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Whenever you have to analyze a huge Teradata table regarding Multivalue compression, this is a costly operation from a workload point of view.

Unfortunately, Teradata (the company) does not offer any tool which would allow automatizing this task.

Usually, analysis requires counting the number of distinct values per table column. Counting is resource and time intensive for huge tables.

Luckily, with Teradata 14.10, we have a less costly method available:

SHOW STATISTICS VALUES COLUMN <column> ON <table>;

The above statement outputs the most biased column values and many other useful statistics about a column. Usually, the biased values are great candidates for Teradata Multivalue compression.

This approach’s advantage is that no costly table analysis is required (compare this against the approach of counting the distinct column values for each column of a huge table). Nevertheless, it delivers astoundingly good compression suggestions.

By additionally using the number of NULL values per column, you should have a great starting point for a quick win regarding space reduction.

Nevertheless, as good as this method is for achieving quick results, it comes with some drawbacks:

  1. It only works for columns with collected and correct statistics.
  2. Unfortunately, the information used in the SHOW STATISTICS statement is taken from a binary object (“FieldStatistics”). There is no easy way to extract this information. As a substitute, we have to use the text output of the statement and parse it, to be able to automatize the process of creating compress statements.
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Roland Wenzlofsky

Roland Wenzlofsky is an experienced freelance Teradata Consultant & Performance Trainer. Born in Austria's capital Vienna, he is building and tuning some of the largest Teradata Data Warehouses in the European financial and telecommunication sectors for more than 20 years. He has played all the roles of developer, designer, business analyst, and project manager. Therefore, he knows like no other the problems and obstacles that make many data warehouse projects fail and all the tricks and tips that will help you succeed.

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