Episode: 2270
Title: HPR2270: Managing tags on HPR episodes - 3
Source: https://hub.hackerpublicradio.org/ccdn.php?filename=/eps/hpr2270/hpr2270.mp3
Transcribed: 2025-10-19 00:41:19

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This is an HBR episode 2, 270 entitled Managing Tag Mod HBR Episodes 3.
It is hosted by Dave Morris and is about 32 minutes long and can remain an explicit flag.
The summary is looking for the best way to store and manage tag in the HBR database part 3.
This episode of HBR is brought to you by An Honest Host.com.
Get 15% discount on all shared hosting with the offer code HBR15.
That's HBR15.
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Hello everybody. Welcome to Hacker Public Radio. My name is Dave Morris and today I'm
finishing a mini-series. I started a few weeks ago on the subject of Managing Tags on HBR
Episodes. This is the third episode of that mini-series. So you probably believe to know that it
is the last one. I don't know. It's haven't had much in the way of feedback. I've had a few comments
about help with database design and so forth, which is great. In the first show we looked at the
whole subject of tags and why we should need them. We need them with HBR shows and we looked at the
way that we're currently storing them and what's good and bad about that. Mostly bad. The major drawbacks
are with searching. It's the sort of thing that you might, the sort of design you might come up with
without really fully getting the idea of what databases are for and what they can do.
Hopefully this series will help to fill in some of those gaps as much as I can do that anyway,
not being a database expert. In the second show we looked at how we could make a simple tags table
and query it and thereby get a better overall effect. In particular we defined some of the things we
wanted to be able to do with tags, partly based around one of Drupes' comments back in an episode
he did about the way to improve HBR. We are going to in this last show look at a more, I've
written here, rigorous, efficient, normalized solution. So I think this is the way that somebody
trained in database design would do things and I've worked up to this over a couple of other
shows really just to air the whole subject of how one designs this type of thing for people
who are maybe not that experienced in this thing. I'm not that experienced but I do have come
across this sort of thing in the past and implemented it. Now one of the drawbacks with the method
that we looked at last time was that our tag table had multiple instances of the same tag
and it also doesn't conform to the accepted database design recommendations. So those two
things really, well you could get away with it, it's not really a good reason to do so as far as
I can see anyway. Although I did cite some instances of people who had implemented such things
in various services on the web, I don't think it's really the best way of doing things. In particular
the design in the last show doesn't really reflect the relationship between the HBR episodes
and the tags they're associated with and this relationship is what's referred to as many to many.
And what this means is that a given episode may have many tags, not very surprisingly,
and a given tag may be associated with many episodes. Now Mike Ray covered this subject very well
in episode 1569 called many to many data relationship how to. It covers the subject really,
really well, but I'm not sure that the audience was quite ready for to hear here such a thing.
I think we could definitely do with more database related shows for the sake of people who might
be wanting to get more into databases. Certainly I would recommend that you listen to Mike Ray's show
if you haven't done so already or if you've forgotten what he said. I've certainly listened and
read his wonderful notes since then because it does give a very good overview of how you would do
this type of thing. So in the many to many design, one copy of each tag would be held in a tags table
and there would be a second table which is linking or cross referencing the tags and episodes in
our particular case. I mean many to many is used in many contexts, but in the one that we're looking
at here we're talking about episodes and tags. So I drew a very simplistic diagram using open
office, Libre office drawer, which has its limitations for this sort of thing, but hopefully it gets
a message across. I've shown an example where we've got an episode's table, we're imagining that
there's a show 1, 2, 3, 4, which I've just shown in the little box, it says ID 1, 2, 3, 4 in it.
Then that is associated with the tag banana, obviously I show about bananas, and the way it's done
is that there's a joining table that contains a record that says episode, episode reference ID 1,
2, 3, 4 in the episodes table, and it's got a tag reference, so there's, imagine there's a tags
table where the tags have an index number and we have that number in the joining table. Then it shows
picture of the tags table with tag ID 456. I wasn't very imaginative with these numbers,
and it's associated with the tag banana. So if you if you like looking at pictures of things
like this, you might find that useful. So what I did in order to demonstrate this, and just to prove
to myself that this was a viable thing to do and that I fully understood it, and this was some time
ago I wrote this, I used the comma separated list that we already have in the episodes table,
which it's called EPS, for some reason, save typing presumably, and I used the contents to
populate new tables that I created. I did the population with a purl script, and I've included
the purl script in with this show just really for reference for completeness. I will look at it
in in brief a bit later on, but as part of this this particular episode I've also included the
SQL or SQL definition of the table, and it's a file that you can download if you're interested,
I call it normalized tags 2. I've also listed it in the notes in the long notes, and it just in
brief it it contains a new table of tags, which are called tags 2, that's because I already had a
table called tags for the the other method you would call it something else if you were doing this
for real. Remember this is experimentation, it contains single instances of tags, I did make it
hold the mix case and lower case versions of the tag, but since I did that I think in my SQL
and MariaDB I discovered that it's easier just to store one because it doesn't, you have to go
to some length to make it check the case of words and stuff, that wouldn't be the case with other
database systems, but it is with this. There's a joining table here which are called
EPS underscore tags 2 underscore X ref, the convention is, this is something that Mike Ray mentioned as
well, the fact that it's joining two tables, it's good to give it a name that references the two
tables and then follow it with X ref meaning that it's a cross referencing table, so it's easy when
you come to look at a database to work out what the thing is from its name. This table contains
just two columns, one is called EPS ID and the other one is called tags2ID, so EPS ID is the key
of one of the rows in the EPS table, so in other words it's an episode number because that's the key
to this table. Tag2ID is the equivalent of a reference to a row in the tags2 table and one of the
key things that you need to do when creating such a cross reference or joining table is that you
need to give it a unique index which is a structure which stores pointers to the rows in the table
effectively, and in this particular case it combines the two columns to make the key and it's
defined as a unique index, that means that you cannot have a case where the same episode and the
same tag is repeated. It doesn't make any sense to do that but since databases can control these
things then it's a good idea to make that the case, it's in to enforce it this way, so you can
imagine in this table there will be multiple instances of the episode number because a given
episode is entirely likely to have multiple tags and for each instance of that episode number
there will be a different tag number referencing into the tags2 table. I also created an index, a
unique index on the tags2 table which just ensures that it's impossible to add the same tag twice
into that table because otherwise the database would let you. Doing this means that you can't.
Then there's a further index I've created which is probably not necessary which I called all tags
and it indexes the tags2ID column of the cross referencing table. That's because when managing
the tags, if a tag gets deleted for whatever reason maybe it was misspelled and you want to change it
for some reason and effectively have to delete the old and replace it with the new, then deletion
is done if it's done external to the database then the index helps to speed things up. Well I'll
come on to that in a little bit more detail later on. Now one of the things that Mike mentioned in
his show was the use of so-called foreign keys. Now MariaDB or MySQL and all the various other
databases are so-called relational databases which means that the relationship between tables
or entities if you want to call them that can be defined by various components of the definition.
This one's lots of lots of further tutorial episodes to fully fully grasp but bear with me.
So the thing so-called referential integrity is managed through foreign keys but by default
MySQL before and MariaDB now don't support foreign keys so if you create a table you don't get the
ability to create foreign keys on it. I think that's true and at one point MySQL, the predecessor
MariaDB, couldn't actually do foreign key relationship at all. That's the reason I never used it
in my work because the time I wanted to do that I wanted to be able to use foreign keys.
There are different types of table you can create and I've noted down here that by default you
get one which doesn't support these features. You have to ask for it explicitly. At the moment we
don't have any of these types of table that can do this stuff in the HBR database so I've not
implemented this in my example though it's something we should be doing. So a foreign key then
is a way of showing relationships between database table or the data within them, making it
one table dependent on another effective. So the field EPS ID in the cross reference table is an
episode ID number in the EPS table and it should only contain episode ID numbers which match
episode numbers in the EPS table. You can't just add 999 in there because it's saying I am referencing
an existing entity in the an existing row in the EPS table. If you define it as a foreign key
then the database itself will say no you can't do this because this doesn't exist in the other
table. So the tags to ID field in the same table would also be a foreign key pointing into the
tags to table and again the database would constrain what can be placed there. One of the other things
that foreign keys can do is that it can ensure that if you delete something like you delete a tag
you delete the final reference to a tag then you can get the database to manage all of the
deletion. So the sort of scenario would be if you had a tag banana referred to by an episode
then if you deleted that tag in the sense that you said this was a mistake it's no longer to be
associated. You want to delete the tag from the tag table you also want to delete the cross
reference. So the maintenance of integrity is a feature called cascading deletion which means
that you can't delete a cross reference entry without the tag also being deleted. You don't end up
with tags sitting in the tag table which don't belong anywhere. Orphaned I think is the term certainly
the term I am inclined to use and Mike similarly I noticed. So I don't sure I explained that very
well but Mike did a much better job of it and so I can refer you back to episode 1569 if you
want to understand this more. So I've added in here note about the pulse script that I wrote which
I called refresh underscore tags underscore two. It's quite a complicated script so I'm not I'm not
going to go into details about it. It's not really a hugely relevant here but I thought I would
put it make it available in case anybody wanted to read it and understand it. In just to explain
it in three quick paragraphs it scans the eps table in the database collecting all of the tags stored
in CSV form and it's it stores them away with the episode number they belong to. It also collects
the tags stored in the tags two table if there are any and stores them again associated with an
episode number so it's made two two tables of information episode number and the tags that
it that are associated with it in the two tables remembering that this depends on the CSV list being
available. They can then compare the two sets of tags and look for differences so if a new tag is
appeared in the CSV list it can add it to the tags two table and if for some reason it's no longer
there then it can delete it and it manages the joining table along with the tags two table to
achieve this. I've noted that the script performs actions that the database itself would carry out
we used foreign keys and so forth and so the deletion in particular and deletion of stuff and
again again in my notes made a reference to the fact that we really need to implement the full
database capabilities in order to get this stuff. So moving on to the advantages and disadvantages
of this method well first of all this is the most efficient way of storing the tags we only
store one instance of everything it's obviously vastly preferable to the common separated
variable method which looked at in episode one and it's also preferable to the method in the last
episode because the same tags stored only once so if you want to make a spelling correction to a tag
you don't have to go and make it several times for example and if we have the full relational database
capabilities foreign keys caster cading deletion and so forth we can use the database capabilities
to help manage this type of structure it's what databases are designed to do the disadvantage and
I've only listed one really this is the best in in terms of database design but the concept of how
it works and the sort of way in which you manage it have become more complicated as a as a
consequence but I don't believe that that's really an issue especially since you can write scripts
or similar types that you can even write so called stored procedures in the database to help you
manage this sort of stuff so I don't think that should be a criterion for rejecting it so as in
the previous episodes let's look at the ways in which this method could be used for searching now
I've put quite a lot of detail in the notes here but I won't talk about them in in great detail
I'll leave them for you to examine if if you're interested the first one is how would you find
all the shows that have a given tag and I'm using the example we used originally which was look
for shows with the tag community the one note I've made here is that since I created the notes
the last show I discovered that the method I used to generate show notes which is a templating
system has the capability of making database queries within it so I've actually done that within
my notes and my notes themselves actually querying the my copy of the HPR database and because I can
do that I can also generate HTML tables to show the results so I've done that and hopefully it's a
bit clearer to to read I think it is anyway previously I was listing things which were too wide
for the for the page so you had to scroll sideways to see them HTML tables wrap in sensible ways
so I think it is preferable and also color things and that sort of stuff so the query that is
an example of how you would do this particular type of query to get the shows of the tags with
the tag community you have to examine the apps table and the cross reference table and the tags
to table in order to do this and you need to make sure that for every row you get out of these
various tables you are making comparisons and to say that you want rows where the episode id number
matches the episode id number in the cross reference table and similarly the tags id number in
the cross reference table matches the tag id number in the tags table so you're doing a sort of
um a set operation where the sets are overlapping between these three tables and then when you've
done that you then say I want only the rows from this combination which have a tag of community
and you get back a list which is the say which is actually not the same as last time because since then
the worlds moved on and we've got more got more shows in the database and one of them I think it
is has got community as a tag it's mine actually but the time of recording this hasn't come to the
top of the queue but whatever by the time you hear this it probably will have so if you want to find
shows with a combination of tags again it's the same same example as before we want to find shows
which contain the tag community or the tag hpr and there's an example query of how you would do
this and the result as a as an html table again we get more back because other shows have come into the
the database the shows the other previous two shows in this mini series appear and that's why
because they both contain hpr as a tag if we want to find shows which have community
and hpr as tags then there's a difference the way the the query is done which which I have shown
without a huge lot of explanation but you can see the result comes out of it I don't think it's
appropriate to drill down too deeply into this one now in the last episode I did a thing where I
followed up troops's suggestion which was that if we select a show
he was imagining that if if we're looking at a particular show listening to a particular show
it would be good to know which other shows share the same tag tags I should say and I wrote a little bit
of sequel to do this which I stored in a file and I shared the file with you this time I haven't
done the same thing I've done the same query the equivalent query but I haven't made it into a
SQL script there are two queries one is simply to get back the tags of the related to a given show
I'm using show 2071 as the target so we're assuming we're listening to show 2071 and that was Mr
X's show I didn't actually know what it was in this one because I did in the last episode but
I don't know what it was actually I think oh it was about his portable amateur radio device
anyway the tags are amateur radio electronics and open source and then the second query is
one which scans the database for all shows which have any of those tags so and then it's actually
listed them with the tag that it found so there's a batch of amateur radio or a batch of electronics
and a batch of open source shows that came back from the query and again it's similar to what was
done last time just different queries basically maybe more shows came back I didn't actually make a
note how many we got back I don't think it's all that important now in the last episode we
looked at using regular expressions because there is that capability within MariaDB to find
partial tags because all we've been doing so far is looking at whole tags but if we want to look
at a partial tag then regular expressions what we need to to use and I've got an example query
which is using the regular expression capability and it's using word boundary expression which I
mentioned in the last episode so I won't go into detail I've gone into a tiny bit more in detail
how this query works it's scanning four tables scanning the EPS table it's scanning the host table
because I thought it would be useful to get back the name of the author of the show it's scanning
the joining table and the tags table tags two and the joining is done to make subsets of the tables
and the way I mentioned earlier on then the regular expression part looks for the word ham
so it's got word boundary before and after it so there's only the word ham as a distinct word
but it's and looking for it as a component of a tag or indeed the whole tag if needs if there is one
but not as part of a word so a Birmingham would not come back from this query it uses a group by
which makes sure that you get only one answer if the query matches the same episode twice or more
so we get back a list of shows and their dates and the titles and the host and then the tags that are
associated with them and they all contain the word ham so it thinks like ham radio ham as a tag
actually in one case ham radio seems to be the most common one though ham radio without a space
is not one of the matches looking through yeah amateur radio ham ham space radio is the
the commonest one but ham just as a tag is also coming back so there's some very
degree of sophistication that can be achieved by using this technique now I thought it would be
useful just to finish off with a technique that's available within the database most databases offer
this this is a thing called a view can use it to hide away the complexity of some of the queries
and there's certainly the case that the queries we're using this time round are more complex than
the ones we used in the last episode so I've created a view and I've called a view I should say is
a piece of SQL SQL which is a means of storing away a select query one of those ones where you
you're asking for particular rows to be returned out of the out of the tables so it's a way of
storing away such a select query and then you can use the the name of that query to query again
as if it's a table all of its own but behind the scenes the the view query is being issued
is being executed and the results of that are then being returned or subset of those results
being returned it's a sort of nested query type of thing I've included the query that I came
up with as a file if you want to look at it and it's also listed in the notes I created a view
called EHTVU which is just a way of signifying that it relates to the EPS table the host table
and the tags table tags two tables I should say it queries these in a similar way to the the way
we've we've done in previous queries and once it's there and stored away it can then be executed
I maybe explain a teeny bit more about it in a moment yeah this isn't really intended to be a
database tutorial as such more a discussion of methodologies so I'm using a create a query
which is just listed in the notes here which uses the view so it's doing a select from EHT
underscore view and then it's saying where tag regular expression reggex and then it's looking
for a the word solder SLDR with word boundaries before and after it and then grouping the result
by the ID number that comes back it gets back three shows which contain the tag a tag which is
either solder or contains solder in the tag so the first one is show 941 which has got the tag
second one is 103 seven mr x where he was he was giving a tutorial on soldering and it contains
the tags solder and the third one he didn't use the tags solder and we've ever added these tags
actually can't remember who created them doesn't contain that tag but it contains multicore solder
as a tag so this thing fished the word solder at a multicore solder because it's a separate word
and returned it which I think is the way you'd want it to do now the view contains it is a select
which will do a query it gets back all of all of the instances of episodes and hosts and tags
you then have to sort of subset that when you call it which is what the example shows but within
the view there is what's called a sub select so I think I did this I think I did an equivalent
in the last episode and the sub select is using a function in my SQL called group concat
which looks for all instances in a table and concatenates them together with a comma so the result
the tag list that you see in the in the result is concatenated from the tags table all of the tags
which relate to that particular show again it's it's it's probably not a thing you would do for real
but it was a demonstration more than anything else okay so we're now at the conclusion and my
conclusion is that the hpr database needs a tag mechanism very much and we've looked at the
present tag storage system in this miniseries so it's not a good way to do things we've looked at
a somewhat better way of doing it but I've concluded that it has some drawbacks this third example
this third episode shows a better way of doing doing things in a in a relational database in a way
that we represent the true relationship between the episodes and tags and that relationship is
a many to many relationship so you could say it's taking me three shows to get to a conclusion
that Mike Bray drew in in one but I felt it was worth working through this in order to explain why
and why not some why not use some of the other solutions so although it's going to require some
work it's strongly recommended that we implement a tag scheme in the hpr database in the way that
it's been discussed in this show and we also enable the foreign key capabilities of MariaDB
so that for the reasons I've mentioned along the way today and at the same time we look at doing
similar upgrades to enable many to many relationships of hosts and episodes we have we don't have
that when it comes to hosts I think that is as important if not more important than the tags thing
there's another one which is that there's a many many relationships between episodes and series
thinking episode will be could be a member of more than one series I don't think it's as critical
as the other ones mind you and I'm prepared to be disagreed with on that one but it's definitely
something you should look at if nothing else okay so as before I've got a little
key at the end saying please include tags in your shows and if you if you have a moment to add
more tags to the missing shows the ones missing tag let's say then be very very much appreciated
but other than that I finished breathe cyber relief okay thanks everybody bye
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