Articles from Release

  • DaCHS 2.5: Check your UCDs

    DaCHS logo on top of a map of UCDs

    In the background of the DaCHS 2.5 release picture: UCDs grabbed from the Registry. The factual background: DaCHS 2.5 will now moan at you when you invent or mistype UCDs

    This afternoon, I have released DaCHS 2.5. As usual, I will discuss the more important changes in a blog post – this one.

    A change many of you will not like too much is that DaCHS now validates UCDs you give it, and it will warn you when you do not follow the UCD rules. This may seem like nit-picking, but as blind discovery is on the verge of becoming usable in the VO, making sure these strings actually are what they should be is becoming operationally important: If I want to find resources that give errors for their photometry, I have to know whether it's stat.error;phot.mag.b or phot.mag.b;stat.error, or else I will miss half the resources out there.

    So, I'm sorry if DaCHS starts complaining about half of your RDs after you update, but it's for a good cause. And don't feel bad about the complaints: DaCHS complained about close to half of my RDs after I had put in that feature.

    By the way, this comes as part of a larger effort on the side of the Operations IG to improve the validity of UCDs and units in the VO, an effort that has unearthed bugs in the SSAP and SLAP specifications in that they require UCDs forbidden by the UCD standard. DaCHS 2.5 still follows SSAP and SLAP, and hence external tools like stilts will protest because of bad UCDs even if DaCHS is happy. Errata for the specifications are being worked on, and once they are accepted, DaCHS and stilts will finally agree on UCD validity, or so I hope.

    Code-wise, a much more intrusive change was that asynchronous services (in particular, async TAP) now use the same formalism for parsing parameters as their synchronous counterparts. It may seem odd that that hasn't been the case up to now, but there were good reasons for that; for instance, with async, people can post incomplete parameter sets that would be rejected by normal sync processing.

    Unless you are running User UWS services, you should not notice anything. If you do run User UWS services, please contact me before upgrading. I would like to work with you on how these should look like in the future.

    Another change that might break your services is that DaCHS now actually complies to VOUnits, which has always forbidden whitespace of all kinds in unit strings. DaCHS, on the other hand, has foolishly encouraged putting whitespace between scale factors and pure units, as in 1e-10 m. That's not interoperable, and hence DaCHS now rejects such units. This may lead to hidden failures when dachs val doesn't notice something is a unit, and things only break during execution. I'm aware of one place where that's relevant: spectral cutout services that need to know the spectral unit If you're running those, make double sure that the spectralUnit in the SSAP mixin does not contain any whitespace. It's 0.1nm according to VOUnits, not 0.1 nm.

    An update that should silently make your services more compliant is that DaCHS' representation of EPN-TAP is updated to what is currently under IVOA review. After you upgrade, DaCHS will try to update your EPN tables' metadata, which in turn should make stilts taplint a lot happier. It will also make DaCHS pass on the new, IVOA table utype to the Registry, which is how people should in the future find EPN-TAP data.

    DaCHS now also contains some code that may help you import data from HDF5 files. For one, there is the HDF5 grammar, which rather directly pulls data from HDF5s written by astropy or vaex. But, really: HDF5 is a rather low-level format not particularly well suited for relational data, and it is virtually impossible to write generic code for doing something sensible with it. The two flavours DaCHS supports have very little in common, and it is therefore almost certain that if you have HDF5s coming from somewhere else, hdf5Grammar will not understand them. Still, let us know what you've got, we may be able to put support for it in.

    Hdf5grammar is written in Python, and thus imports perhaps a few thousand rows per second. For Gigarow-sized data collections, that's nowhere near fast enough, and hence for vaex-written HDF5s, there is booster support. As before, if you have bulk data in HDF5 that you want to put into a database and that was not written by vaex, let us know and we'll see what we can do.

    A surprisingly minor change enabled DaCHS to deal with materialised views, database views that are turned into actual tables by postgres. See the corresponding section in the tutorial for how you can use them. We do not have any materialised views in our Heidelberg data center yet. So, if you use them and notice something is clunky, your feedback is particularly appreciated.

    There are many smaller changes and improvements; let me mention what the changelog euphemistically calls ”better systemd integration”, which really means that so far systemctl restart dachs simply didn't do anything at all. Apologies. And shame on everyone who was bewildered but failed to report this to dachs-support.

    Also, you can use float arrays in boosters now, and DaCHS' ADQL has just leared about COALESCE. That's a SQL feature that lets you deal sensibly with NULLs in some cases: COALESCE(arg1, arg2, ...) will return the first non-NULL argument it encounters. That may sound like a slightly exotic function. Until you need it, at which point you wonder how ADQL could reach its ripe age without COALESCE.

    Finally, let me mention something that is not part of the release, though it is DaCHS-related and is new since the last release: I have cleaned up the access log processing machinery we have used in Heidelberg in the past 15 years or so, and I have packaged it up for general consumption. It is, of course, a DaCHS RD that you can just check out and use in your own DaCHS installation if you have to keep access logs and want to do that with at least some basic respect for your user's rights. See http://docs.g-vo.org/DaCHS/tutorial.html#access-logs for details.

  • DaCHS 2.4 is out: Blind discovery, pretty datalink, and more

    DaCHS screenshots and logo

    DaCHS 2.4: automatic ranges (with registry support!), pretty datalink (with vocabulary support!). And then the usual bunch of improvements (hopefully!).

    I have released DaCHS 2.4 today, and as usual for stable releases, I would like to have something like a commented changelog here so DaCHS deployers perhaps look forward to upgrading – which would be good, because there are far too many outdated DaCHSes out there.

    Among the more notable changes in version 2.4 are:

    Blind discovery overhaul. If you've been following my requests to include coverage metadata three years ago, you have probably felt that the way DaCHS started to hack your RDs to include the metadata it had obtained from the data was a bit odd. Well, it was. DaCHS no longer does that when running dachs limits. While you can still do manual overrides, all the statistics gathered by DaCHS is now kept in the database and injected into the DaCHS' internal idea of your RDs at loading time.

    I have not only changed this because the old way really sucked; it was also necessary because I wanted to have per-column metadata routinely, and since in advanced DaCHS there often are no XML literals for columns (because of active tags), there wouldn't be a place to keep information like what a column is minimally, maximally, in median, or as a “2σ range“ within the RD itself. A longer treatment of where this is going is given in the IVOA note Blind Discovery 2: Advanced Column Statistics that Grégory and I have recently uploaded.

    For you, it's easy: Just run dachs limits q once you're happy with your data, or perhaps once a month for living data, and leave the rest to DaCHS. A fringe benefit: in browser froms, there are now value ranges of the various numeric constraints as placeholders (that's the screenshot on the left in the title picture).

    There is a slight downside: As part of this overhaul, DaCHS is now computing the coverage of SIAP and SSAP services based on the footprints of the products as MOCs. While that gives much more precise service footprints, it only works with bleeding-edge pgsphere as delivered in Debian bullseye – or from our Debian repository. If you want to build this from source, you need to get credativ's pgsphere fork for now.

    Generate column elements: If you have tables with many columns, even just lexically entering the <column> elements becomes straining. That is particularly annoying if there already is a halfway machine-readable representation of that data.

    To alleviate that, very early in the development of DaCHS, I had the gavo mkrd subcommand that you could feed FITS images or VOTables to get template RDs. For a number of reasons, that never worked well enough to make me like or advertise it, and I eventually ended up writing dachs start instead, which is something I like and advertise for general usage.

    However, what that doesn't do is come up with the column declarations. To make good on this, there is now a dachs gencol command that will, from a FITS binary table, a VOTable, or a VizieR-style byte-by-byte description, generate columns with as much metadata as it can fathom. Paste that into the output of dachs start, and, depending on your input format, you should have a quick start on a fairly full-featured data collection (also note there's dachs adm suggestucds for another command that may help quickly generate rich metadata).

    This currently doesn't work for products (i.e., tables of spectra, images, and the like); at least for FITS arrays, I suppose turning their non-obvious header cards into columns might save some work. Let's see: your feedback is welcome.

    Refurbished Datalink XSLT: Since the dawn of datalink, DaCHS has delivered Datalink documents with XSLT stylesheets in order to have nicely formatted pages rather than wild XML when web browsers chance on datalink documents. I have overhauled the Javascript part of this (which, I have to admit, is what makes it pretty). For one, the spatial cutout now works again, and it's modeless (no clicking “edit“ any more before you can drag cutout vertices). I'm also using the datalink/core vocabulary to furnish link groups with proper titles and descriptions, and to have them sorted in in a proper result tree. I've talked about it at the interop, and I've prepared a showcase of various datalink documents in the Heidelberg data centre.

    Update to DaCHS 2.4 and you'll get the same thing for your datalinks.

    Non-product datalinks: When writing a datalink service, you have to first come up with a descriptor generator. DaCHS will provide a simple one for you (or perhaps a bit more complex ones for FITS images or spectra) – but all of these assume that whatever the datalink ID parameter references is in DaCHS' product table. It turned out that in many interesting cases – for instance, attaching time series to object catalogues – that is not the case, and then you had to write rather obscure code to keep DaCHS from poking around in the product table.

    No longer: There is now the //datalink#fromtable descriptor generator. Just fill in which column contains the identifier and the name of the table containing that column and you're (basically) done. Your descriptor will then have a metadata attribute containing the relevant row – along with everything else DaCHS expects from a datalink descriptor.

    gavo_specconv: That's a longer story covered previously on this blog.

    Index declaration in views: Saying on which columns a database index exists allows users to write smart queries, and DaCHS uses such information internally when rewriting geometrical expressions from ADQL to whatever is in use in the actual database. Hence, making sure these indexes are properly declared is important. But at the same time it's difficult for views, because postgres doesn't let you have indexes on views (for good reasons). Still, queries against views will (usually) use indexes of their underlying tables, and hence those should be declared in the corresponding metadata.

    This is tedious in general. DaCHS now helps you with the //procs#declare-indexes-from stream. Essentially, it will compare the columns in the view with the ones from the source tables and then guess which view columns correspond to indexed columns from the source tables; using that, it adds indexed flags to some view columns.

    If all this is too weird for you: Thanks to declare-indexes-from, the index declaration now automatically happens in the modern way to build SSAP services, the //ssap#view mixin. Hence, chances are you won't even see this particular STREAM but just notice its beneficial consequences.

    Sunsetting resources: I've been fiddling off and on with a smart way to pull resources I no longer want to maintain while still leaving a tombstone. I had to re-visit this problem recently because I dropped the Gaia DR1 table from my Heidelberg data centre. So, how do I explain to people why the thing that's been there no longer is?

    In general, this is a rather untractable problem; for instance, it's very hard to do something sensible with the TAP_SCHEMA entries or the VOSI tables endpoints for the tables that went away. Pure web pages, on the other hand, can be adorned with helpful info. To enable that, there is now the superseded meta item, which you define in the RD that once held the resources. For Gaia DR1, here's what I used:

    <meta name="superseded" format="rst">
      We do not publish Gaia DR1 data here any more.
      If you actually need DR1 data, refer to the
      full Gaia mirrors, for instance `the one at
      ARI`_.  Otherwise, please use more recent data
      releases, for instance `eDR3`_.
    
      .. _the one at ARI: http://gaia.ari.uni-heidelberg.de
      .. _eDR3: /browse/gaia/q3
    </meta>
    

    Root page template: I slightly streamlined the default root page template, in particular dropping the "i" and "Q" icons for going to the metadata and querying the service. If you have overridden the root template, you may want to see if you want to merge the changes.

    As usual, there are many more small repairs and additions, but most of these are either very minor or rather technical. One last thing, though: DaCHS now works with Python 3.8 (3.7 will continue to be supported for a few years at least, earlier 3.x never was), which is going to be the python3 in Debian bullseye. Bullseye itself will only have DaCHS 2.3 (with the Python 3.8 fixes backported), though. Once bullseye has become stable, we will look into putting DaCHS 2.4 into the backports.

  • DaCHS 2.3 on the way to Debian main

    DaCHS, Debian, and 2.3

    DaCHS 2.3 will be the first DaCHS officially in Debian.

    DaCHS releases usually come around the Interops in (roughly) May and November. Not this one, though, for one pleasant, one unpleasant, and several other reasons.

    The unpleasant reason first: The 2.2 release has a fairly severe memory leak in it (resulting, in roundabout ways, from python 3 preserving tracebacks of nested exceptions), which of course really became virulent on my server right over the holidays. If you run a site with just a few gigs of RAM that might be hit by second-rate async clients, this will bite you and you ought to upgrade now (well, you ought to upgrade anyway).

    The pleasant reason is that DaCHS has made it into Debian main and thus, unless something disastrous happens, it will be part of the Debian version 11 (“bullseye”). This means that people who do not need to be on the bleeding edge, will not need to monkey around with our repository (and its signing key) any more starting some time in 2021 (or just about now, if they're running testing). I can't tell you how gratifying that feels to me. And well, I wanted relatively recent code corresponding to a something on our release branch in bullseye.

    One of the other reasons is that stilts' author Mark Taylor is trying to stomp out TAP services failing his taplint's validation, and many DaCHS 2.2 services (those that don't define TAP examples, which of course is a shame anyway) fail with only the (really minor) error E-EXDH-1 (see below).

    DaCHS 2.3 has some other noteworthy changes; as usual in minor version steps, my expectation is that none of this will break existing services. Still, you may want to glance over the following list, as there are some behavioural changes nevertheless. In approximate order of the wizardry involved:

    • I've long had a bad consciousness because DaCHS has stored cleartext passwords so far. That's probably not a problem for DaCHS itself (as it does not protect great riches), but people tend to re-use passwords, and I'd have hated to leak passwords that might work elsewhere. Well, no longer: the dc.users table now contains hashed passwords, and the upgrade will hash them. This, in particular, means that you cannot recover them once you have updated (which, of course, is as it should be).

    • The javascript delivered with DaCHS was no longer quite up to date with Debian's jquery. I have updated it in several ways, and I have restored the functionality of the WebSAMP button in the default response. If you have custom HTML templates containing javascript, you may need to update them to newer jquery, too, specifically,

      • change .unload( to .on("unload", (this happens in the SAMP code in defaultresponse.html, for instance).
      • also in the SAMP code in overridden defaultresponses, change the icon URL to completeURL("/logo_tiny.png") (or whatever) to avoid trouble with https installations.
      • if you compare jquery element names: these are now returned in lower case.

      And yes, WebSAMP now mostly works with HTTPS (which is unrelated to this update, except that DaCHS until 2.2 suppresses the WebSAMP button when it thinks it is delivering through HTTPS).

    • DaCHS now honours upgrade-insecure-requests headers that common web browsers issue and will then redirect them to https when appropriate. So, please don't forcibly do these redirects any more from reverse proxies – they break, among other things, TAP, and they're generally just a bad idea.

    • DaCHS now instructs the database to return all bits of floating point numbers. This may break your regression tests, but it's the right thing to do (blog post on this).

    • Another thing that may break regression tests: TAP results now have column names in the case given in the RD (where previously they were lowercased unless quoted). Let me cite rule 1 of SQL table design: Don't use mixed-case column names.

    • Wildcards in the directory parts of sources patterns are now expanded, which means that you can write things like <sources pattern="data/202?/*.fits"/>, which previously wouldn't have done what you might reasonably expect; however, this might in rare cases match additional sources when you re-import data.

    • The examples endpoint now returns a 404 if no examples are defined on a service; this fixes the stilts taplint E-EXA-EXDH-1 error I mentioned above.

    • DaCHS will now refuse to use x-unregistred as an authority when publishing resources or creating publisher DIDs. This is to protect to people who do a lot of imports before settling on their authority; sometimes DaCHS' fallback null authority got into their databases, which then caused quite a bit of cleanup effort.

    • Because of licensing problems, the Debian package no longer contains the CC logos for the time being. If you want them back, drop appropriate files cc0.png, ccby.png, and ccybysa.png into /var/gavo/web/nv_static/img

    • You can now list modules you want in a procedure application in its setup/@imports attribute. I've done this after I had to add code to a proc's setup just to run an import once too often.

    • simbadinterface's Sesame now uses the dc.metastore table to cache results rather than files as before. Previous saveNew, id, and debug parameters are no longer supported (the base.caches.getSesame interface is unchanged, so it's unlikely you'd notice this).

    • table.query() or querier.query() are now seriously deprecated (you may have used them in code embedded in RDs). See Database Queries in the reference documentation for what the recommended query patterns are (and have been for a while). Just one word of warning: table.query would macro-expand its argument, which the connection method obviously cannot. If you depend on that, call table.expand(query) manually first.

    With this: Merry upgrading and a happy new year!

  • DaCHS 2.2 is out

    Image: DaCHS "entails" 2.2

    DaCHS 2.2 adds support for what simple semantics we currently do in the VO. Which is a welcome excuse to abuse one of the funny symbols semanticians love so much.

    Today, I've released DaCHS 2.2, the second stable version of DaCHS running on Python 3. Indeed, we have ironed out a few sore spots that have put that “stable” into question, especially if you didn't run things on Debian Buster. Mind you, playing it safe and just going for Debian is still recommended: Compared to the Python 2 world, where things largely didn't break for a decade, the Python 3 universe is still shaking out, and so the versions of dependencies do matter. It's actually fairly gruesome how badly pyparsing 2.4 will break DaCHS. But that's for another day.

    Despite this piece of fearmongering, it'd be great if you could upgrade your installations if you are running DaCHS, and it's pretty safe if you're on Debian buster anyway (and if you're running Debian in the first place, you should be running buster by now).

    Here are the more notable changes in this release:

    • DaCHS can now (relatively easily) write time series in the form of what Ada Nebot's Time Series Annotation note proposes. See the tutorial chapter on building time series for how to do that in practice. Seriously: If you have time series to publish, by all means try this out. The specification can still be fixed, and so this is the perfect time to find problems with the plan.
    • The 2.2 release contains support for the MOC ADQL functions mentioned in the last post on this blog. Of course, to make them work, you will still have to acquaint your database with the new functionality.
    • DaCHS has learned to use IVOA vocabularies as per the current draft for Vocabularies in the VO 2. The most visible effect for you probably is that DaCHS now warns if your subject keywords are not taken from the Unified Astronomy Thesaurus (UAT) – which they almost certainly are not, because the actual format of these keywords is a bit funky. On the other hand, if you employ the “plain” root page template (see the root template in our templating guide if you are not sure what I am talking about here), you will get nice, human-friendly labels for the computer-friendly terms you ought to put into subjects. In case you don't bother: Given I'm currently serving as chair of the semantics working group of the IVOA, the whole topic will certainly come up again soon, and at that point I will probably also talk about another semantics-related newcomer to DaCHS, the gavo_vocmatch ADQL UDF.
    • There is a new command dachs datapack for interacting with frictionless data packages. The idea is that you can say dachs datapack create myres/q myres.pack and obtain an archive of all that is necessary to re-create myres on another DaCHS installation, where you would say dachs datapack load myres.pack. Frankly, this isn't much different from just tarring up the resource directory at this point, except that any cruft that may have accumulated in the directory is skipped and there is a bit of structured metadata. But then interoperability always starts slowly. Note, by the way, that this certainly does not teach DaCHS to do anything sensible with third-party data packages; while I've not thought hard about this, as it seems a remote use case, I am pretty sure that even the “tabular data packages” that refine the rough general metadata quite a bit simply have nowhere near enough metadata to create a useful VO resource or TAP table.
    • As part of my never-ending struggle against bitrot (in case you've always wondered what “curation” means: that, essentially), I'm running dachs val -vc ALL in my own data center once every month. This used to traverse the file system to locate all RDs defined on a box and then make sure they are still ok and their definitions match the database schema. That behaviour has now changed a bit: It will only check published RDs now. I cannot lie: the main reason for the change is because on my production machine the file system traversal has taken longer and longer as data accumulated. But then beyond that there is much less to worry when unpublished gets a little bit mouldy. To get back the old behaviour of validating all RDs that are reachable by the server, use ALL_RECURSE instead of ALL.
    • DaCHS has traditionally assumed that you are running multiple services on one site, which is why its root page is rendered over a service that exposes metadata on local resources. If that doesn't quite work for how you use DaCHS – perhaps because you want to have your own custom renderers and data functions on your root page, perhaps because you only have one browser-based service and that should be the root page right away –, you can now override what is shown when people access the root URI of your DaCHS installation by setting the [web]root config item to the path of the resource you want as root (e.g., myres/q/s/fixed when the root page should be made by the fixed renderer on the service s within the RD myres/q).
    • Scripting in DaCHS is a powerful way to execute python or SQL code when certain things happen. That seems an odd thing to want until you need it; then you need it badly. Since DaCHS 2.2, scripts executed before or after the creation of a table, before its deletion, or after its meta data has been updated, can sit on tables (where they have always belonged). Before, they could only be on makes (where they can still sit, but of course they are then only executed if the table is operated through that particular make) and RDs (from where they could be copied). That latter location is now forbidden in order to free up RD scripts for later sanitation. Use STREAM and FEED instead if you really used something like that (and I'd bet you don't).
    • Minor behavioural changes:
      1. Due to a bug, you could write things like <schema foo="bar">my_schema<schema>, i.e., have attributes on attributes written in element form. That is now flagged as an error. Since that attribute was fed to the embedding element, you might need to add it there.
      2. If you have custom flot plots in one of your templates (and you don't if you don't know what I'm talking about), you now have to set style to Points or Lines where you had usingIndex 0 or 1 before.
      3. The sidebar template no longer has links to a privacy policy (that few bothered to fill out). See extra sidebar items in the tutorial on how to get them back or add something else.

    The most important change comes last: The default logo DaCHS shows unless you override it is no longer the GAVO logo. That's, really, been inappropriate from the start. It's now the DaCHS logo, the thing that's in this posts's article image. Which isn't quite as tasteful as the GAVO one, true. But I trust we'll all get used to it.

  • Tutorial Renewal

    The DaCHS Tutorial among other seminal works

    DaCHS' documentation (readthedocs mirror) has two fat pieces and a lot of smaller read-as-you-go pieces. One of the behmoths, the reference documentation, at roughly 350 PDF pages, has large parts generated from source code, and there is no expectation that anyone would ever read it linearly. Hence, I wasn't terribly worried about unreadable^Wpassages of questionable entertainment value in there.

    That's a bit different with the tutorial (also available as 150 page PDF; epub on request): I think serious DaCHS deployers ought to read the DaCHS Basics and the chapters on configuring DaCHS and the interaction with the VO Registry, and they should skim the remaining material so they are at least aware of what's there.

    Ok. I give you that is a bit utopian. But given that pious wish I felt rather bad that the tutorial has become somewhat incoherent in the years since I had started the piece in April 2009 (perhaps graciously, the early history is not visible at the documentation's current github home). Hence, when applying for funds under our current e-inf-astro project, I had promised to give the tutorial a solid makeover as, hold your breath, Milestone B1-5, due in the 10th quarter. In human terms: last December.

    When it turned out the Python 3 migration was every bit as bad as I had feared, it became clear that other matters had to take priority and that we might miss this part of that “milestone” (sorry, I can't resist these quotes). And given e-inf-astro only had two quarters to go after that, I prepared for having to confess I couldn't make good on my promise of fixing the tutorial.

    But then along came Corona, and reworking prose seemed the ideal pastime for the home office. So, on April 4, I forked off a new-tutorial branch and started a rather large overhaul that, among others, resulted in the operators' guide with its precarious position between tutorial and reference being largely absorbed into the tutorial. In all, off and on over the last few months I accumulated (according to git diff --shortstat 6372 inserted and 3453 deleted lines in the tutorial's source. Since that source currently is 7762 lines, I'd say that's the complete makeover I had promised. Which is good as e-inf-astro will be over next Wednesday (but don't worry, our work is still funded).

    So – whether you are a DaCHS expert, think about running it, or if you're just curious what it takes to build VO services, let me copy from index.html: Tutorial on importing data (tutorial.html,tutorial.pdf,tutorial.rstx). The ideal company for your vacation!

    And if you find typos, boring pieces, overly radical advocacy or anything else you don't like: there's a bug tracker for you (not to mention PRs are welcome).

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