1

This is my current table definition in a Postgres 10.1-1 database:

CREATE TYPE CUSTOMER_TYPE AS ENUM
('enum1', 'enum2', 'enum3', '...', 'enum15');     -- max length of enum names ~15

CREATE TABLE CUSTOMER(
   CUSTOMER_ONE    TEXT PRIMARY KEY NOT NULL,     -- max 35 char String
   ATTRIBUTE_ONE   TEXT UNIQUE,                   -- max 35 char String
   ATTRIBUTE_TWO   TEXT,                          -- 1-80 char String
   PRIVATEKEYTYPE  CUSTOMER_TYPE                  -- see enum
);

It results in about 4.3x more database size compared to the size of the inserted data. (50 MB, 700.000 lines --> database size is 210 MB)

Attribute_One is computed as hash(Customer_One).

Requirements: fast searches (using algorithms) for columns CUSTOMER_ONE and ATTRIBUTE_ONE. (That's why I think I need an index.)

Typical search query:

select * from customer
where Customer_One='XXX' OR Attribute_One='XXX';

Each SELECT can find a maximum of 1 or 0 matching rows in millions of rows.

Is it possible to further decrease the DB size? I have been told to use an expression index but don't fully understand how this works. A short explanation with an example index or other solution would be great

Is the insert speed effected by those indexes? The faster the better. (To be clear: search speed is more important than insert speed.)

4
  • 1
    You omitted important details. In a comment to your your previous question you mentioned: Attribute_One is calculated from Customer_One. How exactly? And what "algorithms" do you use in your "fast searches"? Show a typical example query. Also: your version of Postgres, please. Dec 14, 2017 at 22:58
  • Attribute_One = Hash(Customer_One); I dont use any specific search algorithms, I want Postgres to use them (and be able to do it). Each select can find a maximum of 1 or 0 matching rows in millions of rows. PG version v.10.1-1. Typical search: select * from customer where Customer_One='XXX' OR Attribute_One='XXX'. Thank you :)
    – A.c
    Dec 15, 2017 at 12:15
  • 1
    All defining information should go into your question, not comments. Dec 15, 2017 at 13:17
  • Done! Sorry, wasnt aware of that.
    – A.c
    Dec 15, 2017 at 13:55

1 Answer 1

1

If hash() is an IMMUTABLE function (which should be the case for a function called "hash"!) you can omit storing the functionally dependent attribute_one in the table altogether and add an expression index to support queries on the expression hash(customer_one):

CREATE TABLE customer (
   privatekeytype customer_type     -- move the enum to 1st pos to save some more 
 , customer_one   text PRIMARY KEY
 , attribute_two  text
);

Expression index:

CREATE INDEX customer_attribute_one_idx ON customer (hash(customer_one));

This is exactly as big (identical) as the index supporting your original UNIQUE constraint on the redundant column attribute_one.

Query:

SELECT *
FROM   customer 
WHERE  'XXX' IN (customer_one, hash(customer_one));

Testing with EXPLAIN you'll see index or bitmap index scans like:

->  BitmapOr  (cost=5.34..5.34 rows=5 width=0)
     ->  Bitmap Index Scan on customer_pkey  (cost=0.00..2.66 rows=1 width=0)
           Index Cond: ('XXX'::text = customer.customer_one)
     ->  Bitmap Index Scan on customer_attribute_one_idx  (cost=0.00..2.68 rows=4 width=0)
           Index Cond: ('XXX'::text = hash(customer.customer_one))

About the same performance as with the redundant table column or faster since the table is smaller, yet - which helps overall performance in various ways.

Moving the enum to first position saves a few bytes of alignment padding per row as explained in my previous answer:

Why does the function have to be IMMUTABLE? See:

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge that you have read and understand our privacy policy and code of conduct.

Not the answer you're looking for? Browse other questions tagged or ask your own question.