Yes, I did, with -Xmx3100m (that's the maximum amount of memory I can allocate on that system for BaseX) and I got OOM.
On Sat, Oct 5, 2019 at 2:19 AM Christian Grün christian.gruen@gmail.com wrote:
About option 1: How much memory have you been able to assign to the Java VM?
first name last name randomcoder1@gmail.com schrieb am Sa., 5. Okt. 2019, 01:11:
I had another look at the script I wrote and realized that it's not working as it's supposed to. Apparently the order of operations should be this:
- turn on all the types of indexes required
- create the db
- the parser settings and the filter settings
- add all the files to the db
- run "OPTIMIZE"
If I'm not doing them in this order (specifically with "OPTIMIZE" at the end) the resulting db lacks all indexes.
On Fri, Oct 4, 2019 at 11:32 PM first name last name < randomcoder1@gmail.com> wrote:
Hi Christian,
About option 4: I agree with the options you laid out. I am currently diving deeper into option 4 in the list you wrote. Regarding the partitioning strategy, I agree. I did manage however to partition the files to be imported, into separate sets, with a constraint on max partition size (on disk) and max partition file count (the number of XML documents in each partition). The tool called fpart [5] made this possible (I can imagine more sophisticated bin-packing methods, involving pre-computed node count values, and other variables, can be achieved via glpk [6] but that might be too much work). So, currently I am experimenting with a max partition size of 2.4GB and a max file count of 85k files, and fpart seems to have split the file list into 11 partitions of 33k files each and the size of a partition being ~ 2.4GB. So, I wrote a script for this, it's called sharded-import.sh and attached here. I'm also noticing that the /dba/ BaseX web interface is not blocked anymore if I run this script, as opposed to running the previous import where I run CREATE DB db_name /directory/ which allows me to see the progress or allows me to run queries before the big import finishes. Maybe the downside is that it's more verbose, and prints out a ton of lines like
ADD /share/Public/archive/tech-sites/
linuxquestions.org/threads/viewtopic_9_356613.html Resource(s) added in 47.76 ms. along the way, and maybe that's slower than before.
About option 1: Re: increase memory, I am running these experiments on a low-memory, old, network-attached storage, model QNAP TS-451+ [7] [8], which I had to take apart with a screwdriver to add 2GB of RAM (now it has 4GB of memory), and I can't seem to find around the house any additional memory sticks to take it up to 8GB (which is also the maximum memory it supports). And if I want to find like 2 x 4GB sticks of RAM, the frequency of the memory has to match what it supports, I'm having trouble finding the exact one, Corsair says it has memory sticks that would work, but I'd have to wait weeks for them to ship to Bucharest which is where I live. It seems like buying an Intel NUC that goes up to 64GB of memory would be a bit too expensive at $1639 [9] but .. people on reddit [10] were discussing some years back about this supermicro server [11] which is only $668 and would allow to add up to 64GB of memory. Basically I would buy something cheap that I can jampack with a lot of RAM, but a hands-off approach would be best here, so if it comes pre-equipped with all the memory and everything, would be nice (would spare the trouble of having to buy the memory separate, making sure it matches the motherboard specs etc).
About option 2: In fact, that's a great idea. But it would require me to write something that would figure out the XPath patterns where the actual content sits. I actually wanted to look for some algorithm that's designed to do that, and try to implement it, but I had no time. It would either have to detect the repetitive bloated nodes, and build XPaths for the rest of the nodes, where the actual content sits. I think this would be equivalent to computing the "web template" of a website, given all its pages. It would definitely decrease the size of the content that would have to be indexed. By the way, here I'm writing about a more general procedure, because it's not just this dataset that I want to import.. I want to import heavy, large amounts of data :)
These are my thoughts for now
[5] https://github.com/martymac/fpart [6] https://www.gnu.org/software/glpk/ [7] https://www.amazon.com/dp/B015VNLGF8 [8] https://www.qnap.com/en/product/ts-451+ [9] https://www.amazon.com/Intel-NUC-NUC8I7HNK-Gaming-Mini/dp/B07WGWWSWT/ [10] https://www.reddit.com/r/sysadmin/comments/64x2sb/nuc_like_system_but_with_6... [11] https://www.amazon.com/Supermicro-SuperServer-E300-8D-Mini-1U-D-1518/dp/B01M...
On Thu, Oct 3, 2019 at 1:30 PM Christian Grün christian.gruen@gmail.com wrote:
Exactly, it seems to be the final MERGE step during index creation that blows up your system. If you are restricted to the 2 GB of main-memory, this is what you could try next:
- Did you already try to tweak the JVM memory limit via -Xmx? What’s
the largest value that you can assign on your system?
- If you will query only specific values of your data sets, you can
restrict your indexes to specific elements or attributes; this will reduce memory consumption (see [1] for details). If you observe that no indexes will be utilized in your queries anyway, you can simply disable the text and attribute indexes, and memory usage will shrink even more.
- Create your database on a more powerful system [2] and move it to
your target machine (makes only sense if there’s no need for further updates).
- Distribute your data across multiple databases. In some way, this
is comparable to sharding; it cannot be automated, though, as the partitioning strategy depends on the characteristics of your XML input data (some people have huge standalone documents, others have millions of small documents, …).
[1] http://docs.basex.org/wiki/Indexes [2] A single CREATE call may be sufficient: CREATE DB database sample-data-for-basex-mailing-list-linuxquestions.org.tar.gz
On Thu, Oct 3, 2019 at 8:53 AM first name last name randomcoder1@gmail.com wrote:
I tried again, using SPLITSIZE = 12 in the .basex config file The batch(console) script I used is attached mass-import.xq This time I didn't do the optimize or index creation post-import, but
instead, I did it as part of the import similar to what
is described in [4]. This time I got a different error, that is,
"org.basex.core.BaseXException: Out of Main Memory."
So right now.. I'm a bit out of ideas. Would AUTOOPTIMIZE make any
difference here?
Thanks
[4] http://docs.basex.org/wiki/Indexes#Performance
On Wed, Oct 2, 2019 at 11:06 AM first name last name <
randomcoder1@gmail.com> wrote:
Hey Christian,
Thank you for your answer :) I tried setting in .basex the SPLITSIZE = 24000 but I've seen the
same OOM behavior. It looks like the memory consumption is moderate until when it reaches about 30GB (the size of the db before optimize) and
then memory consumption spikes, and OOM occurs. Now I'm trying with
SPLITSIZE = 1000 and will report back if I get OOM again.
Regarding what you said, it might be that the merge step is where
the OOM occurs (I wonder if there's any way to control how much memory is being used inside the merge step).
To quote the statistics page from the wiki: Databases in BaseX are light-weight. If a database limit is
reached, you can distribute your documents across multiple database instances and access all of them with a single XQuery expression.
This to me sounds like sharding. I would probably be able to split
the documents into chunks and upload them under a db with the same prefix, but varying suffix.. seems a lot like shards. By doing this
I think I can avoid OOM, but if BaseX provides other, better, maybe
native mechanisms of avoiding OOM, I would try them.
Best regards, Stefan
On Tue, Oct 1, 2019 at 4:22 PM Christian Grün <
christian.gruen@gmail.com> wrote:
> > Hi first name, > > If you optimize your database, the indexes will be rebuilt. In this > step, the builder tries to guess how much free memory is still > available. If memory is exhausted, parts of the index will be split > (i. e., partially written to disk) and merged in a final step. > However, you can circumvent the heuristics by manually assigning a > static split value; see [1] for more information. If you use the
DBA,
> you’ll need to assign this value to your .basex or the web.xml file > [2]. In order to find the best value for your setup, it may be
easier
> to play around with the BaseX GUI. > > As you have already seen in our statistics, an XML document has > various properties that may represent a limit for a single database. > Accordingly, these properties make it difficult to decide for the > system when the memory will be exhausted during an import or index > rebuild. > > In general, you’ll get best performance (and your memory consumption > will be lower) if you create your database and specify the data to
be
> imported in a single run. This is currently not possible via the
DBA;
> use the GUI (Create Database) or console mode (CREATE DB command) > instead. > > Hope this helps, > Christian > > [1] http://docs.basex.org/wiki/Options#SPLITSIZE > [2] http://docs.basex.org/wiki/Configuration > > > > On Mon, Sep 30, 2019 at 7:09 AM first name last name > randomcoder1@gmail.com wrote: > > > > Hi, > > > > Let's say there's a 30GB dataset [3] containing most
threads/posts from [1].
> > After importing all of it, when I try to run /dba/db-optimize/ on
it (which must have some corresponding command) I get the OOM error in the stacktrace attached. I am using -Xmx2g so BaseX is limited to 2GB of memory (the machine I'm running this on doesn't have a lot of memory).
> > I was looking at [2] for some estimates of peak memory usage for
this "db-optimize" operation, but couldn't find any.
> > Actually it would be nice to know peak memory usage because.. of
course, for any database (including BaseX) a common operation is to do server sizing, to know what kind of server would be needed.
> > In this case, it seems like 2GB memory is enough to import 340k
documents, weighing in at 30GB total, but it's not enough to run "dba-optimize".
> > Is there any info about peak memory usage on [2] ? And are there
guidelines for large-scale collection imports like I'm trying to do?
> > > > Thanks, > > Stefan > > > > [1] https://www.linuxquestions.org/ > > [2] http://docs.basex.org/wiki/Statistics > > [3]
https://drive.google.com/open?id=1lTEGA4JqlhVf1JsMQbloNGC-tfNkeQt2