Monday, October 6, 2014

pg_repack pitfalls

pg_repack is a terrific tool for allowing you to reorganize a table without needing to hold long running strong locks on the table. That means that that your normal inserts, updates and deletes can continue to run against the table while the reorganization is proceeding.

I have had clients who have run into problems with it, however. In particular, it is possible to get it wedged so that the table is inaccessible and nothing can proceed, unless you either kill the repack operation or kill what is blocking it. Here is a simple example of how to cause problems.

In session 1, do:
pg_reorg -e -t foo dbnameset

and in session 2 in psql do:
select pg_sleep(10); lock table foo; rollback;
The sleep gets us past the time when pg_reorg is setting up, and happens while it is is doing its CREATE TABLE ... AS SELECT .... When that CREATE TABLE statement finishes, both sessions will be wedged.  Session 2 will be hung because it is unable to lock the table, since pg_reorg's other session will hold a weak lock on the table. And nothing, including pg_reorg, will be able to do anything with the table.

The solution is to make sure that nothing holds or even tries to obtain any strong long running locks on the table.

One useful thing is to use the monitor script to look for things like long running transactions and processes waiting for locks.

Or you can create a more customized test to look for this exact situation.

Most importantly, you need to be aware that problems can occur, and to protect against them happening in the first place.

Friday, October 3, 2014

Towards a PostgreSQL Benchfarm

For years I have been wanting to set up a farm of machines, modelled after the buildfarm, that will run some benchmarks and let us see performance regressions. Today I'm publishing some progress on that front, namely a recipe for vagrant to set up an instance on AWS of the client I have been testing with. All this can be seen on the PostgreSQL Buildfarm Github Repository on a repo called aws-vagrant-benchfarm-client. The README explains how to set it up. The only requirement is that you have vagrant installed and the vagrant-aws provider set up (and, of course, an Amazon AWS account to use).

Of course, we don't want to run members of the benchfarm on smallish AWS instances. But this gives me (and you, if you want to play along) something to work on, and the provisioning script documents all the setup steps rather than relying on complex instructions.

The provisioner installs a bleeding edge version of the buildfarm client's experimental Pgbench module, which currently only exists on the "benchfarm" topic branch. This module essentially runs Greg Smith's pgbench-tools suite, gets the results from the results database's "tests" table, and bundles it as a CSV for upload to the server.

Currently the server does nothing with it. This will just look like another buildfarm step. So the next thing to do is to get the server to start producing some pretty and useful graphs. Also, we need to decide what else we might want to capture.

Friday, September 26, 2014

Big O playing catchup.

I see that a new release of MySQL has been made, and they are touting the fact that they are allowing the omission of unaggregated items in a SELECT list from a GROUP BY clause, if they are functionally dependent on the items in the GROUP BY clause. This would happen, for example, where the items in the GROUP BY list form a primary key. It's a nice feature.

It's also a feature that PostgreSQL has had for three years.

Importing JSON data

Say you have a file that consists of one JSON document per line. How can you import it into a table easily? This is a problem I was called on to help a colleague with yesterday. Using COPY is the obvious answer, but this turns out not to be quite so simple to do.

In text mode, COPY will be simply defeated by the presence of a backslash in the JSON. So, for example, any field that contains an embedded double quote mark, or an embedded newline, or anything else that needs escaping according to the JSON spec, will cause failure. And in text mode you have very little control over how it works - you can't, for example, specify a different ESCAPE character. So text mode simply won't work.

CSV mode is more flexible, but poses different problems. Here, instead of backslash causing a problem, QUOTE characters can cause a problem. First, JSON itself uses the default QUOTE character (double quote) to quote all string values. But if we change use an alternative like single quote, then the presence of any single quote in the JSON leads us into difficulties. Second, JSON also uses the default DELIMITER (comma) extensively. So, clearly we need to use something else for the QUOTE and DELIMITER options. (By default, in CSV mode, the ESCAPE character is the same as the QUOTE character, so we don't need to worry about it separately.)

What we in fact want is  to specify QUOTE and DELIMITER characters that can't appear at all in the JSON. Then the whole line will be seen as a single unquoted datum, which is exactly what we want. There is a small set of single-byte characters that happen to be illegal in JSON, so we can be sure that choosing them for these options should do the right thing with any legal JSON. These are the control characters. So the solution we came up with looks like this:
copy the_table(jsonfield) 
from '/path/to/jsondata' 
csv quote e'\x01' delimiter e'\x02';
Of course, if the JSON has embedded newlines as punctuation, this wont work. So it's important that you configure whatever is producing the JSON not to insert newlines anywhere but at the end of each JSON document.

Now this solution is a bit of a hack. I wonder if there's a case for a COPY mode that simply treats each line as a single datum. I also wonder if we need some more specialized tools for importing JSON, possibly one or more Foreign Data Wrappers. Such things could handle, say, embedded newline punctuation.

Note too that files produced by PostgreSQL's COPY ... TO command will be properly quoted and escaped and won't need to be handled like this to read them back. Of course, if you want them to be readable by other non-CSV processors, then you might need to use similar options to those above to avoid unwanted quoting and escaping.

Monday, September 8, 2014

PLV8 and harmony scoping

The other day I complained on the PostgreSQL hackers list about a couple of aspects of Javascript that make it quite bothersome for large scale programming, namely the old style variable scoping rules and the very limited string literals, which can't stretch across lines (don't mention the awful backslash trick, please) and don't have any provision for interpolation. If you're used as I am to Perl, which has had lexically scoped variables for about 20 years and awsome string literal support for a good deal longer than that, these things are really quite painful.

The good news if that the forthcoming standard, ECMAScript6, also known as "harmony", contains features to deal with both of these issues.

The latest versions of the V8 engine actually support harmony scoping rules, with one restriction, namely that it's only supported in contexts that are in "strict" mode. I believe that this restriction will go away in due course.

Petr Jelinek dropped me a note that other day to tell me how to set V8 flags, and based in that I have developed a patch for PLV8 that allows for harmony scoping. It requires a new GUC setting that is applied during the module's initialization code.

This is available in my clone of the plv8 code, and you can see what it's doing at

I'll do a bit more testing and then talk to the other PLV8 developers about merging it in.

Things are less rosy on the string handling front, I'm afraid. I have no idea when V8 will get the "template strings" feature that will address the string literal deficiencies. As far as I can tell nobody is working on it.

Friday, August 22, 2014

Hoist on my own PLV8 petard

I mentioned to a client that I was going to write a function they had asked me to write using PLPerl, because it has good dynamic string handling capabilities that make it a better fit for this particular task than PLPgsql. "Oh," said the client, "we don't do much Perl. But ever since you hooked us up with PLV8 we do everything in JavaScript. We all know that, and use it every day." So I'm now writing it in Javascript. Proof once again that no good deed goes unpunished. It remains to be seen if it's going to be quite such a good fit as Perl would be, but at least it will give me a thorough refresher in JS.

Thursday, August 21, 2014

Looking for emacs mixed mode editing for functions

I've been looking for a way to edit mixed mode files in emacs, so I can edit a plperl function, and have the create statement part (and everything except the body) use standard SQL mode and the body use CPerl mode or whatever mode some magic marker tells it to use. I've taken a bit of a look at mmm-mode, but haven't been able to get it to work, and don't have more time to spend on it. If someone has a good recipe for this please let me know.

Tuesday, August 19, 2014

New PostgreSQL buildfarm client release 4.14 - bug fix for MSVC

There is a new release - version 4.14 - of the buildfarm client, now available at

The only change of note is that a bug which only affects MSVC clients (such that the client will not complete a run) and is present in releases 4.12 and 4.13 is fixed. Clients on other platforms do not need to upgrade.

Monday, July 21, 2014

Code size

Someone was just talking about the size of some source files in PostgreSQL. The source code (.c, .h, .y and .l files) weighs in at a bit over 1 million lines of code. The documentation source has another roughly 300,000 lines. That's a large project, but by no means enormous by today's standards. The biggest source code file is pg_dump.c, at around 15,700 lines. The biggest documentation file is funcs.sgml, at around 17,600 lines. Both of these might well do with a bit of reorganization.

Wednesday, June 18, 2014

Buildfarm Client version 4.13 released

I have released version 4.13 of the PostgreSQL Buildfarm client.

This can be downloaded from

Changes in this release (from the git log):
  • fcc182b Don't run TestCollateLinuxUTF8 on unsupported branches.
  • 273af50 Don't run FileTextArrayFDW tests if not wanted.
  • 9944a4a Don't remove the ccache directory on failure, unless configured to.
  • 73e4187 Make ccache and vpath builds play nicely together.
  • 9ff8c22 Work around path idiocy in msysGit.
  • 0948ac7 revert naming change for log files
  • ca68525 Exclude ecpg/tests from find_typedefs code.

If you are using ccache, please note that there are adjustments to the recommended use pattern. The sample config file no longer suggests that the ccache directory have the branch name at the end. It is now recommended that you use a single cache for all branches for a particular member. To do this remove "/$branch" from the relevant line in your config file, if you have it, and remove those directories in the cache root. Your first run on each branch will rebuild some or all of the cache. My unifoed cache on crake is now at 615 Mb, rather than the multiples of Gb it had been previously.

It is recommended that this release be deployed by all users fairly quickly because of the fix in log file names that was discarding some that were quite important.

Sunday, June 15, 2014

Sunday, June 8, 2014

buildfarm vs vpath vs ccache

I think we've got more or less to the bottom of the ccache mystery I wrote about recently. It turns out that the problem of close to 100% of cache misses occurs only when the buildfarm is doing a vpath build, and then only because the buildfarm script sets up a build directory that is different each run ("pgsql.$$"). There is actually no need for this. The locking code makes sure that we can't collide with ourselves, so a hardcoded name would do just as well. This was simple an easy choice I made, I suspect without much thought, 10 years ago or so, before the buildfarm even supported vpath builds.

It also turns out there is no great point in keeping a separate cache per branch. That was a bit of a thinko on my part.

So, in my lab machine ("crake") I have made these changes: the build directory is hard coded with a ".build" suffix rather than using the PID. And it keeps a single cache, not one per branch. After making these changes, warming the new cache, and zeroing the stats, I did fresh builds on each branch. Here's what the stats looked like (cache compression is turned on):
cache directory                     ccache
cache hit (direct)                  5988
cache hit (preprocessed)             132
cache miss                             0
called for link                     1007
called for preprocessing             316
compile failed                       185
preprocessor error                    69
bad compiler arguments                 6
autoconf compile/link                737
no input file                         25
files in cache                     12201
cache size                         179.8 Mbytes
max cache size                       1.0 Gbytes

So I will probably limit this cache to, say, 300MB or so. That will be a whole lot better than the gigabytes I was using previously.

As for the benefits: on HEAD "make -j 4" now runs in 13 seconds on crake, as opposed to 90 seconds or more previously.

If we have a unified cache, it makes sense to disable the removal of the cache in failure cases, which is what started me looking at all this. We will just need to be a bit vigilant about failures, as many years ago there was at least some suspicion of persistent failures due to ccache problems.

All this should be coming to a buildfarm release soon, after I have let this test setup run for a week or so.