    SELECT
      ss_customer_sk,
      -- return order ratio
      COUNT(distinct(ss_ticket_number)) AS orders_count,
      -- return ss_item_sk ratio
      COUNT(ss_item_sk) AS orders_items,
      -- return monetary amount ratio
      SUM( ss_net_paid ) AS orders_money
    FROM store_sales s
    GROUP BY ss_customer_sk
  ) orders
  LEFT OUTER JOIN
  (
    SELECT
      sr_customer_sk,
      -- return order ratio
      count(distinct(sr_ticket_number)) as returns_count,
      -- return ss_item_sk ratio
      COUNT(sr_item_sk) as returns_items,
      -- return monetary amount ratio
      SUM( sr_return_amt ) AS returns_money
    FROM store_returns
    GROUP BY sr_customer_sk
  ) returned ON ss_customer_sk=sr_customer_sk 
 '
EXEC sp_execute_external_script
	  @language = N'R'
	, @script = N'
# Define the connection string
connStr <- paste("Driver=SQL Server;Server=", instance_name, " ;Database=", database_name, " ;Trusted_Connection=true;", sep="" );

# Input customer data that needs to be classified. This is the result we get from our query
customer_returns <- RxSqlServerData(sqlQuery = input_query,
									colClasses = c(customer = "numeric", orderRatio = "numeric", itemsRatio = "numeric", monetaryRatio = "numeric", frequency = "numeric"),
									connectionString = connStr);

# Output table to hold the customer cluster mappings
return_cluster = RxSqlServerData(table = "customer_return_clusters", connectionString = connStr);

# set.seed for random number generator for predicatability
set.seed(10);

# generate clusters using rxKmeans and output clusters to a table called "customer_return_clusters".
clust <- rxKmeans( ~ orderRatio + itemsRatio + monetaryRatio + frequency, customer_returns, numClusters = 4
                    , outFile = return_cluster, outColName = "cluster", writeModelVars = TRUE , extraVarsToWrite = c("customer"), overwrite = TRUE);
'
	, @input_data_1 = N''
	, @params = N'@instance_name nvarchar(100), @database_name nvarchar(128), @input_query nvarchar(max), @duration float OUTPUT'
	, @instance_name = @instance_name
	, @database_name = @database_name
	, @input_query = @input_query
	, @duration = @duration OUTPUT;
END;

GO

--Empty table of the results before running the stored procedure
TRUNCATE TABLE customer_return_clusters;
--Execute the clustering. This will load the table customer_return_clusters with cluster mappings
EXEC [dbo].[generate_customer_return_clusters];
                               

--Now select data from table customer_return_clusters to verify that the clustering data was loaded
SELECT * FROM customer_return_clusters;

USE [tpcxbb_1gb]
SELECT customer.[c_email_address], customer.c_customer_sk
  FROM dbo.customer
  JOIN 
  [dbo].[customer_return_clusters] as r
  ON r.customer = customer.c_customer_sk
  WHERE r.cluster = 3