Waiting for PostgreSQL 16 – Allow underscores in integer and numeric constants.

On 4th of February 2023, Dean Rasheed committed patch:

Allow underscores in integer and numeric constants.
 
This allows underscores to be used in integer and numeric literals,
and their corresponding type input functions, for visual grouping.
For example:
 
    1_500_000_000
    3.14159_26535_89793
    0xffff_ffff
    0b_1001_0001
 
A single underscore is allowed between any 2 digits, or immediately
after the base prefix indicator of non-decimal integers, per SQL:202x
draft.
 
Peter Eisentraut and Dean Rasheed
 
Discussion: https://postgr.es/m/84aae844-dc55-a4be-86d9-4f0fa405cc97%40enterprisedb.com

Continue reading Waiting for PostgreSQL 16 – Allow underscores in integer and numeric constants.

Waiting for PostgreSQL 16 – Invent random_normal() to provide normally-distributed random numbers.

On 9th of January 2023, Tom Lane committed patch:

Invent random_normal() to provide normally-distributed random numbers.
 
There is already a version of this in contrib/tablefunc, but it
seems sufficiently widely useful to justify having it in core.
 
Paul Ramsey
 
Discussion: https://postgr.es/m/CACowWR0DqHAvOKUCNxTrASFkWsDLqKMd6WiXvVvaWg4pV1BMnQ@mail.gmail.com

Continue reading Waiting for PostgreSQL 16 – Invent random_normal() to provide normally-distributed random numbers.

Waiting for PostgreSQL 16 – Non-decimal integer literals

On 14th of December 2022, Peter Eisentraut committed patch:

Non-decimal integer literals 
 
Add support for hexadecimal, octal, and binary integer literals:
 
    0x42F
    0o273
    0b100101
 
per SQL:202x draft.
 
This adds support in the lexer as well as in the integer type input
functions.
 
Reviewed-by: John Naylor <john.naylor@enterprisedb.com>
Reviewed-by: Zhihong Yu <zyu@yugabyte.com>
Reviewed-by: David Rowley <dgrowleyml@gmail.com>
Reviewed-by: Dean Rasheed <dean.a.rasheed@gmail.com>
Discussion: https://www.postgresql.org/message-id/flat/b239564c-cad0-b23e-c57e-166d883cb97d@enterprisedb.com

Continue reading Waiting for PostgreSQL 16 – Non-decimal integer literals

Waiting for PostgreSQL 16 – Add grantable MAINTAIN privilege and pg_maintain role.

On 14th of December 2022, Jeff Davis committed patch:

Add grantable MAINTAIN privilege and pg_maintain role.
 
Allows VACUUM, ANALYZE, REINDEX, REFRESH MATERIALIZED VIEW, CLUSTER,
and LOCK TABLE.
 
Effectively reverts 4441fc704d. Instead of creating separate
privileges for VACUUM, ANALYZE, and other maintenance commands, group
them together under a single MAINTAIN privilege.
 
Author: Nathan Bossart
Discussion: https://postgr.es/m/20221212210136.GA449764@nathanxps13
Discussion: https://postgr.es/m/45224.1670476523@sss.pgh.pa.us

Continue reading Waiting for PostgreSQL 16 – Add grantable MAINTAIN privilege and pg_maintain role.

Waiting for PostgreSQL 16 – Add test scaffolding for soft error reporting from input functions.

Title: On 9th of December 2022, Tom Lane committed patch:

Add test scaffolding for soft error reporting from input functions.
 
pg_input_is_valid() returns boolean, while pg_input_error_message()
returns the primary error message if the input is bad, or NULL
if the input is OK.  The main reason for having two functions is
so that we can test both the details-wanted and the no-details-wanted
code paths.
 
Although these are primarily designed with testing in mind,
it could well be that they'll be useful to end users as well.
 
This patch is mostly by me, but it owes very substantial debt to
earlier work by Nikita Glukhov, Andrew Dunstan, and Amul Sul.
Thanks to Andres Freund for review.
 
Discussion: https://postgr.es/m/3bbbb0df-7382-bf87-9737-340ba096e034@postgrespro.ru

Continue reading Waiting for PostgreSQL 16 – Add test scaffolding for soft error reporting from input functions.

Picking random element, with weights

Whenever I'm doing some testing I need sample data. Easiest way to do it is to generate data using some random/generate_series queries.

But what if I need specific frequencies?

For example, I need to generate 10,000,000 rows, where there will be 10% of ‘a', 20% of ‘b', and the rest will be split equally between ‘c' and ‘d'?

Continue reading Picking random element, with weights