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LOAD "PL/CBMBASIC",8,1: Commodore 64 BASIC for PostgreSQL

If you are of a certain age, the words 38911 BASIC BYTES FREE will bring memories flooding back. You remember the blue screen that you had spent hours staring at, and all those games in magazines that you could type in line by line, and not really understanding most of what you're even typing. You remember that the disk drive was device 8, and that you had time to go make a cup of tea before it would finish loading. All of that now runs inside PostgreSQL. PL/CBMBASIC is a procedural language extension that executes function bodies on Commodore 64 BASIC V2. The actual Microsoft/Commodore interpreter from 1982, by way of Michael Steil's cbmbasic project, which statically recompiled the 6502 ROM into C. That C is compiled into the extension's shared library, so the interpreter lives inside your backend process. Every function call is an in-memory power cycle: zero the 64KB RAM array, reset the CPU registers, and re-enter the ROM at $E394. The whole thing costs about 15 to 20...
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Don't let your PostgreSQL get exploited

As you may have heard, there are reportedly over 1,500 PostgreSQL servers that have been exploited to mine Bitcoin. And your server could be next if you haven't taken precautions. Firstly, you need to update to the latest minor release, just so no known exploitable bugs exist on your system. But regardless of whether you update, your PostgreSQL instance could still be misconfigured in a way that would allow unwelcome visitors access, so you need to make sure you shore up your defenses. Here are some steps you should take. 1. Get it off the internet Your database shouldn't be accessible from the open internet. People run port scanners on public IP addresses all the time, and yours will eventually be found. Edit postgresql.conf and ensure listen_addresses isn't set to "*" , because this tells PostgreSQL to accept connections from any network interface. Instead, make sure it only listens to connections from the local network. For example: listen_addresses = '...
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jsquery vs SQL/JSON

SQL/JSON is coming to PostgreSQL 12 and provides a native way to query JSON data (although, to be specific, JSON data stored as a JSONB data type).  This also introduces the jsonpath data type which is used for SQL/JSON query expressions.  I'll not be going into its usage in detail, or covering performance characteristics (at least not in this post), but I will compare the syntax and functionality with jsquery.  Note that this may potentially change prior to final release. jsquery was introduced as a non-core extension for PostgreSQL 9.4 and higher by Teodor Sigaev, Alexander Korotkov and Oleg Bartunov.  Like jsonpath, it also used its own datatype, jsquery. We have some functions to which we can pass jsonpath expressions to, 2 of which have operators which can be used as shorthand (albeit without additional parameter control, as they exist primarily for indexing purposes): Function Operator Description jsonb_path_exists ...
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PostgreSQL 9.6 - Part 1.1 - Horizontal Scalability revisited

In my previous blog post about horizontal scalability changes in PostrgreSQL 9.6, I covered pushing sorts and joins to the remote server, but Robert Haas (EnterpriseDB) has just committed a change that allows DML (that's UPDATEs and DELETEs) to be pushed to the remote server too. This is thanks to the work of Etsuro Fujita (NTT) with advice and testing from Rushabh Lathia (EnterpriseDB), Shigeru Hanada, Robert Haas (EnterpriseDB), Kyotaro Horiguchi (NTT), Albe Laurenz and myself (EnterpriseDB). So this calls for an appendix to my original post! DML pushdown The problem previously was that an update or a delete would mean fetching a batch of rows from the remote server, and sending individual UPDATE commands to the remote server. So if we ran this on the local server (where remote.big_table is a remote table which resides on the remote server): UPDATE remote.big_table SET content = content || '.'; The remote server would receive the following request from the local s...
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PostgreSQL 9.6 - Part 2 - Monitoring

This is part 2 in a 4 part blog series on improvements coming in PostgreSQL 9.6. Part 1 - Horizontal Scalability Join Pushdown Sort Pushdown "Walk and chew gum at the same time" Part 2 - Monitoring VACUUM progress monitoring Wait monitoring Part 3 - Parallelism Part 4 - Vertical Scalability VACUUM progress monitoring When you run VACUUM on a large table, do you know how much it's done after 5 minutes? Do you know how much more there is to go? The answer is, no. You can't know, at least not accurately or easily. In PostgreSQL 9.6, you'll be able to monitor just this (although not VACUUM FULL), thanks to the work of Amit Langote (NTT) and Robert Haas (EnterpriseDB), which was built upon the work done by Rahila Syed (EnterpriseDB) and Vinayak Pokale (NTT). We now have a system view called pg_stat_progress_vacuum. This is the first in, hopefully, several progress monitoring views to come in future. Here's an example of what it shows you (shown in...
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PostgreSQL 9.6 - Part 1 - Horizontal Scalability

PostgreSQL 9.6 is shaping up to be an impressive release, so I thought I'd try to summarise some of the big features and improvements that it will bring. This certainly won't be exhaustive, but it will touch upon areas I've looked at closely. I'm looking at breaking this down into the following areas: Part 1 - Horizontal Scalability Part 2 - Monitoring Part 3 - Parallelism Part 4 - Vertical Scalability So without further ado, here's Part 1 - Horizontal Scalability I guess I should start with the question some might be asking: "What is 'Horizontal Scalability'?" This is just a fancy way of describing the ability to distribute workload among several clusters/servers/locations etc. So rather than putting all the burden on one server, you can delegate at least some of the work to other servers to speed things up. For 9.6, I'll specifically be covering foreign tables (i.e. tables on remote servers which are being queried as if they wer...
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This is a blog test

This is just a blog test. Please ignore.
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