Step 5: Testing System Performance in the New Table

After recreating the test data set with the selected storage modes, compression levels, distribution modes, and distribution keys, you will retest the system performance.

Record the storage space usage of each table.

Determine how much disk space is used for each table using the pg_size_pretty function and record the results in base tables.

     
          SELECT T_NAME, PG_SIZE_PRETTY(PG_RELATION_SIZE(t_name)) FROM (VALUES('store_sales'),('date_dim'),('store'),('item'),('time_dim'),('promotion'),('customer_demographics'),('customer_address'),('household_demographics'),('customer'),('income_band')) AS names1(t_name);

         t_name         | pg_size_pretty
------------------------+----------------
 store_sales            | 14 GB
 date_dim               | 27 MB
 store                  | 4352 kB
 item                   | 259 MB
 time_dim               | 14 MB
 promotion              | 3200 kB
 customer_demographics  | 11 MB
 customer_address       | 27 MB
 household_demographics | 1280 kB
 customer               | 111 MB
 income_band            | 896 kB
(11 rows)

Test the query performance and record the performance data in the benchmark table.

Execute the following queries again and record the time spent on each query.

     
      
        
        
          \timing on
SELECT * FROM (SELECT  COUNT(*)  
FROM store_sales 
    ,household_demographics  
    ,time_dim, store 
WHERE ss_sold_time_sk = time_dim.t_time_sk    
    AND ss_hdemo_sk = household_demographics.hd_demo_sk  
    AND ss_store_sk = s_store_sk 
    AND time_dim.t_hour = 8 
    AND time_dim.t_minute >= 30 
    AND household_demographics.hd_dep_count = 5 
    AND store.s_store_name = 'ese' 
ORDER BY COUNT(*) 
 ) LIMIT 100;

SELECT * FROM (SELECT  i_brand_id brand_id, i_brand brand, i_manufact_id, i_manufact,
SUM(ss_ext_sales_price) ext_price
 FROM date_dim, store_sales, item,customer,customer_address,store
 WHERE d_date_sk = ss_sold_date_sk
   AND ss_item_sk = i_item_sk
   AND i_manager_id=8
   AND d_moy=11
   AND d_year=1999
   AND ss_customer_sk = c_customer_sk 
   AND c_current_addr_sk = ca_address_sk
   AND substr(ca_zip,1,5) <> substr(s_zip,1,5) 
   AND ss_store_sk = s_store_sk 
 GROUP BY i_brand
      ,i_brand_id
      ,i_manufact_id
      ,i_manufact
 ORDER BY ext_price desc
         ,i_brand
         ,i_brand_id
         ,i_manufact_id
         ,i_manufact
 ) LIMIT 100;

SELECT * FROM (SELECT  s_store_name, s_store_id,
        SUM(CASE WHEN (d_day_name='Sunday') THEN ss_sales_price ELSE null END) sun_sales,
        SUM(CASE WHEN (d_day_name='Monday') THEN ss_sales_price ELSE null END) mon_sales,
        SUM(CASE WHEN (d_day_name='Tuesday') THEN ss_sales_price ELSE  null END) tue_sales,
        SUM(CASE WHEN (d_day_name='Wednesday') THEN ss_sales_price ELSE null END) wed_sales,
        SUM(CASE WHEN (d_day_name='Thursday') THEN ss_sales_price ELSE null END) thu_sales,
        SUM(CASE WHEN (d_day_name='Friday') THEN ss_sales_price ELSE null END) fri_sales,
        SUM(CASE WHEN (d_day_name='Saturday') THEN ss_sales_price ELSE null END) sat_sales
 FROM date_dim, store_sales, store
 WHERE d_date_sk = ss_sold_date_sk AND
       s_store_sk = ss_store_sk AND
       s_gmt_offset = -5 AND
       d_year = 2000 
 GROUP BY s_store_name, s_store_id
 ORDER BY s_store_name, s_store_id,sun_sales,mon_sales,tue_sales,wed_sales,thu_sales,fri_sales,sat_sales
  ) LIMIT 100;

         

       

     
    

The following benchmark table shows the validation results of the cluster used in this tutorial. Your results may vary based on a number of factors, but the relative results should be similar. The execution durations of queries having the same table structure can be different, depending on the OS cache during execution. You are advised to perform several rounds of tests and select a group with average values.

Benchmark	Before	After
Loading time (11 tables)	341584 ms	257241 ms
Occupied storage space
Store_Sales	42 GB	14 GB
Date_Dim	11 MB	27 MB
Store	232 KB	4352 KB
Item	110 MB	259 MB
Time_Dim	11 MB	14 MB
Promotion	256 KB	3200 KB
Customer_Demographics	171 MB	11 MB
Customer_Address	170 MB	27 MB
Household_Demographics	504 KB	1280 KB
Customer	441 MB	111 MB
Income_Band	88 KB	896 KB
Total storage space	42 GB	15 GB
Query execution time
Query 1	14552.05 ms	1783.353 ms
Query 2	27952.36 ms	14247.803 ms
Query 3	17721.15 ms	11441.659 ms
Total execution time	60225.56 ms	27472.815 ms

If you have higher expectations for the performance after the table design, you can run the EXPLAIN PERFORMANCE command to view the execution plan for tuning.

For more details about execution plans and query tuning, see SQL Execution Plan and Query Performance Tuning Overview.