postgresql

In the previous post my queries were still reading the indexed column only, from a table which had no modifications since the last vacuum, and then didn’t need to read table pages: it was Index Only Scan. However, we often need more columns than the ones that are in the index. Here is the Index Scan access path.

We have seen how an index can help to avoid a sorting operation in the previous post. This avoids a blocking operation: the startup cost is minimal and the first rows can be immediately returned. This is often desired when displaying rows to the user screen. Here is more about Postgres startup cost, Oracle first_rows costing, and fetching first rows only.

Here is the execution plan we had in Oracle to get the values of N sorted. The cost for Oracle is the cost to read the index leaves: estimated to 46 random reads:

PLAN_TABLE_OUTPUT
------------------------------------------------------------------------------------------------------------------------------------------------------
SQL_ID dbck3rgnqbakg, child number 0
-------------------------------------

I realize that I’m talking about indexes in Oracle and Postgres, and didn’t mention yet the best website you can find about indexes, with concepts and examples for all RDBMS: http://use-the-index-luke.com. You will probably learn a lot about SQL design. Now let’s continue on execution plans with indexes.

In the previous post I said that an Index Only Access needs to find all rows in the index. Here is a case where, with similar data, Postgres can find all rows but Oracle needs additional considerations.

In the previous post I’ve executed:
select sum(n) from demo1
The execution plan was:

Aggregate (cost=295.29..295.30 rows=1 width=8) (actual time=2.192..2.193 rows=1 loops=1)
Output: sum(n)
Buffers: shared hit=30
-> Index Only Scan using demo1_n on public.demo1 (cost=0.29..270.29 rows=10000 width=4) (actual time=0.150..1.277 rows=10000 loops=1)
Output: n
Heap Fetches: 0
Buffers: shared hit=30


In the previous post I’ve explained a sequential scan by accident: my query needed only one column which was indexed, and I expected to read the index rather than the table. And I had to hint the Oracle example to get the same because the Oracle optimizer chooses the index scan over the table scan in that case. Here is where I learned a big difference between Postgres and Oracle. They both use MVCC to query without locking, but Postgres MVCC is for table rows (tuples) only whereas Oracle MVCC is for all blocks – tables and indexes.

Here is the first test I’ve done for my Postgres vs. Oracle access paths series and the first query did a sequential scan. It illustrates the first constant you find in the documentation for the query planner:
seq_page_cost (floating point)
Sets the planner’s estimate of the cost of a disk page fetch that is part of a series of sequential fetches. The default is 1.0.

I’ll start a series on Postgres vs. Oracle access paths because I know Oracle and I learn Postgres. While preparing it, I came upon some surprises because I’m so used to Oracle that I take some behavior as granted for any SQL databases. I recently posted a tweet about one of them, comparing latest Postgres version to earliest Oracle version I have on my laptop.
The goal of the tweet was exactly what I said above: show my surprise, using Oracle 7 as a reference because this is the version where I started to learn SQL. And there’s no judgment behind this surprise: I can’t compare a software I use for more than 20 years with one I’m just learning. I have a big admiration for the Oracle design and architecture choices. But I’ve also a big admiration for what the Postgres community is doing.

This is the start of a series on PostgreSQL execution plans, access path, join methods, hints and execution statistics. The approach will compare Postgres and Oracle. It is not a comparison to see which one is better, but rather to see what is similar and where the approaches diverge. I have a long experience of reading Oracle execution plans and no experience at all on Postgres. This is my way to learn and share what I learn. You will probably be interested if you are in the same situation: an Oracle DBA wanting to learn about Postgres. But you may also be an experienced Postgres DBA who wants to see a different point of view from a different ‘culture’.

I’ll probably use the Oracle terms more often as I’m more familiar with them: blocks for pages, optimizer for query planner, rows for tuples, tables for relations…

I run my laptop with Windows 10 for office programs, and VirtualBox machines with Linux for the big stuff (Oracle databases). I have also Cygwin installed on Windows for GNU programs. I wanted to quickly install PosgreSQL and rather than installing it in a Linux VM, or as a Windows program, I installed the Cygwin version of it. Here is how.

Cygwin

Cygwin is easy to install: just run the setup-x86_64.exe from https://www.cygwin.com/ and choose the packages you want to install. Here is what is related to PostgreSQL:

This is the third part in a series of blogposts about how postgresql manages data in its blocks (called ‘pages’ in postgres speak). If you found this post and did not read the previous ones, it might be beneficial to read block internals (part 1) and block internals, part 2 first. In these blogposts I’ve shown how heap and index pages look like, and how these can be investigated, including looking at the raw block information.

This blogpost is intended to show the effects on pages when DML happens. This is inherently different from my personal reference of database implementation, which is the oracle database.