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Amazon Redshift
Database Developer Guide (API Version 2012-12-01)

Step 8: Evaluate the Results

You tested load times, storage requirements, and query execution times before and after tuning the tables, and recorded the results.

The following table shows the example results for the cluster that was used for this tutorial. Your results will be different, but should show similar improvements.

Benchmark Before After Change %
Load time (five tables) 623 732 109 17.5%
Storage Use
LINEORDER 51024 27152 -23872 -46.8%
PART 200 200 0 0%
CUSTOMER 384 604 220 57.3%
DWDATE 160 160 0 0%
SUPPLIER 152 236 84 55.3%
Total storage 51920 28352 -23568 -45.4%
Query execution time
Query 1 6.97 3.19 -3.78 -54.2%
Query 2 12.81 9.02 -3.79 -29.6%
Query 3 13.39 10.54 -2.85 -21.3%
Total execution time 33.17 22.75 -10.42 -31.4%

Load time

Load time increased by 17.5%.

Sorting, compression, and distribution increase load time. In particular, in this case, you used automatic compression, which increases the load time for empty tables that don't already have compression encodings. Subsequent loads to the same tables would be faster. You also increased load time by using ALL distribution. You could reduce load time by using EVEN or DISTKEY distribution instead for some of the tables, but that decision needs to be weighed against query performance.

Storage requirements

Storage requirements were reduced by 45.4%.

Some of the storage improvement from using columnar compression was offset by using ALL distribution on some of the tables. Again, you could improve storage use by using EVEN or DISTKEY distribution instead for some of the tables, but that decision needs to be weighed against query performance.

Distribution

You verified that there is no distribution skew as a result of your distribution choices.

By checking the EXPLAIN plan, you saw that data redistribution was eliminated for the test queries.

Query execution time

Total query execution time was reduced by 31.4%.

The improvement in query performance was due to a combination of optimizing sort keys, distribution styles, and compression. Often, query performance can be improved even further by rewriting queries and configuring workload management (WLM). For more information, see Tuning Query Performance.

Next Step

Step 9: Clean Up Your Resources

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