That phrase "main memory updates" also implies there's something I should learn.

Maybe it’s also something I should still find a better wording for ;) Previously, we have used the unfortunate term "non-updating update expression", and we now refer to it as "Main-Memory Updates" [1]. It describes updates on XML nodes that will not affect the persistent database storage, but will be returned to the user as an updated XML node.

A persistent update:
  delete nodes db:open('db')//text()

A main-memory update:
  db:open('db') update {
    delete nodes .//text()
  }

If you perform numerous updates, it’s sometimes faster to update a main-memory copy and replace the original node with the updated one:

  let $node := db:open('db')/path/to/node
  let $updated-node := $node update { ..... }
  return replace node $node with $updated-node

But the major advantage of this pattern is that you can perform additional operation on the updated node (validations, optimizations, reports) before eventually writing it to disk.

Hope this helps,
Christian

[1] https://docs.basex.org/wiki/XQuery_Update#Main-Memory_Updates


 
  I am simply doing updates using a repository.  Should I be doing something to trigger main memory updates?  

FWIW, here is a small sample of my data (one sentence) and the query I use to expand a morphology code in each <w> element into meaningful, readable attributes.  So a <w> element in the output looks like this:

<w pos="preposition" n="010010010011" morph="R" lang="H" lemma="b">בְּ</w>
<w pos="noun" type="common" gender="feminine" number="singular" state="absolute" n="010010010012" morph="Ncfsa" lang="H" lemma="7225" after=" ">רֵאשִׁית</w>
<w pos="verb" stem="qal" type="qatal" person="third" gender="masculine" number="singular" n="010010010021" lang="H" after=" " lemma="1254 a" morph="Vqp3ms" id="01Nvk">בָּרָ֣א</w>
<w pos="noun" type="common" gender="masculine" number="plural" state="absolute" n="010010010031" lang="H" after=" " lemma="430" morph="Ncmpa" id="01TyA">אֱלֹהִ֑ים</w>
<w pos="particle" type="direct object marker" n="010010010041" lang="H" after=" " lemma="853" morph="To" id="01vuQ">אֵ֥ת</w>
<w pos="particle" type="definite article" n="010010010051" morph="Td" lang="H" lemma="d">הַ</w>
<w pos="noun" type="common" gender="masculine" number="plural" state="absolute" n="010010010052" morph="Ncmpa" lang="H" lemma="8064" after=" ">שּׁמַ֖יִם</w>
<w pos="conjunction" n="010010010061" morph="C" lang="H" lemma="c">וְ</w>
<w pos="particle" type="direct object marker" n="010010010062" morph="To" lang="H" lemma="853" after=" ">אֵ֥ת</w>
<w pos="particle" type="definite article" n="010010010071" morph="Td" lang="H" lemma="d">הָ</w>
<w pos="noun" type="common" gender="both" number="singular" state="absolute" n="010010010072" morph="Ncbsa" lang="H" lemma="776" after=":">אָֽרֶץ</w>

These are leaf nodes in a syntax tree - for simplicity, I am not showing the syntax tree here, look to the input file for that.

Jonathan

On Tue, Feb 22, 2022 at 8:57 AM Christian Grün <christian.gruen@gmail.com> wrote:
A little announcement: With BaseX 10 [1], main memory updates will get much faster:

<x>{
  (1 to 1000000) ! <y/>
}</x> update {
  y ! (insert node <z/> into .)
}

BaseX 9: ages (6-7 minutes)
BaseX 10: 3 seconds

The reason: The disk-based block storage layout is now also used for the main memory representation of XML nodes.



On Tue, Feb 22, 2022 at 9:49 AM ETANCHAUD Fabrice <fabrice.etanchaud@maif.fr> wrote:
Hi Jonathan !

Apologizes for my late contribution...

Do you really have to use XQuery Update ? Do you have to stick to a specific format ?
If not, maybe you could use a schema on read approach ?
I mean, you could add new data as new documents,
and recombine these documents into the attribute based format when requesting the data.

Would that be a viable solution for you ?

I once had success with this solution, as BaseX is very quick at adding documents.

Best regards,
Fabrice


De : BaseX-Talk <basex-talk-bounces@mailman.uni-konstanz.de> de la part de Eliot Kimber <eliot.kimber@servicenow.com>
Envoyé : lundi 21 février 2022 18:06
À : BaseX <basex-talk@mailman.uni-konstanz.de>
Objet : Re: [basex-talk] Faster in the cloud?
 

You can use prof:track() to time your insertion operation for enough iterations to get a reasonable time and then multiply by 2.5 million to get an approximate time to completion.

 

On my machine I’m finding times around 0.05 seconds for my operations, which are more than just attribute insertions, where I need to do 40K iterations. I would expect attribute insertion to be faster, especially if you can batch up the insertions into a small number of transactions.

 

But five hours to do the update doesn’t seem entirely out of spec if your machine is significantly slower. Doing the math, I get 7ms per insertion:

 

Hours

Seconds/ Hour

Seconds

# operations

Time/operation

5

3600

18000

2500000

0.0072

 

That seems pretty fast on a per-operation standpoint.

 

If you can break your content into multiple databases you could parallelize the updates across multiple BaseX instances and then combine the result back at the end.

 

So spin up one server for each core, have a master server that provides a REST API to kick off the processing and then use the REST method to farm jobs out to each of the servers (using REST to make it easy to target each of the servers via a port. Could also do it from a shell script through the baseclient command-line.).

 

With that should be able to reduce the processing to the time it takes one server to process its share, which will be total objects/number of cores (its share, that is).

 

Cheers,

 

E.

 

_____________________________________________

Eliot Kimber

Sr Staff Content Engineer

O: 512 554 9368

M: 512 554 9368

servicenow.com

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From: BaseX-Talk <basex-talk-bounces@mailman.uni-konstanz.de> on behalf of Jonathan Robie <jonathan.robie@gmail.com>
Date: Monday, February 21, 2022 at 8:44 AM
To: Liam R. E. Quin <liam@fromoldbooks.org>
Cc: BaseX <basex-talk@mailman.uni-konstanz.de>
Subject: Re: [basex-talk] Faster in the cloud?

[External Email]

 

I have a 2013 Macbook Pro with 16 Gig RAM and a 1 Terabyte SSD.  So not entirely wimpy, but nowhere near as fast as the current Macbooks, I have no idea how that compares to a typical laptop these days.  Most things run fairly quickly, but inserting 2.5 million attributes into a document takes perhaps 5 hours, I didn't time it.  I can run that overnight, and do test runs on smaller subsets, but I want to think through my options.

 

Jonathan

 

On Sat, Feb 19, 2022 at 6:11 PM Liam R. E. Quin <liam@fromoldbooks.org> wrote:

On Sat, 2022-02-19 at 16:05 -0500, Jonathan Robie wrote:
> If I am running my queries and updates on a typical laptop, would
> they run much faster if I ran them on a suitably configured instance
> in the cloud?

"suitably configured" is very subjective.  Potentially your queries
could run a lot faster.

A lot depends on the speed of the disk (or SSD) in the laptop, and the
amount of memory it has, as well as the CPU - a recent Macbook Pro will
be faster than a ten-year-old chromebook.  However, server blades (the
machines used in data centres) typically have much higher bandwidth
between memory and devices including both the CPU and the long-term
storage, and likely have more physical RAM than your laptop.

On the other hand, connecting over the network to the cloud can be
slow....

Liam

--
Liam Quin, https://www.delightfulcomputing.com/
Transformers team, Paligo.net

Pictures from old books - www.fromoldbooks.org